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Contemporary structure of software employment in metropolitan Tel Aviv

Contemporary structure of software employment in metropolitan Tel Aviv. The diminishing impact of distance on the spatial organization of employment. Nurit Alfasi, Shaul Krakover Department of Geography and Environmental Development Ben-Gurion University of the Negev.

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Contemporary structure of software employment in metropolitan Tel Aviv

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  1. Contemporary structure of software employment in metropolitan Tel Aviv The diminishing impact of distance on the spatial organization of employment Nurit Alfasi, Shaul Krakover Department of Geography and Environmental Development Ben-Gurion University of the Negev

  2. Software firms by size, 2006 425 out of 552 software firms in Israel are located at the Tel Aviv metropolitan area Source: Dan & Bradstreet report, 2006

  3. Objective • Examination of the distance factor as a spatial organization power Utilizing five nodes: • Old CBD • New CBD • The location of the three largest firms employing more than 2000 workers each. Matrix 2150 employees Ness IT 2450 employees New CBD Team 2077 employees Old CBD

  4. Methods employed to examine relationships with distance: • Major rings and sectors using LQ. • Aggregation by 5 km.-wide rings. • Single node – log-linear regression • Piecemeal linear regression • Piecemeal log-linear regression • Multi-focal regression

  5. Software firms, 2006 Location quotients of employees in software firms 1 The software industry is concentrated at the north-eastern parts of the metropolitan area, mainly in the core area and in the inner and middle rings.

  6. Software firms, 2006 1 Location quotient < 1 1 < Location quotient < 3 3 < Location quotient

  7. Aggregation by distance bands 2 * Not significant

  8. Aggregation by distance bands Number of employees by distance bands to the nodes 2 Distance decay curves of total employment originated from New CBD and Ness-IT produce statistically significant linear relationship with distance.

  9. Single Node analysis Log employees with distance 3 N.S. – Not significant *** Significant at the 0.01 level

  10. 4 Piecemeal linear regression N.S. – Not significant * Significant at the 0.10 level ** Significant at the 0.05 level. Three segments of firms: 1) larger than 750, 2) larger than 100 to 750, and 3) 1 to 100. Each segment fitted independently Only for medium size firms there is a slight decreasing slope indicating a decrease in the number of employees with distance.

  11. Piecemeal analysis Log employees with distance 5 N.S. – Not significant * Significant at the 0.10 level ** Significant at the 0.05 level. The old and new CBD does not show signs of organizational power. All three large firms exercise a small but significant amount of organizational power on other large and medium firms.

  12. Multi-focal analysis Log employees with distance 6 N.S. – Not significant ** Significantat the 0.05 level *** Significant at the 0.01 level

  13. 1. Proximity to specific nodes appears to have diminutive organizational power on employment in software. In particular, the Old and New CBDs do not display organizational power on the location of the software firms when analyzed by exact location. However, significant though weak regression results were produced for the location of the firms with respect to their distance to the three largest firms. Team, located in the suburb of Petah Tiqwa has the most powerful organizational effect as reflected by the highest R squares. 2. Medium and large software firms (100+ employees) show some organization patterns around the three largest firms. Whereas, analysis did not procure any distance profiles for small firms.Thus, while large and medium firms are somewhat sensitive to the impact of distance, small firms are less organized. Conclusions

  14. Conclusions 3. Do we face new locational decision realities within urban spaces? Israel’s software firms tend to concentrate in the TA metropolitan area in the north-eastern sectors of the inner ring. However, the impact of distance within this area seem to be marginal and there is no central node that organizes the spatial distribution. This corresponds with Frenkel’s, Shefer’s and Roper’s (2003) findings about the tendency of innovative hi-tech businesses in Israel to locate in metropolitan areas. With diminishing distance relationships does the pattern correlates with Porter’s (1990, 1998, 2000) notion of clusters? 4. Clearly there is a need to employ other techniques to reveal the structure of agglomeration in metropolitan areas.

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