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Wednesday, 16 November 2016

A Study on the Growth and Management Status of Mansongjung forest in Hahoe, Andong

Published Date
Journal of Korean Nature
September 2011, Vol.4(3):161–171, doi:10.7229/jkn.2011.4.3.161
Open Access, Creative Commons license, Funding information

Author 
-jeong Kim ,
National Research Institute of Cultural Heritage, 396-1, Mannyeon-dong, Seo-gu, Daejeon 302-834, Korea
Received 22 July 2011. Revised 22 August 2011. Accepted 29 August 2011. Available online 2 December 2014.

Abstract

A village forest is a place for intentional purposes with natural and ecological grounds including history, culture and faith. The study investigates and analyzes land use, soil status, flora, vegetation, disease and insects, uses and management of Mansongjeong (pine tree) forest in Hahoe, Andong designated as natural monument for the purpose of preserving the Village forest. This diagnoses current vegetation of the forest and secures basic information to propose sustainable management. The land use analysis showed that wetlands and streams around the forest accounted for 44.2%, peripheral environment with high humidity and the soil analysis stated that the pH was proper but organic materials, total nitrogen and effective phosphorous reached below the average or overfeeding. The flora consists of 119 kinds including 37 families, 13 varieties, 1 species and 1 frost aster (Aster pilosus Willd) and there are 22 naturalized species. The vegetation stated that there were 859 Pine trees (Pinus densiflora), 6 zelkovas (Zelkova serrata), 1 nut tree (Castanea crenata) and 1 plum tree (Prunus mume), showing that the pine trees dominated in the upper part of the forest. There shall be consideration for new or existing forest with tree planting by excluding factors which may affect traditional tree-planting pattern in region with old trees and forming natural generation congress in the future. Pest research discovered that there were 9 kinds including Rhyacionia duplana (Hubner), aphids, mites, Tomicus piniperda (Linne) and zelkova silverfish. Usage and management results showed that the number of visitors was small but sharply increased during the festival season of Hahoe Village and there were 14 facilities in 2 kinds. A project on protecting the forest was designated and performed once in 2006. Systemic and pest managements considering ecological features of shade intolerant trees like pine trees through proper light penetration and adjusting crowd rates and regulating number of visitors are required to sustain the Mansongjeong Forest.

Keywords

  • Value preservation
  • village forest
  • protection project
  • natural monument

  • cultural propertie

  • References

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        Citing articles (1)
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        Citing articles (5)
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      • J.W. Choi, D.Y. Kim
      • Perspectives on the Landscape Ecological Function of Dangsan Forests and Rural Community Forests as a Stream Landscape
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      • View Record in Scopus
        Citing articles (1)
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      • J.W. Choi, D.Y. Kim
      • Preparation of Data for Restoration of Dangsan Forests and Rural Community Forests from the Case Study of Hanbam and Goiran Villages
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      • www.kma.go.kr
      • www.kma.go.kr

    • * 
      To whom correspondence should be addressed. Tel: +82-42-610-7621
    Copyright © 2011 Korean Biodiversity Information Facility. Production and hosting by Elsevier B.V.
    Open access funded by Korean Biodiversity Information Facility (KBIF) in National Science Museum of Korea and Korea National Arboretum (KNA)

    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/S1976864814600748
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    Study for selection of industrial areas suitable to small and medium-sized enterprises (SMEs) in Korea

    Published Date
    Journal of Open Innovation: Technology, Market, and ComplexityTechnology, Market, and Complexity20162:19
    DOI: 10.1186/s40852-016-0045-9
    ©  The Author(s). 2016
    Received: 6 July 2016
    Accepted: 3 September 2016
    Published: 27 September 2016

