海洋運輸是國際貿易最常使用的貨物運送方式，其中定期航運運送的貨物價值占所有海運貨物的70%，對以國際貿易為經濟成長動力的國家來說，定期航運是相當重要的運輸產業，因此掌握市場動態與發展趨勢成為政府與航商的重要課題。貨櫃吞吐量是衡量各國定期航運產業規模與表現的主要指標之一，且能進一步反映國際貿易對運輸服務需求的變化；定期航運連通性則是指國家對外的運輸連結能力與效率，代表航商針對市場的需求所提供的服務規模。本研究假設，當國家的連通性增加時，能有效減少貿易障礙並提高競爭力，進而帶來更多潛在的貿易機會，增加該國的貨櫃吞吐量，且連通性或吞吐量的增加所帶來的效益，可能會透過與其他國家的連結而向外傳遞。本研究使用空間計量經濟模型實證貨櫃吞吐量與定期航運連通性之間的關係為正相關，且模型中存在顯著的正向空間外溢效應，表示各國的貨櫃吞吐量會受到其他國家的吞吐量與連通性的影響，其中以雙邊航運連通性為空間關聯的模型具有最佳的配適度，即一國的定期航運連通性指數提升一個單位時，其航運高度連結國家的貨櫃吞吐量自然對數會增加0.0201個單位，相當於14,939個20呎標準貨櫃。本研究亦針對臺灣、韓國、中國與美國的外溢效應分布情形做個別探討，並發現臺灣與韓國因產業型態與經濟結構相似，皆以出口貿易為主，因此在航運的外溢效應的強度與傳遞對象具有相似的分布；中國與美國做為全球經濟與貨物進出口的兩大核心，彼此之間透過貿易所建立的航運連結，使兩國間的交互作用程度高於其他國家的雙邊關係。本研究的結果可作為政府、航商或港埠管理單位檢視本國的定期航運產業與其他國家的發展關係，並成為制定未來產業發展策略與基礎設施投資規劃的重要參考資訊。

This paper aims to assess and empirically analyze the effect of spatial interaction on liner shipping performance of coastal countries in order to detect how a country’s liner shipping industry interacts with that of others. We use a spatial data analysis approach to explore the spatial dependence of port container throughput and liner shipping connectivity of 138 coastal countries in 2010 to 2017 as well as build spatial econometrics models to estimate the spillover effect and verify the relationship between throughput and connectivity. The data were collected from the UNCTAD database. The results show that connectivity is a significant explanatory variable for throughput, and there are positive spillover effects. The container throughput of a coastal country will be affected by neighboring countries. In the context of globalization, the country's marine freight transportation will be affected by other countries, and this impact will vary according to different relationships between countries. This is important information for the related authority, including port management units, governments, and carriers. They can predict the future trend of freight volume based on the results of this study and focus on those countries that may be affected. Finally, policies for the liner shipping industry should also be beneficial to the country.

中文部分
1. 張有恆(2013)。現代運輸學(三版)。臺北市：華泰文化。
2. 林光、張志清(2014)。航業經營與管理(八版)。臺北市：航貿文化。
3. 溫在弘(2015)。空間分析：方法與應用。臺北市：雙葉書廊。
英文部分
1. Anselin, L. (1995). Local indicators of spatial association - LISA. Geographical Analysis, 27(2), 93-115.
2. Anselin, L. (2001). Spatial econometrics. A Companion to Theoretical Econometrics (pp. 310-330). John Wiley & Sons.
3. Anselin, L. (2013). Spatial econometrics: Methods and models (vol. 4). Springer Science & Business Media.
4. Anselin, L., & Hudak, S. (1992). Spatial econometrics in practice: A review of software options. Regional Science and Urban Economics, 22(3), 509-536.
5. Anselin, L., Le Gallo, J., & Jayet, H. (2008). Spatial panel econometrics. The Econometrics of Panel Data (pp. 625-660). Springer.
6. Anselin, L., & Rey, S. (2008). Spatial econometrics: Foundations. Unpublished manuscript.
7. APEC. (2010). The economic impact of enhanced multimodal connectivity in the APEC region.
8. Arvis, J. F., & Shepherd, B. (2011). The air connectivity index: measuring integration in the global air transport network. World Bank.
9. Arvis, J. F., Saslavsky, D., Ojala, L., Shepherd, B., Busch, C., & Raj, A. (2014). Connecting to compete 2014: Trade logistics in the global economy. World Bank.
10. Arvis, J. F., Shepherd, B., Duval, Y., & Utoktham, C. (2013). Trade costs and development: A new data set. World Bank.
11. Arvis, J. F., & Shepherd, B. (2016). Measuring connectivity in a globally networked industry: The case of air transport. The World Economy, 39(3), 369-385.
