Partnership Characteristics, Network Behavior, and Publicness: Evidence on the Performance of Sustainable Development Projects

ABSTRACT

This study examines partnership characteristics, network behavior, and publicness in the complex policy arena of sustainable development (SD). The study is set in Hong Kong, a city moving away from command-and-control policy instruments to the use of partnerships and stakeholder engagement. It is contended that network partnership characteristics of commitment, equity, mutuality, and trust together with network behavior will vary by the degree of publicness but collectively contribute in a positive manner towards the performance of SD projects. Data were collected from members of 28 SD advisory committees/representative organizations (a 57% response rate) and resulted in a usable dataset of 53 SD projects. Results of analysis indicate that government, business, and civil society SD project members do not perceive major differences between partnership characteristics and perceived project performance but do in relation to network behavior. Multiple regression analysis suggests that trust contributes towards perceived project performance, as do the network behavior characteristics of private sector and civil society group actors; however, for the latter group, network behavior is negatively correlated with project performance. The conclusion discusses implications of these findings for the study of SD projects in Hong Kong and beyond.

ACKNOWLEDGEMENTS

The authors acknowledge the Research Grant Council Public Policy Program (grant # 7010-PPR-09), National Research Foundation of Korea Grant funded by the Korean Government (grant # NRF-2011-330-B00194), and research assistance from Esther Wong.

Notes

Note: The full questions read:

How would you rate the effectiveness of the project?—that is meeting the formal goals of the project.

How efficient is the project?—that is cost per unit of output (minimum cost of maximum output).

How equitable is the project?—that is the equity or fairness of service provision; i.e., distribution of outputs by gender, age, race, income, and geographical area.

How responsive to the needs of the public?—i.e., consumer/citizen satisfaction.

What has been the impact of the project?

Note: Numbers called out in bold indicate factor loading.

*p < .05.

Wicked policy issues also include issues such as poverty alleviation and crime reduction.

The phrase civil society organization is used as a short-hand and includes civil society, nonprofit, and nongovernmental groups and organizations.

Hong Kong's engagement with SD can be traced back to the early 1990s (Hong Kong Government 1991). This engagement, while resulting in some significant institutional reforms (Hills 2005), has not given rise to any notable policy initiatives as government was more comfortable in addressing conventional pollution problems, which it has done with some success. Fundamental tensions remain between the consumption-led priorities of policymakers and much of the local community and the need for a more realistic appraisal of Hong Kong's future development trajectory in the context of the city's overall long-term sustainability and the potential impacts of climate change. Institutional reforms include the establishment of the Sustainable Development Unit in 2001, later to become the Sustainable Development Division of the Environment Bureau, and the Council for Sustainable Development in 2003. The latter functions as a high-level advisory body to government. Despite the Council's attempts to engage with key policy areas such as renewable energy, the built environment, air quality, waste disposal, and, currently, climate change, these efforts have been piecemeal, have lacked coherence, and have not resulted in the formulation of a comprehensive SD strategy for Hong Kong.

Given the cross-sectional nature of our research design, sensitivity tests were undertaken for common source bias by running a factor analysis across the whole data set. This resulted in a number of factors, suggesting variations in the way respondents replied to questions.

The sample was of SD committees and organizations with an environmental or climate change focus. We did, however, offer a broad definition of SD in the survey: “fields linked to sustainability concerns, for example, activities that relate to the environment, climate change, bio-diversity, social welfare, health care and economic development and regeneration.” We used this broad definition to encourage those contacted to respond.

The measurement of performance in the public management literature is complex and contested (Walker, Boyne, and Brewer 2010). Sources of data include administrative records and perceptions from actors that can be recorded internally or externally. In this study of SD projects, no common administrative records present themselves and external actors that have experienced the project are difficult to track down. Having said this, the internal participants that offer their perceptions of the SD partnership are knowledgeable. Similar strategies have been adopted in other studies of the consequences of partnership projects (Chen 2010; Klijn, Steijn, and Edelenbos 2010).

Respondents were offered a definition of partnerships for SD thus: “Any activity that involves two or more parties/individuals/institutions/organizations working on an activity that has particular sustainable development or climate change objectives within a timeframe.”

To ensure that respondents were not discussing a planned SD project, they were asked about the progress using four categorical questions which indicated that they were discussing active endeavors: preparation (0% of respondents), development (23.7%), active (69.7%), and maintenance (6.7%) (Klijn, Steijn, and Edelenbos 2010).

The variance inflation factor scores for the network behavior variables rose towards 10 for the public and private actors, the point at which multicolinarity is a problem. This might be expected given the relative similarity of the first network factor score. To explore if multicolinarity was inflating the coefficients, the networking behavior scores for these two variables were independently entered into the model. This did not change the overall pattern of results reported in Table 3.

We are grateful to one of the anonymous reviewers for making this suggestion.

Additional information

Notes on contributors

Richard M. Walker

Richard M. Walker ([email protected]) is Chair Professor of Public Management in the Department of Public and Social Administration and Associate Dean (Research and Postgraduate Studies) in the College of Liberal Arts and Social Sciences at the City University of Hong Kong. He is also an Honorary Professor at University of Hong Kong and a Senior Research Associate at Xi'an Jiaotong University. His current research interests cover innovation, publicness, red tape, strategic management, and organizational performance in public agencies together with management reform in Asia. His policy interests are in environmental policy and sustainable development. He applies questions of public management to this complex policy arena.

Peter Hills

Peter Hills is Chair Professor in the Kadoorie Institute at the University of Hong Kong. His research interests include sustainability studies, ecological modernization, and environmental policy studies. He has previously held academic posts at the University of Aston in Birmingham and the University of Nottingham in the United Kingdom.