    Author

  • Jun-Hwan Park, 
  • Bangrae Lee, 
  • Yeong-Ho Moon and 
  • Lee-Nam Kwon

    • View ORCID ID profil
    Abstract 
    In this study, the investigation into basic methodology for selecting the industrial areas suitable to the small and medium-sized enterprises (SMEs) in Korea was performed by using the statistical data about the corporations (2010 ~ 2012) as the quantitative evidences containing the number of companies, the number of workers, the annual sales, and the indices of market concentration and growth potential. From the Statistics Korea and the KISTI Market Analysis and Prediction System (K-MAPS), the statistical data organized by the Korean Standard Industrial Classification (KSIC) were obtained to conduct this research through the following procedure. First of all, the numbers of enterprises and employees and the annual sales of all industries were investigated and the largest number of workers and the highest annual sales were found in the sector of manufacturing among all sectors of KSIC. Secondly, the top three divisions with the highest annual sales in all divisions of manufacturing sector were selected. Thirdly, the subclasses having high values of annual sales and SMEs proportions among all subclasses in the top three divisions of the previous step were chosen as the candidates of SMEs-recommendable fields. Fourthly, the degree of market concentration was analyzed by using three-firm concentration ratio (CR3) and Herfindahl-Hirschman index (HHI) of the selected subclasses. Finally, the study for growth potential of chosen subclasses was performed through the analysis of compound annual growth rate (CAGR). After the overall process of this study was carried out with the synthetic consideration of the above-mentioned factors, the three subclasses of KSIC as industrial areas suitable to the SMEs could be found: (1) Manufacture of printed circuit boards, (2) Manufacture of parts and accessories for motor engines, and (3) Manufacture of parts and accessories for motor vehicle body. From this result, it was found that the values of annual sales, CR3, HHI, and CAGR can be very useful factors to discover the recommendable industry fields to the SMEs.

    Keywords

    Small and medium-sized enterprises (SMEs) SMEs-suitable areas Three-firm concentration ratio (CR3) Herfindahl-Hirschman index (HHI) Compound annual growth rate (CAGR)

    Introduction

    Promising industry and emerging technology have attracted much attention by government and companies because the innovation of industry and technology is being made with rapid progress under the globalization of world economy. For this reason, government and corporations should find the promising industry and technology appropriate to the future demand by obtaining the competitiveness in order to maintain the sustainable growth. To achieve this purpose, the studies for innovation have been widely performed in recent years (Guan and Ma, 2003; Martensen et al., 2007; Tura et al., 2008; Forsman, 2009; Paalanen et al., 2009; Damanpour, 2010; Forsman and Rantanen, 2011; Oganisjana, 2015; Yusr, 2016; Yun et al., 2016). In addition, the effect of research and development (R&D) support has been studied with great attention (Belderbos et al., 2004; Cassiman and Veugelers, 2005; Czarnitzki et al., 2007; Aerts and Schmidt, 2008; Hussinger, 2008; Czarnitzki and Hottenrott, 2011; Takalo et al., 2013; Kang and Cho, 2016; Kim et al., 2016). In order to accomplish the innovation capability and the R&D support in the perspective of small and medium-sized enterprises (SMEs) for finding the prospective areas, they depends on the announcement of promising industry and technology from government and public institutions. Since the SMEs have the limitations of manpower and resources, it is difficult for them to search for the promising fields autonomously. However, many fields of industry and technology which are not suitable to the SMEs are included in the prospective areas presented by government and public institutions. This is because the procedure to choose the promising industry and technology by government and public institutions is mostly dependent on the opinion of experts (ex. Delphi method). Also, in Korea, the polarization between large corporations and SMEs has not been solved yet. It is induced by rapid expansion of business field for major companies. Therefore, for the survival of SMEs in present and future market, it is necessary to develop the basic methodology of finding the SMEs-recommendable areas.
    Hottenrott and Lopes-Bento (2014) investigated the impact and the influence of targeted public R&D support in the level of company and they observed the effect of policy-induced R&D investment on the sales from the market novelties in the viewpoint of international collaborators and SMEs. In addition, they found the contribution of R&D support from public subsidies to innovation performance of SMEs. Saunila and Ukko (2014) studied the intangible factors in the innovation capability of SMEs by utilizing a web-based questionnaire. The results from their research demonstrated that the intangible aspects in the innovation capability of SMEs are not influenced by their size and industry. Due to this reason, the SMEs are able to have a higher potential for innovation than major companies. Ahmedova (2015) carried out the research for the factors to improve the competitiveness of SMEs. In this reference, the reason for the focal point on the SMEs was that their business areas are very significant to develop the national economics. It is because the SMEs have the great potential of flexible adaptation to market situation. The author found the main features helpful to enhance the competitiveness of companies: access to finance, innovation activities, internationalization, and so on.
    The goal of this research is the establishment of basic methodology for selecting the candidates of promising fields appropriate to the SMEs in Korea systemically by utilizing the statistical data as the quantitative evidences. For achievement of this purpose, annual sales, three-firm concentration ratio (CR3), Herfindahl-Hirschman index (HHI), and compound annual growth rate (CAGR) of corporations were used and the analyses for those factors were performed with the Korean Standard Industrial Classification (KSIC).

