FIRM SIZE AND LOCATION CHOICE OF FOOD INDUSTRY: IZMIR/TURKEY CASE

Nilnaz AKBAŞOĞULLARI

MSc City Planner, Izmir, Turkey, Tel: +90 554 972 37 64

nilnazakb@gmail.com

Hasan Engin DURAN

(Corresponding Author) Izmir Institute of Technology, City and Regional Planning Department, Associate Professor of Economics, Adress: Gülbahce Kampüsü, Izmir Yüksek Teknoloji Ensitüsü, Mimarlık Fakültesi, Şehir ve Bölge Planlama Bölümü, Urla-Izmir, Tel: +90 232 750 70 04

enginduran@iyte.edu.tr

Abstract

Purpose of the current study is to analyze the determinants of firm location in Izmir’s food industry. The dataset covers 734 firms in 2018. The analyses particularly focus on the impact of experience and size of the firms, the effects of which are not yet adequately analyzed by the existing literature. In terms of methodologies, initially, explorative maps are used to illustrate the data. Then, linear regression analyses are applied to analyze the location behavior determinants. Spatial autocorrelation test is applied to as a robustness test. Our findings point to three main results. First, firm size is not statistically a significant determinant of firm location. So, big firms may locate in/around or out of cities, whereas, also small firms may locate close to or distant from city centers Second, the influence of the experience variable is rather definite; earlier founded firms naturally locate closer to CBD. Third, with regard to results regarding sub-sectors, firms in packaged food and bakery sectors locate nearby CBDs where, in contrast, firms in animal products sector tend to locate in rural areas. Overall, the key lesson that we learn from the analysis is that concentration of large firms around urban areas should be avoided so to cope with environmental problems and to maintain fair competition between big and small firms. Moreover, younger firms should be subsidized (through tax exemptions, rental aid, export and employment subsidies) so that their capital structure remains strong even if they are not able to place close to the market.

Keywords: Location Choice, Food Industry, Determinants, Firm Size

JEL classification: D22, R3

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EFFECTS ON EMPIRICAL ECONOMIC PERFORMANCE IN PROVINCIAL CLUSTER OF THE SOUTHERN SHORE OF THE GULF OF THAILAND

Kiatkajon CHAIRAT

Department of Management, Faculty of Management Technology, Rajamangala University of Technology Srivijaya, Nakhon Si Thammarat, Thailand Corresponding author: Kiatkajon Chairat Tel:+6681 870 0219

fmtkiat@gmail.com

Piya PECHSONG

Department of Management, Faculty of Management Technology, Rajamangala University of Technology Srivijaya, Nakhon Si Thammarat, Thailand

p_piya1@hotmail.com

Abstract

The aim of this paper are analyze the role of spatial concentration of  economic activities and estimate the effect of provincial cluster in the Southern shore of the Gulf of Thailand on economic growth. Panel data from the years 1995-2015 are data that collected for all 4 provinces in provincial cluster. The result show the value of LQ that more than 1 reveal in agricultural (LQAgricultural) and industry sector (LQIndustry). While, the analyzed the effect of spatial concentration of economic activities in provincial cluster present agricultural sector (LQIndustry) and service sector (LQService) variables significant on economic performance. The case of hotels and restaurants (LQHotel) which is sub economic activities of service sector be significant on economic growth. These results presence the role of externalities as the factor component in the operation of the economic activities in provincial cluster of the Southern shore of the Gulf of Thailand.

Keywords: Agglomeration economies, Spatial concentration, Provincial cluster

JEL classification: R11, R12, R58

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DETECTING INTERREGIONAL PATTERNS IN TOURISM SEASONALITY OF GREECE: A PRINCIPAL COMPONENTS ANALYSIS APPROACH

Dimitrios TSIOTAS

Adjunct Lecturer, Department of Regional and Economic Development, Agricultural University of Athens, Greece, Nea Poli, Amfissa, 33100, Greece, Department of Planning and Regional Development, University of Thessaly, Pedion Areos, Volos, 38334, Greece, tsiotas@aua.gr

tsiotas@uth.gr

Thomas KRABOKOUKIS

Ph.D. candidate, Department of Planning and Regional Development, University of Thessaly, Pedion Areos, Volos, 38334, Greece

tkrabokoukis@uth.gr

Serafeim POLYZOS

Professor, Department of Planning and Regional Development, University of Thessaly, Pedion Areos, Volos, 38334, Greece

spolyzos@uth.gr

Abstract

Tourism seasonality is a complex phenomenon incorporating a temporal, a spatial, and a socioeconomic (ontological) dimension. This paper builds on principal component analysis (PCA) to provide an integrated methodological framework for studying all three dimensions of tourism seasonality. The proposed method classifies the seasonal patterns of tourism demand of the Greek prefectures into regional groups, which are examined in terms of their geographical and socioeconomic characteristics. The study aims to configure distinguishable seasonal profiles in terms of their socioeconomic attributes. The proposed method is applied to monthly data of tourism overnight stays for the period 1998-2018 and detects seven principal components described by diverse socioeconomic attributes. The overall analysis proposes a useful tool for tourism management and regional policy, it advances PCA to be used as a tool of regional classification, and it incorporates a multivariate consideration based on the socioeconomic evaluation of the principal components. The proposed methodology develops an integrated framework dealing with complexity describing socioeconomic research and particularly tourism seasonality.

Keywords: regional development; seasonal classification; spatiotemporal patterns; pattern recognition.

JEL classification: C18, C38, O52, R10, R58, Z30

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