Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/137697
|
| Title: | 網絡觀點下的跨地方服務協議：檢視影響地方行動者之網絡連結的關鍵因素
A perspective of network on interlocal service agreements: Inspecting the critical factors influencing actors’ connection in local collaborative networks |
| Authors: | 張鐙文
Chang, Teng-Wen |
| Contributors: | 黃東益
Chen, Yu-Che
張鐙文
Chang, Teng-Wen |
| Keywords: | 跨地方服務協議
網絡結構
網絡連結
社會網絡分析
指數隨機圖模型
Interlocal service agreements (ISAs)
Network structures
Network connections
Social network analysis (SNA)
Exponential random graph models (ERGMs) |
| Date: | 2021 |
| Issue Date: | 2021-11-01 12:06:50 (UTC+8) |
| Abstract: | 當代治理的結構，已經從層級節制轉向為網絡連結，且有愈加明顯的現象。晚近，這股協力的浪潮開始從公私合夥，慢慢地吹向公共組織之間及其與利害關係人的通力合作。在這樣的趨勢之下，讓公共協力的研究漸趨多元，而透過跨地方服務協議的機制，作為公共服務提供的方式，也逐漸地受到重視。然而，在行動者各自擁有不同的目標與偏好的前提之下，如何提高協力的成果並減少非預期的結果，便成為實踐公共協力的首要之務，尤其是在資訊不對稱及專業不對稱的情境中，（1）地方行動者如何選擇合適的協力夥伴，以發揮一加一大於二綜效；以及（2）所選定之協力夥伴的特定作為，是否會影響地方行動者的行為，均是攸關跨地方服務協議能否成功的關鍵，而成為必須面對的管理議題。
不過，如欲掌握隱藏在協議締結背後，行動者的多元連結已非易事，更遑論要分析並理解行動者的複雜互動。所幸，在網絡關係理論及社會網絡分析的輔助下，使得網絡結構的概念漸趨成熟，無論是在理論建構、概念測量及分析技術等層面都有豐碩的成果，而被廣泛地應用於不同的研究主題，將有助於檢視跨地方服務協議中行動者之間的互動模式及其成因。因之，本研究奠基於既有跨地方服務協議的實證研究，並從不同網絡關係理論中汲取養分，嘗試提出一個整合性的分析架構，用以檢視跨地方服務協議之網絡結構（分為純結構、行動者-屬性及網絡-屬性等效果）對網絡連結（又細分為協力關係建立及協議參與程度）的影響，同時，探討在不同的系絡因素（即三種公共服務類型）之協力網絡中，網絡結構與網絡連結之間的關係會是否有所差異，藉此說明在協力賽局中，地方行動者在協力關係建立及協議參與程度等行動的策略與邏輯。
爰此，本研究以Iowa 28E Agreement資料庫中的跨地方服務協議作為分析對象，一方面，應用各種社會網絡分析的指標，描繪跨地方服務協議之協力網絡的輪廓與底蘊；另一方面，透過不同的指數隨機圖模型，梳理在各類型的公共服務網絡中，網絡結構對於協力關係建立及協議參與程度的影響。結果顯示，在不同公共服務類型的協力網絡中，各種網絡結構對於網絡連結的影響並不一致，代表公共服務類型對於網絡結構與網絡連結之間的關係，具有相當程度的調解效果。其中，純結構之網絡組態對於協力關係建立的影響，其效果在準公共財的協力網絡中最為明顯；而行動者-屬性之網絡組態對於協力關係建立的影響，以及網絡-屬性之網絡組態對於協議參與程度的影響，其效果則是在純公共財的協力網絡中最為明顯。相關成果均可以作為後續研究精進與未來實務推動之參考。
Contemporary governance structure has shifted from hierarchical to heterarchy. This wave of change has gradually shifted from public-private partnerships to collaboration between public organizations, and collaboration between public organizations and stakeholders. In response to these changes, the research on public collaboration has diversified. More attention has also been given to the importance of the model of interlocal service agreements (ISAs). However, under the premise that the actors in the network usually have different goals and preferences, how to improve the results of the collaboration and reduce the unintended results becomes the priority in the practice of public collaboration. This is especially important in the scenario of information asymmetry and professional asymmetry, (1) how the local actors choose their suitable partners to achieve the synergy of collaboration, and (2) whether their partners’ behaviors affect the local actors’ behaviors or not are the key factors to the success of executing the interlocal service agreements.