    Data and methodology

    Data

    Two kinds of statistical data were used in this study: (1) public data (2010) gained in the Statistics Korea and (2) processed data (2010 ~ 2012) in the KISTI Market Analysis and Prediction System (K-MAPS). Both data are based on the KSIC. The KSIC is the systematic classification for industrial activities of Korean corporations according to their similarity. There are 5 levels in the KSIC composed of sector (1-digit level, alphabet), division (2-digit level), group (3-digit level), class (4-digit level), and subclass (5-digit level) and the numbers of each level are 21, 76, 228, 487, and 1,145, respectively. The statistical data of all firms in Korea including their data (ex. the number of companies, the number of employees, the annual sales, the business profits, and so on) could be obtained from the Korean Statistical Information Service (KOSIS) which is a core service site of the Statistics Korea. For the production of this public data, the Economic Census for investigation of all enterprises by the Statistics Korea is being performed in every 5 years. Therefore, the statistical data for 2010 is the newest now and the data about 2015 will be provided in 2017 after the survey for all enterprises of Korea in 2016. For this reason, the public data for all companies of 2010 was used in this research. Furthermore, the data for subclass level of manufacturing sector of KSIC related to market analysis (ex. annual sales, CR3, and HHI) could be gained from the K-MAPS site. Those data about market analysis from 2010 to 2012 were produced by utilizing the database of corporate finance (about 370,000 companies in the manufacturing sector) provided by the Korea Enterprise Data (KED).

    Methodology

    In this research, four factors (annual sales, three-firm concentration ratio (CR3), Herfindahl-Hirschman index (HHI), compound annual growth rate (CAGR) of sales) having effects on the selection of industrial areas suitable to the SMEs were considered and they are listed with their definition and usefulness (Table 1). By taking account of those factors synthetically, the industrial areas appropriate for the SMEs in Korea were chosen through the following process. First of all, the number of enterprises, the number of workers, and the annual sales of all KSIC sectors in 2010 were utilized to find the industrial area with the highest values of those factors because they can be the typical indicators for measuring the market size of each industrial field. Secondly, among all divisions of manufacturing sector found as the industrial area having the largest number of employees and the highest annual sales, top three divisions with the highest value of annual sales were selected. Thirdly, the annual sales and the SMEs proportions were used as indices to choose the industrial areas among all subclasses in the top three divisions. Fourthly, the values of CR3 and HHI from 2010 to 2012 were employed for analyzing the market concentration of chosen subclasses in the manufacturing sector of KSIC. The details of CR3 and HHI will be explained in the next section. Finally, the CAGR of sales (period of time: 2010 ~ 2012) was used to figure out the growth potential of selected subclasses. After the procedure of this basic methodology, it was possible to find the SMEs-recommendable industrial areas.
    Table 1
    Introduction to various factors influencing the selection of SMEs-recommendable industry areas based on the KSIC
    Factor
    Definition
    Usefulness
    Annual sales
    Amount of income from selling goods or providing services during 1 year
    One of the representative indicators for the market size of industry
    Three-firm concentration ratio (CR3)
    Total market share (%) of top three companies
    Evidence for the degree of market concentration
    Herfindahl-Hirschman Index (HHI)
    Sum of squared value of market share percentage
    Evidence for the degree of market concentration
    Compound Annual Growth Rate (CAGR) of sales
    Mean annual growth rate of sales over a specified period of time
    Evidence for the growth potential of industry

