Odongtoo G., Ssebuggwawo D., Lating P.O. (2021) Water Resource Management Frameworks in Water-Related Adaptation to Climate Change. In: Leal Filho W., Ogugu N., Adelake L., Ayal D., da Silva I. (eds) African Handbook of Climate Change Adaptation. Springer, Cham. Online ISBN978-3-030-42091-8. https://doi.org/10.1007/978-3-030-42091-8_24-1

Abstract: This chapter addresses the use of partial least squares–structural equation modeling (PLS-SEM) to determine the requirements for an effective development of water resource management frameworks. The authors developed a quantitative approach using Smart-PLS version 3 to reveal the views of different experts based on their experiences in water-related adaptation to climate change in the Lake Victoria Basin (LVB) in Uganda. A sample size of 152 was computed from a population size of 245 across the districts of Buikwe, Jinja, Mukono, Kampala, and Wakiso. The chapter aimed to determine the relationship among the availability of legal, regulatory, and administrative frameworks, public water investment, price and demand management, information requirements, coordination structures, and analytical frameworks and how they influence the development of water resource management frameworks. The findings revealed that the availability of legal, regulatory, and administrative frameworks, public water investment, price and demand management, information requirements, and coordination structures had significant and positive effects on the development of water resource management frameworks. Public water investment had the highest path coefficient (β = 0.387 and p = 0.000), thus indicating that it has the greatest influence on the development of water resource management frameworks. The R2 value of the model was 0.714, which means that the five exogenous latent constructs collectively explained 71.4% of the variance in the development. The chapter suggests putting special emphasis on public water investment to achieve an effective development of water resource management frameworks. These findings can support the practitioners and decision makers engaged in water-related adaptation to climate change within the LVB and beyond.and beyond.

Odongtoo Godfrey, Ssebuggwawo Denis, Lating Peter Okidi. (2019). Factors Affecting Communication and Information sharing for Water Resource Managementin Lake Victoria Basin (LVB). Paper presented at: World Symposium on Climate Change and Biodiversity (WSCCB-2018), Manchester, UK, 3rd – 5th April 2018. In: Leal Filho W., Barbir J., Preziosi R. (eds) Handbook of Climate Change and Biodiversity. Climate Change Management: pp 211-222. Springer, Cham. doi: https://link.springer.com/chapter/10.1007/978-3-319-98681-4_13, ISBN: 978-3-319-98680-7

Abstract: Lake Victoria Basin (LVB) is a very important resource for the five riparian countries: Uganda, Kenya, Tanzania, Rwanda and Burundi. The basin provides resources for fishing, agriculture, medicine, forestry, water transport and other economic activities. However, its area is grossly affected by climate change due to population growth, urbanization, industrialization, increasing commercial activities and inadequate provision of sanitation services which have caused a lot of pollution. This climate change is likely to lead to loss of biodiversity in terms of species richness. Moreover, the increase in the population growth around Lake Victoria Basin is associated with an increase in economic activities that lead to ecosystem vulnerability and social-ecological disequilibrium. Climate change is likely to affect biodiversity as species struggle to adapt to climatic changes. In order to address the issue of climate change, proper communication and information sharing among the stakeholders around the Lake Victoria Basin is paramount. This paper addresses this need, by discussing major socio-economic activities taking place around this Basin, their impact on climate change and its impact on biodiversity thereof, and problems related to resource management. The study took place in the districts of Buikwe and Mayuge in Uganda. Qualitative and quantitative research approaches were used, data collected was analyzed using Statistical Package for Social Science research software. From the findings, there are variations in access to communication gadgets, mobile phones being top on the list of accessibility. The study concludes by identifying the best option for communication and information sharing based on the factors evaluated and recommends an integrated web-based and mobile application tool for better management of resource in Lake Victoria Basin.

Denis Ssebuggwawo, Stijn S.J.B.A. Hoppenbrouwers, Erik H.A. Proper (2010). Assessing Collaborative Modeling Quality Based on Modeling Artifacts. In: van Bommel, P., Hoppenbrouwers, S., Overbeek, S., Proper, E., Barjis, J. (eds.): LNBIP vol. 68, pp. 76 – 90. Springer, Berlin. ISBN: 978-3-642-16781-2.

Abstract: Collaborative modeling uses and produces modeling artifacts whose quality can help us gauge the effectiveness and efficiency of the modeling process. Such artifacts include the modeling language, the modeling procedure, the products and the support tool or medium. To effectively assess the quality of any collaborative modeling process, the (inter-) dependencies of these artifacts and their effect on modeling process quality need to be analyzed. Although a number of research studies have assessed and measured the quality of collaborative processes, no formal (causal) model has been developed to assess the quality of the collaborative modeling process through a combination of modeling artifacts. This paper develops a Collaborative Modeling Process Quality (CMPQ) construct for assessing the quality of collaborative modeling. A modeling session involving 107 students was used to validate and measure the quality constructs in the model. 

Denis Ssebuggwawo, Stijn S.J.B.A. Hoppenbrouwers, Erik H.A. Proper (2009). Interactions, Goals and Rules in a Collaborative Modeling Session.  In: A. Persson and J. Stirna (eds.):  LNBIP vol. 39, pp. 54 – 68. Springer, Heidelberg. ISBN: 978-3-642-05351-1 (Print), 978-3-642-05352-8 (Online).

Abstract: Collaborative modeling can enhance productivity and quality of modeling in system development and enterprise engineering projects by helping to construct agreement and a sense of model ownership among stakeholders/modelers. Most of these stakeholders have relatively low expertise in formal modeling; advanced modeler-oriented support for collaborative modeling is a possible remedy. As a basis for further development of such support (methods, tools), we have carried out a detailed exploratory study of the interaction between modelers, involving diverse aspects of modeling: goal setting, modeling language concepts, planning, etc. Central in our approach is the study of how collaborative modelers negotiate, set, use, and deal with the various rules/goals governing interactive modeling sessions. We describe the conceptual framework and approach used for our analysis, and present findings from a case study which focused on the first phases of a session concerning basic Business Process Modeling. We also compare our findings to some existing work, to demonstrate the relevance of our approach.

Denis Ssebuggwawo, Stijn S.J.B.A Hoppenbrouwers, Erik H.A. Proper (2009). Evaluating Modeling Sessions Using the Analytic Hierarchy Process. In: A. Persson and J. Stirna (eds.): LNBIP vol. 39, pp. 69 – 83. Springer, Heidelberg. ISBN: 978-3-642-05351-1 (Print), 978-3-642-05352-8 (Online).

Abstract: In this paper, which is methodological in nature, we propose to use an established method from the field of Operations Research, the Analytic Hierarchy Process (AHP), in the integrated, stakeholder-oriented evaluation of enterprise modeling sessions: their language, process, tool (medium), and products. We introduce the AHP and briefly explain its mechanics. We describe the factors we take into consideration, and demonstrate the approach at the hand of a case example we devised based on a semi-realistic collaborative modeling session. The method proposed is to be a key part of a larger setup: a “laboratory” for the study of operational (i.e. real) modeling sessions and related study and development of methods and tools deployed in them.