It is not easy to grasp the connections between actors in the network, let alone analyze and understand the interactions between actors. Fortunately, with the assistance of the network relationship theory and social network analysis (SNA), the concept of network structure has gradually matured. As a result, network structure has achieved fruitful results in theoretical construction, conceptual measurement, and analysis techniques, and has been widely used in different research topics. Network structure provides the theoretical framework and analytical tools for examining the interaction patterns between actors in the network of interlocal service agreements and revealing the reasons for their actions. Therefore, this research organized past empirical studies of interlocal service agreements and different network relationship theories. It then attempts to propose an integrated analysis framework for examining the relationship between network structure (i.e. purely structural effects, actor-relation effects, and network-attribute effects) and network connection (i.e. formation of collaborative ties and degree of agreement participation) in the network of interlocal service agreements. We also compared the relationship between network structure and network connection in the three types of public service pattern networks.
Accordingly, this research used the interlocal service agreements in the Iowa 28E Agreement database as the object of analysis. On the one hand, various indicators of social network analysis were applied to describe the outline and details of the collaborative network of interlocal service agreements. On the other hand, different exponential random graph models were conducted to identify the relationships between network structure, formation of collaborative ties, and degree of agreement participation in the diverse networks of public service patterns. The results show that the relationships between network structure and network connection in distinct networks of public service patterns are not consistent. This indicates that public service patterns have a considerable degree of mediation effect on the relationship between network structure and network connection. More specifically, purely structural effects have more influence on the formation of collaborative ties in the network of quasi-public goods. Whereas, actor-relation effects have more influence on the formation of collaborative ties in the network of public goods. Finally, network-attribute effects have more influence on the formation of collaborative ties in the network of public goods. The results from this research provide significant insights into the reality of public collaboration. These insights could contribute to future academic research and assist practitioners in real-world scenarios. |
| Reference: | 1. 李宗勳、陳世榮（2019）。都會災害防救中的協力決策：對市府部門的互動網絡評估。文官制度季刊，11（1），1-33。
2. 李長晏（2009）。從協力治理模式探討淡水河流域的管理。中國地方自治，62（10），3-19。
3. 李長晏（2016）。如何強化中央與地方府際合作協調機制。國土及公共治理季刊，4（3），42-57。
4. 李長晏、林煥笙。（2009）。中央與地方協力夥伴關係之分析—以台中縣潭子段旱溪整治工程為例。公共行政學報，31，49-100。
5. 李長晏、曾淑娟（2009）。北臺與高高屏區域聯盟治理營運之比較。臺灣民主季刊，6（2），1-60。
6. 周志龍（2014）。臺灣區域發展與縣市跨域整合治理之實踐：國土規劃觀點。國土及公共治理季刊，2（4），9-25。
7. 林淑馨（2020）。臺灣非營利組織參與政府災害防救之協力經驗。政治科學論叢，86，191-236。
8. 高誓男（2012）。中央與地方公共治理互動機制。研考雙月刊，36（6），146-157。
9. 張峻豪（2018）。制度韌性與台灣半總統制下的災後重建：以九二一地震、莫拉克風災為例。東吳政治學報，36（1），65-126。