    CR3 and HHI

    The value for CR is the sum of market shares from a specified number of companies (Calkins, 1983). In this research, the CR3 (CR value of three largest firms in the market share) was utilized and this can be gained by using the following equation.
    CR3 (%)=∑i=13MSiCR3 %i13MSi
    (1)
    In this formula, the MS i means the market share of individual enterprise with the ith highest value. The higher value of CR3 for a certain market area indicates that the market is more concentrated. However, the value of CR3 has a limitation in its application for analyzing the market concentration because the remaining corporates excluding top 3 firms are not considered (Sys, 2009). To compensate this deficiency of CR3, the value of HHI is also used in the analysis of the market concentration and it can be calculated from the following equation (Calkins, 1983).
    HHI=∑i=1nMSi2HHIi1nMSi2
    (2)
    In this equation, n is the number of companies and the unit of MS i value is the percentage. As presented in Equation (2), the market shares of all enterprises are considered in obtaining the value of HHI. Thus, both CR3 and HHI should be taken into account for analyzing the market concentration. Furthermore, the HHI value can be utilized as a criterion showing the degree of market concentration (Calkins, 1983; Sys, 2009; Titilayo and Victor, 2014). (1) When the HHI value is lower than 1,000, the market is unconcentrated. (2) The value of HHI between 1000 and 1800 indicates the moderate concentration of market. (3) When the HHI value is 1800 or more, it means that the market is highly concentrated. In order to find the SMEs-recommendable industry areas by using the statistical data about companies, the values of CR3 and HHI showing the degree of market concentration were utilized in this research.

    Results and discussion

    Investigation into the statistical data for all enterprises in the levels of sector and division of the KSIC

    The numbers of companies and employees and the annual sales of all industries and 21 sectors of KSIC could be obtained by using the statistical data of 2010 from the KOSIS of the Statistics Korea (Table 2). In addition, the proportions for those components were calculated. As presented in Table 2, the most numerous employees (3,417,698 people, 19.37 %) and the highest annual sales (1,464,336,545 million won, 33.80 %) of Korea in 2010 were found in the sector of manufacturing. From this statistical data, it is expected that the industrial area concerned with the manufacturing was the main field of Korea industry in 2010. Therefore, the manufacturing sector of KSIC was chosen to research for the basic methodology to discover the appropriate industry area of SMEs in Korea.
    Table 2
    Numbers of companies and employees and annual sales of all industries and sectors (2010)
    KSIC code
    Sector of KSIC in all industries
    (a) Number of companies
    Ratio of (a) (%)
    (b) Number of employees
    Ratio of (b) (%)
    (c) Annual sales (Million won)
    Ratio of (c) (%)
     
