Cross Sector Collaboration Study (Economic Cluster Development)

Understanding a complex phenomenon like an economic cluster requires the ability to continuously read and evaluate available research literature on related issues/topics. I'm working on an economic piece on the concept of transactional clusters so reading other's research helps to ensure appropriate context of those efforts. Hopefully to be published in a scientific journal somewhere (probably not groundbreaking). Likewise, some of the information will be used in the last chapter of a book discussing why entities might collaborate around a problem. The more studies one reads, generally the more knowledgeable one becomes on a topic, and more likely to understand how others as well as mine are formed (similarities and differences). For research studies this is used as a literary discussion which is necessary for complex theoretical models (For example, I have 15+ years of research but am writing it in smaller batches based on that information.) The background is important for research and theory development  (You can read What Are Literature Reviews?).

Here is what I found in the study,

Cross Sector Collaboration Study

Notice from the study why and how organizations will sometimes collaborate with each other to achieve certain goals. The authors also mention the community as a major influence and that is important. Community is a primary source of economic growth but is often neglected in economic theory. This is also why our previous discussions on the blog include the social development of community as a major input factor and benefactor of economic growth (This is becoming increasingly important as wealth gaps rise and zip code as a major factor in life quality. Finding ways to increase quality of life for local residents in our model is part of community support, individual effort, and purpose that underline all sustainable economic engines.).

There is also a level of discussion on data and data collection. Data is used to assess an issue and evaluate such information for possible cause and/or association. Within the model I have been working on it is possible to collect data and measure the value of that data in a way that provides a dashboard health of an entire cluster that would allow for better policy development and overall cluster management. Because elements interact within a cluster they also should be measure in different ways to better understand the flow of such elements within a system.

The study provides some interesting information on mutual learning and blaming loops. There are going to be agreement and disagreements about when and how things function, so some organizational framework is likely needed to handle lack of interest on certain projects that still need support (i.e. a fund on cluster-based research not specific to any study or industry but to general cluster problems as one possibility). Different interests come into play when collaborating on key objectives, projects, etc. The areas where entities in the study collaborated are around education, economic development, and public safety. The manuscript also discusses what happens under a blaming loop. In collaborative efforts you want to avoid non-constructive engagement.

Santiago Pulido-Gómez, Jorrit de Jong, Jan W Rivkin, Cross-sector collaboration in cities: learning journey or blame game?, Journal of Public Administration Research and Theory, 2025;, muae026, https://doi.org/10.1093/jopart/muae026