10. 張鐙文、吳佩靜（2020）。探索我國中央機關協力式決策制定的態樣：政策論證觀點之應用與檢視。2020年臺灣公共行政與公共事務系所聯合會年會暨國際學術研討會。臺南。
11. 郭翡玉、謝慧娟（2014）。以跨域加值方式推動公共建設之作法與推動成效。國土及公共治理，2（4），26-36。
12. 曾淑娟（2008）。北臺與高高屏區域合作機制比較。研考雙月刊，32（5），69-84。
13. 曾淑娟（2009）。臺灣各縣市間區域合作現況與前瞻。研考雙月刊，33（5），111-116。
14. 湯京平（2001）。災難、官僚與民主：台灣九二一震災援救行政的政治與制度分析。中國行政評論，11（1），67-98。
15. 湯京平、陳金哲（2015）。新公共管理與鄰避政治：以嘉義縣市跨域合作為例。政治科學論叢，23，101-132。
16. 程仁宏（2005）。垃圾焚化廠跨縣市營運管理之研究一以臺北市及基隆市為例。華岡地理學報，18，1-17。
17. 廖俊松、曾憲華（2006）。全球化下地方警政跨域治理之初探。中國地方自治，59（2），3-18。
18. 劉明德、徐玉珍（2011）。地方政府跨域合作模式與案例分析—台灣與德國之比較。公共行政學報，41，37-72。
19. 謝儲鍵、林煥笙、陳敦源（2016）。緊急災害管理中之協力網絡分析：以莫拉克風災災後的教育重建為例。行政暨政策學報，62，59-125。
20. Agranoff, R., & M. McGuire (2001). Big questions in public network management Research. Journal of. Public Administration Research and Theory, 11(3), 295-396.
21. Andrew, S. A. (2009). Regional integration through contracting networks: An empirical analysis of institutional collection action framework. Urban Affairs Review, 44(3), 378-402.
22. Andrew, S. A. (2010). Adaptive versus restrictive contracts: Can they resolve different risk problems? In R. C. Feiock & J. T. Scholz (Eds.), Self-organizing federalism: Collaborative mechanisms to mitigate institutional collective action dilemmas (pp. 91-113). New York, NY: Cambridge University Press.
23. Ansell, C., & A. Gash (2008). Collaborative governance in theory and practice. Journal of Public Administration Research and Theory, 18(4), 543-571.
24. Bai, X., S. Sheng, & J. J. Li (2016). Contract governance and buyer-supplier conflict: The moderating role of institutions. Journal of Operations Management, 41(1), 12-24.
25. Batina, R. G., & T. Ihori (2005). Public goods: Theories and evidence. New York, NY: Springer.
26. Bel, G., & M. Sebő (2021). Does inter-municipal cooperation really reduce delivery costs? An empirical evaluation of the role of scale economies, transaction costs, and governance arrangements. Urban Affairs Review, 57(1), 153-188.
27. Berardo, R., & J. T. Scholz (2010). Self-organizing policy networks: Risk, partner selection, and cooperation in estuaries. American Journal of Political Science, 54(3), 632-649.
28. Bingham, L. B., T. Nabatchi, & R. O`Leary (2005). The new governance: Practices and processes for stakeholder and citizen participation in the work of government. Public Administration Review, 65(5), 547-558.
29. Borgatti, S. P., & M. G. Everett (1997). Network analysis of two mode data. Social Networks, 19, 243-269.
30. Borgatti, S. P., & D. S. Halgin (2011). Analyzing affiliation networks. In J. Scott & P. J. Carrington (Eds.), The SAGE handbook of social network analysis. London, UK: SAGE Publications.
31. Brown, T. L., & M. Potoski (2003). Transaction costs and institutional explanations for government service production decisions. Journal of Public Administration Research and Theory, 13(4), 441-468.
32. Brown, T. L., & M. Potoski (2005). Transaction costs and contracting: The practitioner perspective. Public Performance & Management Review, 28(3), 326-351.
33. Bryson, J. M., B. C. Crosby, & M. M. Stone (2006). The design and implementation of cross-sector collaborations: Propositions from the literature. Public Administration Review, 66(S1), 44-55.
34. Bryson, J. M., B. C. Crosby, & M. M. Stone (2015). Designing and implementing cross-sector collaborations: Needed and challenging. Public Administration Review, 75(5), 647-663.