    All industries
    3,355,470
    100.00
    17,647,028
    100.00
    4,332,292,658
    100.00
    A
    Agriculture, forestry, and fishing
    2354
    0.07
    30,418
    0.17
    9,207,983
    0.21
    B
    Mining and quarrying
    1770
    0.05
    16,377
    0.09
    3,650,007
    0.08
    C
    Manufacturing
    326,813
    9.74
    3,417,698
    19.37
    1,464,336,545
    33.80
    D
    Electricity, gas, steam, and water supply
    1499
    0.04
    66,267
    0.38
    120,556,744
    2.78
    E
    Sewerage, waste management, materials recovery, and remediation activities
    5402
    0.16
    69,132
    0.39
    14,474,084
    0.33
    F
    Construction
    96,833
    2.89
    1,180,659
    6.69
    271,063,929
    6.26
    G
    Wholesale and retail trade
    876,654
    26.13
    2,617,891
    14.83
    819,828,179
    18.92
    H
    Transportation
    347,179
    10.35
    992,546
    5.62
    147,571,423
    3.41
    I
    Accommodation and food service activities
    634,500
    18.91
    1,766,290
    10.01
    77,682,506
    1.79
    J
    Information and communications
    26,375
    0.79
    468,585
    2.66
    115,566,239
    2.67
    K
    Financial and insurance activities
    39,353
    1.17
    706,859
    4.01
    744,138,697
    17.18
    L
    Real estate activities and renting and leasing
    126,081
    3.76
    440,556
    2.50
    64,305,803
    1.48
    M
    Professional, scientific, and technical activities
    70,601
    2.10
    750,393
    4.25
    117,677,853
    2.72
    N
    Business facilities management and business support services
    35,910
    1.07
    788,674
    4.47
    36,393,804
    0.84
    O
    Public administration and defense; compulsory social security
    11,929
    0.36
    663,673
    3.76
    97,290,425
    2.25
    P
    Education
    165,964
    4.95
    1,420,892
    8.05
    84,001,584
    1.94
    Q
    Human health and social work activities
    107,012
    3.19
    1,084,758
    6.15
    69,552,877
    1.61
    R
    Arts, sports, and recreation related services
    102,948
    3.07
    322,881
    1.83
    34,228,991
    0.79
    S
    Membership organizations, repair, and other personal services
    376,293
    11.21
    842,479
    4.77
    40,764,985
    0.94
    T
    Activities of households as employers; undifferentiated goods- and services- producing activities of households for own use
    N/A
    N/A
    N/A
    N/A
    N/A
    N/A
    U
    Activities of extraterritorial organizations and bodies
    N/A
    N/A
    N/A
    N/A
    N/A
    N/A
    Since the properties of sector T and U are not applicable to compute the numbers of companies and employees and the sales, the values for them were not provided by the Statistics Korea
    Data source: Economic Census, Korean Statistical Information Service (KOSIS) which is a core service site of the Statistics Korea (http://kosis.kr)
    To find the top 3 divisions having the highest annual sales in 2010 among all divisions in the manufacturing sector, the values of their annual sales were compared (Table 3). The division in the first place for the annual sales was the KSIC code 26 (Manufacture of electronic components, computer, radio, television, and communication equipment and apparatuses, 17.98 %). As the second place, the KSIC code 30 (Manufacture of motor vehicles, trailers, and semitrailers) was observed (10.39 %). The KSIC code 24 (Manufacture of basic metal products) was in the third place (10.11 %). By utilizing these results, those three divisions were chosen for studying the proportion of SMEs in the annual sales.
    Table 3
    Annual sales and their ratio of manufacturing sector and its 24 divisions (2010)
    KSIC code
    Division in the manufacturing sector of KSIC
    Annual sales (Million won)
    Ratio (%)
    C
    Manufacturing
    1,464,336,545
    100.00
    10
    Manufacture of food products
    66,303,956
    4.53
    11
    Manufacture of beverages
    8,047,923
    0.55
    12
    Manufacture of tobacco products
    3,100,366
    0.21
    13
    Manufacture of textiles, except apparel
    26,372,142
    1.80
    14
    Manufacture of wearing apparel, clothing accessories, and fur articles
    23,015,703
    1.57
    15
    Tanning and dressing of leather, manufacture of luggage and footwear
    5,958,998
    0.41
    16
    Manufacture of wood and of products of wood and cork; except furniture
    6,603,706
    0.45
    17
    Manufacture of pulp, paper and paper products
    22,855,447
    1.56
    18
    Printing and reproduction of recorded media
    7,914,757
    0.54
    19
    Manufacture of coke, hard-coal and lignite fuel briquettes, and refined petroleum products
    113,218,854
    7.73
    20
    Manufacture of chemicals and chemical products except pharmaceuticals and medicinal chemicals
    124,063,180
    8.47
    21
    Manufacture of pharmaceuticals, medicinal chemicals, and botanical products
    14,210,794
    0.97
    22
    Manufacture of rubber and plastic products
    60,710,165
    4.15
    23
    Manufacture of other non-metallic mineral products
    37,852,453
    2.58
    24
    Manufacture of basic metal products
    148,078,592
    10.11
    25
    Manufacture of fabricated metal products, except machinery and furniture
    82,730,945
    5.65
    26
    Manufacture of electronic components, computer, radio, television, and communication equipment and apparatuses
    263,295,000
    17.98
    27
    Manufacture of medical, precision, optical instruments, and watches and clocks
    18,242,154
    1.25
    28
    Manufacture of electrical equipment
    70,066,678
    4.78
    29
    Manufacture of other machinery and equipment
    107,261,402
    7.32
    30
    Manufacture of motor vehicles, trailers, and semitrailers
    152,108,349
    10.39
    31
    Manufacture of other transport equipment
    83,082,252
    5.67
    32
    Manufacture of furniture
    12,359,000
    0.84
    33
    Other manufacturing
    6,883,729
    0.47
    Data source: Economic Census, Korean Statistical Information Service (KOSIS) which is a core service site of the Statistics Korea (http://kosis.kr)