12. Aten, B. H. (1997). Does space matter? International comparisons of the prices of tradables and nontradables. International Regional Science Review, 20(1-2), 35-52.
13. Bartholdi, J. J., Jarumaneeroj, P., & Ramudhin, A. (2016). A new connectivity index for container ports. Maritime Economics & Logistics, 18(3), 231-249.
14. Baumont, C., Ertur, C., & Le Gallo, J. (2001). A spatial econometric analysis of geographic spillovers and growth for european regions, 1980-1995.
15. Behar, A., & Manners, P. (2008). Logistics and exports. Oxford University.
16. Bertoli, S., Goujon, M., & Santoni, O. (2016). The CERDI-seadistance database. CERDI.
17. Bottasso, A., Conti, M., Ferrari, C., & Tei, A. (2014). Ports and regional development: a spatial analysis on a panel of European regions. Transportation Research Part A: Policy and Practice, 65, 44-55.
18. Calatayud, A., Mangan, J., & Palacin, R. (2017). Connectivity to international markets: A multi-layered network approach. Journal of Transport Geography, 61, 61-71.
19. Case, A. C. (1991). Spatial patterns in household demand. Journal of the Econometric Society, 953-965.
20. Case, A. C., Rosen, H. S., & Hines Jr, J. R. (1993). Budget spillovers and fiscal policy interdependence: Evidence from the states. Journal of Public Economics, 52(3), 285-307.
21. Chou, C. C., Chu, C. W., & Liang, G. S. (2008). A modified regression model for forecasting the volumes of Taiwan’s import containers. Mathematical and Computer Modelling, 47(9-10), 797-807.
22. Cliff, A. D. & Ord, J. K. (1973). Spatial autocorrelation. Pion.
23. Cohen, J., & Monaco, K. (2008). Ports and highways infrastructure: An analysis of intra-and interstate spillovers. International Regional Science Review, 31(3), 257-274.
24. Cohen, J. P., & Paul, C. J. M. (2004). Public infrastructure investment, interstate spatial spillovers, and manufacturing costs. Review of Economics and Statistics, 86(2), 551-560.
25. Conley, T. G., & Ligon, E. (2002). Economic distance and cross-country spillovers. Journal of Economic Growth, 7(2), 157-187.
26. Conley, T. G., & Topa, G. (2002). Socio‐economic distance and spatial patterns in unemployment. Journal of Applied Econometrics, 17(4), 303-327.
27. Elhorst, J. P. (2003). Specification and estimation of spatial panel data models. International Regional Science Review, 26(3), 244-268.
28. Elhorst, J. P. (2014). Spatial panel data models. Spatial Econometrics (pp. 37-93). Springer.
29. Fischer, M. M., & Getis, A. (2009). Handbook of applied spatial analysis: Software tools, methods and applications. Springer Science & Business Media.
30. Florax, R. J., & Rey, S. (1995). The impacts of misspecified spatial interaction in linear regression models. New Directions in Spatial Econometrics (pp. 111-135). Springer.
31. Fugazza, M., & Hoffmann, J. (2017). Liner shipping connectivity as determinant of trade. Journal of Shipping and Trade, 2(1).
32. Geary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5(3), 115-146.
33. Getis, A., & Aldstadt, J. (2004). Constructing the spatial weights matrix using a local statistic. Geographical Analysis, 36(2), 90-104.
34. Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206.
35. Gosasang, V., Chandraprakaikul, W., & Kiattisin, S. (2011). A comparison of traditional and neural networks forecasting techniques for container throughput at Bangkok port. The Asian Journal of Shipping and Logistics, 27(3), 463-482.
36. Griffith, D. A. (1995). Some guidelines for specifying the geographic weights matrix contained in spatial statistical models. Practical Handbook of Spatial Statistics. CRC Press.
37. Guerrero, D., Grasland, C., & Ducruet, C. (2015). Explaining international trade flows with shipping-based distances. Maritime Networks: Spatial Structures and Time Dynamics (pp. 303-321).
38. Ho, C. Y., Wang, W., & Yu, J. (2013). Growth spillover through trade: A spatial dynamic panel data approach. Economics Letters, 120(3), 450-453.
39. Hoffmann, J. (2012). Corridors of the Sea: An investigation into liner shipping connectivity. Les Corridors De Transport (pp. 263-276).
40. Hoffmann, J., & Sirimanne, S. N. (2017). Review of maritime transport 2017. UN.
41. Hoffmann, J., & Sirimanne, S. N. (2018). Review of maritime transport 2018. UN.
42. Hoffmann, J., Wilmsmeier, G., & Lun, Y. V. (2017). Connecting the world through global shipping networks. Journal of Shipping and Trade, 2(2).