35. Carr, J. B., & C. V. Hawkins, (2013). The costs of cooperation: What the research tells us about managing the risks of service collaborations in the U.S. State and Local Government Review, 45(4), 224-239.
36. Carr, J. B., C. V. Hawkins, & D. E. Westberg (2017). An exploration of collaboration risk in joint ventures: Perceptions of risk by local economic development officials. Economic Development Quarterly, 31(3), 210-227.
37. Carter, D. P., A. Deslatte, & T. A. Scott (2019). The formation and administration of multipurpose development sistricts: Private interests through public institutions. Perspectives on Public Management and Governance, 2(1), 57-74.
38. Chen, B., L. Suo, & J. Ma (2015). A network approach to interprovincial agreements. State and Local Government Review, 47(3), 181-191.
39. Chen, Y.-C., & K. Thurmaier (2008). Interlocal agreements as collaborations. The American Review of Public Administration, 39(5), 536-552.
40. Common, R., & B. Acevedo (2006). Governance and the management of networks in the public sector. Public Management Review, 8(3), 395-414.
41. Cranmer, S. J., & B. A. Desmarais (2011). Inferential network analysis with exponential random graph models. Political Analysis, 19(1), 66-86.
42. Daraganova, G., & P. Pattison (2013). Autologistic actor attribute model analysis of unemployment: Dual importance of who you know and where you live. In D. Lusher, J. Koskinen, & G. Robins (Eds.), Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications (pp. 102-114). New York, NY: Cambridge University Press.
43. Davis, J. H., F. D. Schoorman, & L. Donaldson (1997). Toward a stewardship theory of management. Academy of Management Review, 22, 20-47.
44. Denhardt, R. B., & J. V. Denhardt (2000). The new public service: Serving rather than steering. Public Administration Review, 60(6), 549-559.
45. Douglas, S., O. Berthod, M. Groenleer, & J. Nederhand (2020). Pathways to collaborative performance: Examining the different combinations of conditions under which collaborations are successful. Policy and Society, 39(4), 638-658.
46. Emerson, K., T. Nabatchi, & S. Balogh (2012). An integrative framework for collaborative governance. Journal of Public Administration Research and Theory, 22(1), 1-29.
47. Faems, D., M. Janssens, A. Madhok, & B. V. Looy (2008). Toward an integrative perspective on alliance governance: Connecting contract design, trust dynamics, and contract application. Academy of Management Journal, 51(6), 1053-1078.
48. Feiock, R. C. (2007). Rational choice and regional governance. Journal of Urban Affairs, 29(1), 47-63.
49. Feiock, R. C. (2009). Metropolitan governance and institutional collective action. Urban Affairs Review, 44(3), 356-377.
50. Feiock, R. C. (2013). The institutional collective action framework. The Policy Studies Journal, 41(3), 397-425.
51. Feiock, R. C., I. W. Lee, H. J. Park, & K.-H. Lee (2010). Collaboration networks among local elected officials: Information, commitment, and risk aversion. Urban Affairs Review, 46(2), 241-262.
52. Golbeck, J. (2013). Analyzing the social web. Waltham, MA: Elsevier Inc.
53. Hanneman, R. A., & M. Riddle (2005). Introduction to social network methods. Riverside, CA: University of California, Riverside.
54. Harris, J. K. (2014). An introduction to exponential random graph modeling. Thousand Oaks, CA: SAGE Publications.
55. Hawkins, C. V. (2009). Prospects for and barriers to local government joint ventures. State and Local Government Review, 41(2), 108-119.
56. Ilcan, S. M., D. M. O’Connor, & M. L. Oliver (2004). Contract governance and the Canadian public sector. Relations industrielles / Industrial Relations, 58(4), 620-643.
57. Isett, K. R., I. A. Mergel, K. LeRoux, P. A. Mischen, & R. K. Rethemeyer (2011). Networks in public administration scholarship: Understanding where we are and where we need to go. Journal of Public Administration Research and Theory, 21(S1), i157-i173.
