Understanding dynamics of agricultural runoff to Oslofjord: A causal loop modelling approach.

In Ontario, Canada, incarcerated individuals and their newborns have adverse health outcomes. Perinatal care delivery in these settings is complex and fragmented across health, social service and carceral systems. This study aimed to apply and demonstrate an integrated systems-based analytical approach to examine dynamic interactions within carceral perinatal care and to identify influential variables and leverage points for policy and service improvement. Using qualitative interview data from individuals who experienced incarceration while pregnant and from healthcare and social service providers, we applied an integrated methodological framework combining structural analysis (MICMAC) and causal loop diagramming. This stepwise approach was used to identify system variables, map causal pathways and feedback loops, and assess influence-dependence relationships within Ontario's carceral perinatal care system. Our analysis identified two key variables as central drivers of system behaviour through reinforcing and balancing loops, respectively: carceral staff autonomy and availability of providers. High levels of carceral staff autonomy reinforce power imbalances by decreasing providers' autonomy, which in turn constrains perinatal care delivery. Availability of providers operates within a balancing loop, whereby increased availability strengthens incarcerated clients' autonomy and increases their knowledge of human rights. Advocacy was identified as a key leverage point for navigating power dynamics within the system. This study demonstrates the utility of integrating structural analysis with causal loop modelling to examine institutional dynamics, constraints and leverage points in complex health service systems. By identifying advocacy and comprehensive rights training as potentially essential interventions, alongside policy modifications, these findings highlight actionable pathways to reduce power imbalances and improve perinatal health outcomes among incarcerated individuals and their newborns. The approach provides a transferable framework for understanding complex and fragmented service delivery contexts and for informing evidence-based health policy and implementation strategies.

Application of System Thinking Causal Loop Modelling in understanding water Crisis in India: A case for sustainable Integrated Water resources management across sectors

In their paper exploring fast fashion principles and mass production within globalised supply chains (Martinez-Jaramillo & Tilebein, 2024), the authors address a wicked problem, namely, a class of problem that is ill-formulated, with many clients and decision makers with conflicting values (Churchman, 1967; Termeer et al., 2019). An aspect of this complexity can be observed through the multiple influences of modern technology on their model. For example, they present digital textile microfactories as a promising technological solution to reduce waste, yet at the same time they note that social media technology is a key enabler of trend chasing within the artificial demand reinforcing loop. Their work highlights the utility of qualitative modelling (de Gooyert et al., 2024; Lane et al., 2016) with causal loop diagrams (CLDs) that help explore dynamic patterns, propose solutions and identify possible leverage points, as well as providing a basis for developing quantitative models. Motivated by their work, we now present (1) an extension to their causal loop model in terms of an additional balancing feedback loop and (2) an initial exploratory stock and flow model, with sensitivity analysis, focusing on the model variable fashion obsolescence time. For the extension of the causal loop model we focus on loop R2, artificial demand. Our approach is to consider one of the loop's variables that contributes to the reinforcing behaviour, fashion obsolescence time. In the original model, this moves in the opposite direction to total demand for garments. We propose a balancing factor to this which is that as total demand for garments increases, so too does the demand for higher quality garments. As this demand is fulfilled, this leads to an increase in fashion obsolescence time, and so the overall impact of this change is that a new loop is emerging, a balancing loop, which we label ‘quality not quantity’ (Figure 1). With the focus on the fashion obsolescence time, we can now address this variable within a quantitative stock and flow model. The translation from a CLD to a stock and flow model, for simplicity, proposes a one-stock model for garments (garments in circulation), with garments produced as an inflow and garments discarded as the solitary outflow. The quantitative model is shown in Figure 2, and the completed Stella implementation (and R sensitivity code) can be accessed online.1 We run the model for two scenarios to highlight its behaviour through the stock total discards. For the first run, we fix the fashion obsolescence rate at 1.0, and this models fast fashion where people are discarding and replacing garments at a high rate. The second run sets the obsolescence rate to 0.5 (2 months), and the overall discards are reduced by 50%. While the results of these two runs would appear obvious, to explore this further, and gain additional insights into the relationship between total discards and fashion obsolescence Rate, we utilise sensitivity analysis (Figure 3). The simulation model is run 2500 times, once for each combination of the two parameters. The maximum for total discards is recorded for each individual run (the final value of the stock), as this is a useful overall measure of how successful the policy was. A scatter plot showing a random sample of 250 results is displayed in Figure 4, where each point size is proportional to the maximum size of total discards for that run. As expected, the plots show that total discards is smaller in the lower section of the graph, with longer lifetimes for garments and quick response times to the overall goal. The least desirable solutions are in the area where the desired fashion obsolescence rate is highest, as that corresponds to a shorter delay time for the garments in circulation. We can gain further insights into these relationships by exploring a contour plot (exploring a 3D surface in 2D), as this shows the parameter combinations that generate similar overall results. For example, in Figure 5, the navy shading indicates all those solutions that are in the range of 0–106, while the yellow band captures those results in the range of 9 × 106 and 107. While this is a simple model, nonetheless, the process highlights the potential value of initially building a simple simulation model that is informed by the causal loop structures, and these exploratory models can play a valuable role as part of an iterative model building process. We look forward to seeing future work by the authors, and indeed the wider systems thinking community, to further develop quantitative fast fashion models that further illuminate this important fixes that fail dynamic. Open access funding provided by IReL.