    Research for the selected subclasses of manufacturing sector

    In order to examine the ratio of SMEs in the annual sales of 2010 among all subclasses contained in the top three divisions selected from Table 3, the values of annual sales were computed by using the analysis service of K-MAPS and the subclasses with relatively high annual sales were listed in Table 4. The reason for utilizing analysis service of the K-MAPS is that it provides the annual sales of individual corporates operating in the industrial fields related to the manufacturing sector of KSIC by using the business finance database of about 370,000 companies purchased from the KED. Furthermore, the value of market share for each company can be calculated by utilizing its annual sales (In the next section, the analysis for market concentration will be discussed.). Also, the values of annual sales for individual corporates are not provided in the KOSIS. For these reasons, the analysis of statistical data about each company in the K-MAPS was performed instead of that in the KOSIS. In addition, the number of workers was utilized to distinguish the SMEs in this study. The criterion number of employees in the manufacturing sector in order to separate the SMEs from the large enterprises is 300 people by applying the Basic Law for SMEs of Korea from 2010 to 2012. In other words, the number of employees in a corporate should be less than 300 people to be recognized as a SME of Korea in the sector of manufacturing from 2010 to 2012.
    Table 4
    Annual sales and their proportion of SMEs for the chosen subclasses (2010)
    KSIC code
    Subclass in the manufacturing sector of KSIC
    Annual sales (Million won)
    Proportion of SMEs (%)
    24121
    Manufacture of hot rolled, drawn, and extruded iron or steel products
    6,425,208
    23
    24132
    Manufacture of pipes and tubes of non-cast iron or steel
    13,902,211
    22
    24191
    Manufacture of guilt, coloration, surface processing steel materials
    2,162,861
    24
    24211
    Manufacture of smelting, refining, and alloys of copper
    8,945,571
    6
    24221
    Manufacture of rolled, drawn, and folded products of copper
    6,033,576
    26
    24222
    Manufacture of rolled, drawn, and folded products of aluminum
    7,151,018
    34
    26110
    Manufacture of electronic integrated circuits
    6,346,772
    27
    26120
    Manufacture of diodes, transistors, and similar semi-conductor devices
    24,335,270
    13
    26211
    Manufacture of liquid crystal flat display boards
    51,354,130
    4
    26221
    Manufacture of printed circuit boards
    6,579,265
    44
    26422
    Manufacture of mobile phone
    148,261,264
    0.4
    26511
    Manufacture of television
    2,972,917
    21
    30121
    Manufacture of passenger motor vehicles
    80,394,434
    0.01
    30310
    Manufacture of parts and accessories for motor engines
    9,379,206
    32
    30320
    Manufacture of parts and accessories for motor vehicle body
    9,071,525
    59
    30391
    Manufacture of power transmission for motor vehicles
    6,849,358
    31
    30392
    Manufacture of electrical equipment for motor vehicles
    1,446,523
    50
    The selected subclasses showed high annual sales among all subclasses contained in the top 3 divisions with the largest annual sales in Table 3 (2010): (1) Manufacture of electronic components, computer, radio, television, and communication equipment and apparatuses (17.98 %, KSIC code 26), (2) Manufacture of motor vehicles, trailers, and semitrailers (10.39 %, KSIC code 30), and (3) Manufacture of basic metal products (10.11 %, KSIC code 24)
    In Korea, to be recognized as a SME in the manufacturing sector, the number of employees should be less than 300 people (Application of the Basic Law for SMEs of Korea from 2010 to 2012)
    Data source: Analysis of market concentration, KISTI Market Analysis and Prediction System (K-MAPS) (http://kmaps.kisti.re.kr)
    As listed in Table 4, most subclasses showed higher ratio of SMEs than 20 % in the annual sales but the subclasses having very low proportions of SMEs in the annual sales were also found. From these results, total 5 subclasses with very low ratios of SMEs were excluded in the further analysis of market concentration: the KSIC code (1) 24211 (Manufacture of smelting, refining, and alloys of copper, 6 %), (2) 26120 (Manufacture of diodes, transistors, and similar semi-conductor devices, 13 %), (3) 26211 (Manufacture of liquid crystal flat display boards, 4 %), (4) 26422 (Manufacture of mobile phone, 0.4 %), and (5) 30121 (Manufacture of passenger motor vehicles 0.01 %). Also, the subclasses with “other” term in their designations were also excluded (not shown in Table 4) because they include so many kinds of industrial areas which cannot be classified elsewhere in the subclasses of KSIC: the KSIC code (1) 24199 (Manufacture of other basic iron and steel n. e. c.), (2) 26429 (Manufacture of other wireless telecommunication apparatuses), and (3) 30399 (Manufacture of other parts and accessories for motor vehicles n. e. c.). Through the above-mentioned process, total 12 subclasses were selected for the analysis of their market concentration.