58. Jung, K., M. Song, & H. J. Park (2018). The dynamics of an interorganizational emergency management network: Interdependent and independent risk hypotheses. Public Administration Review, 79(2), 225-235.
59. Kadushin, C. (2012). Understanding social networks: Theories, concepts and findings. New York, NY: Oxford University Press.
60. Klijn, E.-H. (2008). Governance and governance networks in Europe. Public Management Review, 10(4), 505-525.
61. Klijn, E.-H., & J. Koppenjan (2016). Governance Networks in the Public Sector. New York, NY: Routledge.
62. Klijn, E.-H., & Koppenjan, J. F. M. (2006). Public management and policy networks: Foundations of a network approach to governance. Public Management: An International Journal of Research and Theory, 2(2), 135-158.
63. Koliba, C. J., J. W. Meek, A. Zia, & R. W. Mills (2018). Governance networks in public administration and public policy. New York, NY: Routledge.
64. Letina, S., G. Robins, & D. Maslić Seršić (2016). Reaching out from a small scientific community: The social influence models of collaboration across national and disciplinary boundaries for scientists in three fields of social sciences. Revija za sociologiju, 46(2), 103-139.
65. Lusher, D., & G. Robins (2013). Formation of social network structure. In D. Lusher, J. Koskinen, & G. Robins (Eds.), Exponential random graph models for social networks: Theories, methods and applications (pp. 16–28). New York, NY: Cambridge University Press.
66. Marcussen, M., & H. P. Olsen (2007). Transcending analytical cliquishness with second-generation governance network analysis. In M. Marcussen & J. Torfing (Eds.), Democratic network governance in Europe (pp. 273-292). New York, NY: Palgrave Macmillan.
67. Milward, H. B., & K. G. Provan (1998). Measuring network structure. Public Administration, 76(2), 387-407.
68. O`Leary, R. (2015). From silos to network: Hierarchy to heterarchy. In M. E. Guy & M. M. Rubin (Eds.), Public administration evolving: From foundations to the future (pp. 84-101). New York, NY: Routledge.
69. O`Leary, R., & N. Vij (2012). Collaborative public management: Where have we been and where are we going? The American Review of Public Administration, 42(5), 507-522.
70. O`Toole, L. J., Jr. (1997). Treating networks seriously: Practical and research-based agendas in public administration. Public Administration Review, 57(1), 45-52.
71. O`Toole, L. J., Jr. (2015). Networks and networking: The public administrative agendas. Public Administration Review, 75(3), 361-371.
72. Osborne, S. P. (2006). The new public governance? Public Management Review, 8(3), 377-387.
73. Osborne, S. P. (2010). The (new) public governance: A suitable case for treatment? In S. P. Osborne (Ed.), The new public governance? Emerging perspectives on the theory and practice of public governance (pp. 1-16). London and New York: Routledge.
74. Ospina, S. M., & A. Saz-Carranza (2010). Paradox and collaboration in network management. Administration & Society, 42(4), 404-440.
75. Parker, A., F. Pallotti, & A. Lomi (2021). New network models for the analysis of social contagion in organizations: An introduction to autologistic actor attribute models. Organizational Research Methods. doi:10.1177/10944281211005167
76. Peters, B. G., & J. Pierre (1998). Governance without government? Rethinking public administration. Journal of Public Administration Research and Theory, 8(2), 223-243.
77. Provan, K. G., A. Fish, & J. Sydow (2007). Interorganizational networks at the network level: A review of the empirical literature on whole networks. Journal of Management, 33(3), 479-516.
78. Rhodes, R. A. W. (1996). The new governance: Governing without government. Political Studies, 44, 652-667.
79. Rhodes, R. A. W. (1997). Foreword by professor R. A. W. Rhodes. In W. J. M. Kickert, E. H. Klijn, & J. F. M. Koppenjan (Eds.), Managing complex networks: Strategies for the public sector (pp. xi-xv). London, UK: SAGE Publications.
80. Ring, P. S., & A. H. van de Ven (1994). Developmental processes of cooperative interorganizational relationships. The Academy of Management Review, 17(1), 90-118.