43. Hsiao, C. (2005). Why panel data? The Singapore Economic Review, 50(2), 143-154.
44. Jiang, J., Lee, L. H., Chew, E. P., & Gan, C. C. (2015). Port connectivity study: An analysis framework from a global container liner shipping network perspective. Transportation Research Part E: Logistics and Transportation Review, 73, 47-64.
45. Jing, N., & Cai, W. (2010). Analysis on the spatial distribution of logistics industry in the developed East coast area in China. The Annals of Regional Science, 45(2), 331-350.
46. Jones, D. A., Farkas, J. L., Bernstein, O., Davis, C. E., Turk, A., Turnquist, M. A., . . . Ostrowski, S. D. (2011). US import/export container flow modeling and disruption analysis. Research in Transportation Economics, 32(1), 3-14.
47. Kooijman, S. A. L. M. (1976). Some remarks on the statistical analysis of grids especially with respect to ecology. Annals of Systems Research (pp. 113-132). Springer.
48. Lam, W. H., Ng, P. L., Seabrooke, W., & Hui, E. C. (2004). Forecasts and reliability analysis of port cargo throughput in Hong Kong. Journal of Urban Planning and Development, 130(3), 133-144.
49. Lee, C. B., Wan, J., Shi, W., & Li, K. (2014). A cross-country study of competitiveness of the shipping industry. Transport Policy, 35, 366-376.
50. Lee, T. W., & Lam, S. L. (2015). Container port competition and competitiveness analysis: Asian major ports. Handbook of Ocean Container Transport Logistics (pp. 97-136): Springer.
51. LeSage, J., & Pace, R. K. (2009). Introduction to spatial econometrics. Chapman and Hall/CRC.
52. Lun, Y. V., & Hoffmann, J. (2016). Connectivity and trade relativity: the case of ASEAN. Journal of Shipping and Trade, 1(1).
53. Merkel, A. (2017). Spatial competition and complementarity in European port regions. Journal of Transport Geography, 61, 40-47.
54. Márquez‐Ramos, L. (2016). Port facilities, regional spillovers and exports: Empirical evidence from Spain. Papers in Regional Science, 95(2), 329-351.
55. Moran, P. A. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17-23.
56. Niebuhr, A. (2006). Market access and regional disparities. The Annals of Regional Science, 40(2), 313-334.
57. O’Sullivan, D., & Unwin, D. J. (2010). Geographic information analysis and spatial data. Geographic Information Analysis (pp. 1-32).
58. OECD. (2017). Digital connectivity and trade logistics - Getting goods shipped, across the border and delivered.
59. Openshaw, S. (1977). Optimal zoning systems for spatial interaction models. Environment and Planning A, 9(2), 169-184.
60. Rodrigue, J. P., Comtois, C., & Slack, B. (2016). The geography of transport systems. Routledge.
61. Seabrooke, W., Hui, E. C., Lam, W. H., & Wong, G. K. (2003). Forecasting cargo growth and regional role of the port of Hong Kong. Cities, 20(1), 51-64.
62. Singh, T. (2010). Does international trade cause economic growth? A survey. The World Economy, 33(11), 1517-1564.
63. Surugiu, M. R., & Surugiu, C. (2015). International trade, globalization and economic interdependence between European countries: Implications for businesses and marketing framework. Procedia Economics and Finance, 32, 131-138.
64. Syafi’i, K. K., & Takebayashi, M. (2005). Forecasting the demand of container throughput in Indonesia. Memoirs of Construction Engineering Research Institute, 47.
65. Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46(1), 234-240.
66. Tong, T., Yu, T. H. E., Cho, S. H., Jensen, K., & Ugarte, D. D. L. T. (2013). Evaluating the spatial spillover effects of transportation infrastructure on agricultural output across the United States. Journal of Transport Geography, 30, 47-55.
67. Veldman, S. J., & Bückmann, E. H. (2003). A model on container port competition: An application for the West European container hub - ports. Maritime Economics & Logistics, 5(1), 3-22.
68. Wang, J., Tsai, C. H., & Lin, P. C. (2016). Applying spatial-temporal analysis and retail location theory to public bikes site selection in Taipei. Transportation Research Part A: Policy and Practice, 94, 45-61.
69. Yu, N., De Jong, M., Storm, S., & Mi, J. (2013). Spatial spillover effects of transport infrastructure: evidence from Chinese regions. Journal of Transport Geography, 28, 56-66.
70. Zarzoso, I. M., & Hoffmann, J. (2007). Costes de transporte y conectividad en el comercio internacional entre la Unión Europea y Latinoamérica. ICE, Revista de Economía, 834.
網路資源
1. UNCTAD Stat, (2018)
http://unctadstat.unctad.org/EN/Index.html
2. WTO Regional Trade Agreements Information System, (2018)
http://rtais.wto.org/UI/PublicMaintainRTAHome.aspx
3. Excel2Earth與空間分析，（2018）
http://excel2earth.blogspot.com/