    Analysis of the market concentration for the selected subclasses

    For studying the market concentration from 2010 to 2012 based on the annual sales of individual enterprises in the level of KSIC subclass, the processed data for the values of CR3 and HHI computed by utilizing the market share of individual corporates in the K-MAPS were used. As listed in Table 5, there were four subclasses showing the high values of HHI larger than 1800 with relatively high CR3 (from 56 to 94 %): the KSIC code (1) 24132 (Manufacture of pipes and tubes of non-cast iron or steel), (2) 24191 (Manufacture of guilt, coloration, surface processing steel materials), (3) 24221 (Manufacture of rolled, drawn, and folded products of copper), and (4) 26511 (Manufacture of television). These four subclasses were removed from the list of industrial areas appropriate to the SMEs because the values of CR3 and HHI should be low for the initial market penetration of SMEs. Also, it is expected that the market competition of the SME with other SMEs is much easier than that with major corporates having relatively high values of annual sales and market share. Therefore, it is important to analyze the statistical data relevant to the market environment including annual sales, CR3, and HHI synthetically in the level of KSIC subclass in order to discover the promising industry fields for the SMEs.
    Table 5
    Values of CR3 and HHI for the selected subclasses (2010 ~ 2012)
    KSIC code
    Subclass in the manufacturing sector of KSIC
    CR3 (%)
    HHI
    2010
    2011
    2012
    2010
    2011
    2012
    24121
    Manufacture of hot rolled, drawn, and extruded iron or steel products
    35
    35
    37
    770
    786
    836
    24132
    Manufacture of pipes and tubes of non-cast iron or steel
    59
    57
    57
    2326
    2210
    2148
    24191
    Manufacture of guilt, coloration, surface processing steel materials
    75
    72
    72
    2833
    2587
    2467
    24221
    Manufacture of rolled, drawn, and folded products of copper
    58
    56
    57
    1809
    1686
    1785
    24222
    Manufacture of rolled, drawn, and folded products of aluminum
    47
    48
    47
    1254
    1309
    1214
    26110
    Manufacture of electronic integrated circuits
    39
    39
    40
    1020
    1069
    1056
    26221
    Manufacture of printed circuit boards
    22
    22
    24
    944
    936
    925
    26511
    Manufacture of television
    89
    78
    94
    5909
    3866
    7459
    30310
    Manufacture of parts and accessories for motor engines
    29
    30
    31
    820
    797
    784
    30320
    Manufacture of parts and accessories for motor vehicle body
    19
    19
    20
    677
    643
    644
    30391
    Manufacture of power transmission for motor vehicles
    44
    46
    48
    1253
    1455
    1621
    30392
    Manufacture of electrical equipment for motor vehicles
    51
    53
    50
    1163
    1239
    1226
    As presented in Table 4, the chosen subclasses had 20 % or more proportion of SMEs in the annual sales
    Data source: Analysis of market concentration, KISTI Market Analysis and Prediction System (K-MAPS) (http://kmaps.kisti.re.kr)

