A study on the impact of soft location factors in the relocation of service and manufacturing firms

An, Yi; Kang, Yeonggyeong; Lee, Seungil

doi:10.1080/12265934.2014.893834

Cited by 13 publications

(14 citation statements)

References 7 publications

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“…Hasil studi empiris membuktikan bahwa pendekatan teori klasik masih tetap diacu sebagai pendekatan normatif dalam pemilihannya (Kimelberg & Nicoll, 2012). Penelitian terhadap industri manufaktur di Kawasan Metropolitan Seoul menunjukkan bahwa faktor lokasi tradisional atau yang sering disebut sebagai hard factors masih merupakan variabel yang berpengaruh (An, Kang, and Lee, 2014). Kriteria pasar tenaga kerja, pasar produk, dan biaya produksi masih dipertimbangkan sebagai sebagai faktor penting untuk menentukan lokasi aktivitas produksi industri konstruksi di Polandia (Szymanska & Plaziak, 2014) dan pengembangan industri yang berbasis produk pertanian lokasi industri gula dan etanol di Brazil masih menekankan kedekatannya pada sumber input (Bargos et al, 2016).…”

Section: Arah Baru Pendekatan Lokasi Industriunclassified

“…Kesepuluh faktor yang berpengaruh terhadap pemilihan lokasi IBPL di Kabupaten Banyumas cenderung menunjukkan ciri industri tradisional/ traditional industries sebagaimana disampaikan oleh Gatfield & Yang (2006) atau dipengaruhi oleh faktor lokasi tradisional yang biasa disebut hard factors (An et al, 2014). Ciri yang mengarah kepada new emerging industries hanya sedikit ditunjukkan oleh beberapa industri, dalam hal ini elemen ketergantungan bahan baku/ kedekatan jarak terhadap bahan baku yang cenderung rendah karena pengaruh kemajuan teknologi transportasi.…”

Section: Hasil Dan Pembahasanunclassified

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Preferensi Lokasi Industri Berbasis Potensi Lokal Di Kabupaten Banyumas

Tsani

Nugroho

2019

tataloka

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Locations for industrial development in Indonesia often determined by spatial allocation policies than the needs of industrial players. This creates a gap between the industrial spatial allocation stated in regulation and location needs of industrial actors. That indicated by the rejection of offerings location by industrial actors. The industry is a business activity and its location chosen in the most favourable place and influenced by the location factors. However, industrial location decisions not only emphasizes to the preferences of the perpetrators but also influenced by strategies and policies within the larger organizational environment of central and local governments. A quantitative approach used in this study to assess the location preferences of local-based industries (IBPL) in Banyumas Regency, Central Java Province, Indonesia. The objective is to evaluate the local spatial regulation of industrial allocation zones so that the gap can be reduced. The study findings revealed that IBPL site preferences related to the local content of industrial characteristics and industrial scales. Medium and large IBPLs indicated to clustered; their location preferences tend to close to the supplier industries and located in the main of roads. The spatial distribution of small-scales IBPL sites show the symptoms of spontaneous location. It influenced by factor of local potential accessibility of labor. There are ten location factors affecting IBPL site selection and lean to show the dependence element of traditional industry characteristics. The most influential location factors are accessibility to the local potencies and accessibility to the business networks.

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Section: Arah Baru Pendekatan Lokasi Industriunclassified

Section: Hasil Dan Pembahasanunclassified

Preferensi Lokasi Industri Berbasis Potensi Lokal Di Kabupaten Banyumas

Tsani

Nugroho

2019

tataloka

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“…Another important line of research investigates the change of firms from the life-cycle perspective, i.e., the demography of firms [21][22][23][24][25]. Along the life-cycle development of firms, some changes may feature an explicit spatial dimension.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The independent variables are the city-level attributes. The selection of locational variables is informed by existing literature [24,27,[33][34][35]40,41]. To address the issue of spatial autocorrelation and select the appropriate regression model accordingly, we follow established methods [43] based on empirical data.…”

Section: Regression Analysismentioning

confidence: 99%

“…This category includes not only population and employment but also the density of firms in the same industry [24,27,33,35]. 'Human Capital' ensures that the level of education required for each type of manufacturing industry is different and has an effect on it [24,27,44,45]. It shows the skill and education level of the local workforce.…”

Section: Setting Independent Variablesmentioning

confidence: 99%

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Monitoring Spatial Changes in Manufacturing Firms in Seoul Metropolitan Area Using Firm Life Cycle and Locational Factors

Wan

2019

Sustainability

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This paper diagnoses the development of the manufacturing industry in the Seoul Metropolitan Area (SMA) using portfolio and regression analyses. Following the life-cycle perspective, four types of spatial changes of firms have been identified, namely firm formation, inflow, outflow, and dissolution, which are applied to analyze the manufacturing development in SMA. For portfolio analysis, we propose the Net Formation Index and Net Inflow Index to measure the spatial changes of firms at the city level. The two indices facilitate horizontal comparison among cities in SMA in terms of firm growth from new opening and relocation. Using spatial regression analysis, we identify significant location factors that contribute to firm change patterns. Our tests show that a high level of industrial specialization (measured by location quotient) has a dual effect. On the one hand, high level specialization attracts new or inflow firms, particularly in the light and high-tech manufacturing industries. On the other hand, it leads to an increased number of closed or outflow firms, plausibly due to increased competition among local firms. The proposed methods can be applied to diagnose industrial development in clusters of inter-connected cities and design policy tools to boost the local industry.

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