81. Robins, G., & G. Daraganova (2013). Social selection, dyadic covariates, and geospatial effects. In D. Lusher, J. Koskinen, & G. Robins (Eds.), Exponential random graph models for social networks: Theories, methods and applications (pp. 91-101). New York, NY: Cambridge University Press.
82. Robins, G., & D. Lusher (2013a). Illustrations: Simulation, estimation, and goodness of fit. In D. Lusher, J. Koskinen, & G. Robins (Eds.), Exponential random graph models for social networks: Theories, methods and applications (pp. 167-185). New York, NY: Cambridge University Press.
83. Robins, G., & D. Lusher, (2013b). What are exponential random graph models? In D. Lusher, J. Koskinen, & G. Robins (Eds.), Exponential random graph models for social networks: Theories, methods and applications (pp. 9-15). New York, NY: Cambridge University Press.
84. Robins, G., P. Pattison, & P. Elliott (2001). Network models for social influence processes. Psychometrika, 66(2), 161-189.
85. Robins, G., P. Pattison, Y. Kalish, & D. Lusher (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2), 173-191.
86. Rose Kim, J. Y., M. Howard, E. Cox Pahnke, & W. Boeker (2016). Understanding network formation in strategy research: Exponential random graph models. Strategic Management Journal, 37(1), 22-44.
87. Runya, X., S. Qigui, & S. Wei (2015). The third wave of public administration: The new public governance. Canadian Social Science, 11(7), 11-21.
88. Scott, T. A., & N. Ulibarri (2019). Taking network analysis seriously: Methodological improvements for governance network scholarship. Perspectives on Public Management and Governance, 2(2), 89-101.
89. Shrestha, M. K. (2010). Do risk profiles of services alter contractual patterns? A comparison across multiple metropolitan services. In R. Feiock & J. T. Scholz (Eds.), Self-organizing federalism: Collaborative mechanisms to mitigate institutional collective action dilemmas (pp. 114-141). New York, NY: Cambridge University Press.
90. Shrestha, M. K., & R. C. Feiock (2010). Transaction cost, exchange embeddedness, and interlocal cooperation in local public goods supply. Political Research Quarterly, 64(3), 573-587.
91. Siciliano, M. D., W. Wang, & A. Medina (2021). Mechanisms of network formation in the public sector: A systematic review of the literature. Perspectives on Public Management and Governance, 4(1), 63-81.
92. Song, M., H. J. Park, & K. Jung (2018). Do political similarities facilitate interlocal collaboration? Public Administration Review, 78(2), 261-269.
93. Tabassum, S., F. S. F. Pereira, S. Fernandes, & J. Gama (2018). Social network analysis: An overview. WIREs Data Mining and Knowledge Discovery, 8(5), e1256.
94. Torfing, J. (2007). Introduction: Democratic network governance. In M. Marcussen & J. Torfing (Eds.), Democratic network governance in Europe (pp. 1-22). New York, NY: Palgrave Macmillan.
95. Wang, P., G. L. Robins, & P. Pattison (2009). PNet: Program for the simulation and estimation of exponential random graph (p*) models. Melbourne, Australia: Melbourne School of Psychological Sciences, The University of Melbourne.
96. Yi, H., & C. Cui (2018). Coping with functional collective action dilemma: Functional fragmentation and administrative integration. Public Management Review, 21(7), 1052-1075.
97. Yi, H., L. Suo, R. Shen, J. Zhang, A. Ramaswami, & R. C. Feiock (2018). Regional governance and institutional collective action for environmental sustainability. Public Administration Review, 78(4), 556-566. |
| Description: | 博士
國立政治大學
公共行政學系
100256501 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0100256501 |
| Data Type: | thesis |
| DOI: | 10.6814/NCCU202101674 |
| Appears in Collections: | [公共行政學系] 學位論文
|
Files in This Item:
| File |
Size | Format | |
|---|
| 650101.pdf | 24997Kb | Adobe PDF2 | 90 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