    Study for tendency and CAGR of the annual sales from 2010 to 2012

    In order to perform the analysis for growth potential of the selected subclasses from Table 5, the tendency and the CAGR of annual sales from 2010 to 2012 were computed as listed in Table 6. For the discovery of SMEs-recommendable industry fields, the value of CAGR should be relatively high and the sales from 2010 to 2012 should be increased continuously. Among total 8 subclasses remaining in the previous step, very low values of CAGR were observed in three subclasses: the KSIC code (1) 24121 (Manufacture of hot rolled, drawn, and extruded iron or steel products, 1.01 %), (2) 24222 (Manufacture of rolled, drawn, and folded products of aluminum, -0.06 %), and (3) 26110 (Manufacture of electronic integrated circuits, 0.61 %). In addition, the high value of CAGR was found in the KSIC code 30391 (Manufacture of power transmission for motor vehicles, 10.92 %) but its annual sales from 2010 to 2012 did not show the continuous increment. From these results, total 4 subclasses with the high value of CAGR and the continuous increase in the annual sales were selected as the candidates of suitable areas to the SMEs: the KSIC code (1) 26221 (Manufacture of printed circuit boards, 14.89 %), (2) 30310 (Manufacture of parts and accessories for motor engines, 9.16 %), (3) 30320 (Manufacture of parts and accessories for motor vehicle body, 9.17 %), and (4) 30392 (Manufacture of electrical equipment for motor vehicles, 16.18 %).
    Table 6
    Annual sales and their values of CAGR for the chosen subclasses (2010 ~ 2012)
    KSIC code
    Subclass in the manufacturing sector of KSIC
    Annual sales (Million won)
    CAGR (%)
    2010
    2011
    2012
    24121
    Manufacture of hot rolled, drawn, and extruded iron or steel products
    6,425,208
    6,988,439
    6,555,231
    1.01
    24222
    Manufacture of rolled, drawn, and folded products of aluminum
    7,151,018
    7,554,277
    7,142,339
    -0.06
    26110
    Manufacture of electronic integrated circuits
    6,346,772
    6,587,213
    6,424,311
    0.61
    26221
    Manufacture of printed circuit boards
    6,579,265
    7,480,920
    8,684,789
    14.89
    30310
    Manufacture of parts and accessories for motor engines
    9,379,206
    11,077,627
    11,175,734
    9.16
    30320
    Manufacture of parts and accessories for motor vehicle body
    9,071,525
    10,709,960
    10,811,588
    9.17
    30391
    Manufacture of power transmission for motor vehicles
    6,849,358
    8,516,331
    8,426,627
    10.92
    30392
    Manufacture of electrical equipment for motor vehicles
    1,446,523
    1,805,942
    1,952,468
    16.18
    As listed in Table 5, the selected subclasses showed the HHI values lower than 1800
    Data source: Analysis of market concentration, KISTI Market Analysis and Prediction System (K-MAPS) (http://kmaps.kisti.re.kr)

    Selection of SMEs-recommendable industrial areas

    For the discovery of industrial fields appropriate to the SMEs, the values of annual sales, CR3, HHI, and CAGR should be taken into account synthetically. From this perspective, the subclass with the KSIC code 30392 (Manufacture of electrical equipment for motor vehicles) could not be listed in the industrial fields suitable to the SMEs because of its relatively high values of CR3 (51, 53 and 50 %) and HHI (1163, 1239 and 1226) from 2010 to 2012 compared to those of other three subclasses (The KSIC code 26221, 30310, and 30320). According to the position of SMEs, it is possible for them to choose the appropriate fields through the following two ways. The first one is that the SMEs can select the industrial area with higher CAGR when their first consideration is in its growth potential. In this case, the subclass of the KSIC code 26221 (Manufacture of printed circuit boards) is able to become the best field by following the basic methodology of this study. On the other hand, the second one is that the SMEs preferentially consider the stable entrance to the initial market having lower value of HHI. For this objective, the SMEs can choose the subclasses of the KSIC code 30310 (Manufacture of parts and accessories for motor engines) and 30320 (Manufacture of parts and accessories for motor vehicle body) as their prospective areas through the selection procedure of SMEs-recommendable industry area from this research. Thus, the SMEs can discover the suitable fields by applying their realistic position and purpose to the basic methodology of this study.

    Conclusions and future work

    This research was performed for the establishment of the basic methodology utilizing the statistical data as quantitative evidences. Through the overall procedure of this study, it was possible to select the SMEs-recommendable industry fields by considering their annual sales, market consideration (CR3 and HHI), and growth potential (CAGR). From the results of this study, it was found that those factors can be used as indicators to find the industrial areas suitable to the SMEs in Korea. However, the methodology of this study has the potential limits because it is difficult to reflect the market situation which can be changed suddenly in the near future. In order to overcome this defect, it is necessary to develop the methodology of this study as a further work under the consideration of more factors such as the business profits, the information about the number of enterprises founded or closed, the analysis of emerging industry/technology, and so on. Through the continuous development of the basic methodology studied in this study for the discovery of industrial areas appropriate to the SMEs, it will be very helpful for them to select the specific industry field with the value of investment having high annual sales or business profits, low market concentration, great potential of growth, and so on. Furthermore, from this research, the following influences on the SMEs can be accomplished: (1) improvement in their capabilities of business planning, (2) progress of their innovation, and (3) enhancement of investment efficiency in the national R&D for them.

    Declarations

    Acknowledgement

    This research was supported by the research project (Activation of research and development services through the establishment of information analysis platform, K-16-L02-C04-S01) funded by the Ministry of Science, ICT and Future Planning of Korea.

    Authors’ contributions

    All authors read and approved the final manuscript.

    Competing interests

    The authors declare that they have no competing interests.
    Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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