Considering the growing demand for railway transportation, especially metros, and the changing social context, regular 24-hour operation is becoming a requirement. The railway is an inherently complicated and complex system and extending the service hours increases the level of difficulty in operating. In order to run all the services safely, punctually and reliably, we have to manage this complexity. In this paper, the authors suggest the application of system dynamics tools to model 24-hour metros in terms of sub-systems, sub-components and behaviour. An initial causal loop diagram (CLD) has been developed to study the relationships and interactions between different sub-systems of system. The proposed causal loop diagram is intended to allow planners, designers and managers of 24-hour metros to develop a proper understanding of the non-linear environment of such systems. In metros, due to the high level of diversity and variability, there are many system interfaces that must be managed systematically. Causal loop diagram empower managers to understand the effect of their decision-making in managing the interfaces and related changes. The causal loop diagram can be applied as a system optimisation tool when upgrading the existing metros to 24-hour operation and developing new lines while considering risks, complexities and complications. Causal loop modelling allows a rapid identification of the problems of 24-hour operation and will result in safer, more punctual and more reliable system.

PurposeThe purpose of this paper is to adapt a causal modelling approach to investigate the organisational collaboration and information technology (IT) project management issues concerning the planning and adoption of inter‐organisational IT systems across NHS hospital pathology departments.Design/methodology/approachThe researchers adopted an interpretive research approach utilising qualitative methods and in particular template analysis. Themes and categories were initially derived from a review of the literature based on critical success factors from enterprise resource planning (ERP) projects.FindingsA causal loop modelling approach was adapted to define key linkages between success factors. This highlighted virtuous and vicious cycles associated with IT project management and team collaboration – influencing the adoption process of large‐scale integrated IT systems.Research limitations/implicationsSingle case studies can be problematic in terms of generalising from the research. The study had a limited number of interview participants due to the focus on strategic management. Future studies could extend the number of stakeholders involved and also focus on end‐users of services, such as clinicians in primary care.Practical implicationsThe discussion and conclusions assess the appropriateness and utility of using a causal modelling approach, and an adapted causal loop model, to inform more effective approaches to IT planning, project management, team collaboration and adoption of integrated systems.Social implicationsThe findings indicate that a more enhanced understanding of project team collaboration involving technical, administrative and clinical stakeholders has the potential to inform more effective strategies for modernisation of hospital clinical services such as pathology.Originality/valueThis study investigates the anatomy of a high‐profile IT project under the umbrella of strategic modernisation of health services. Privileged access to key stakeholders has enabled the development of a causal model for IT project collaboration and management. This will form the basis for further development of more refined models to enhance project outcomes in the future.

In line with the Paris Agreement, the global hotel sector must reduce its carbon emissions by 66% by 2030 and 90% by 2050. Adopting renewable energy technology (RET) to produce electricity on site is one of the UN’s recommended tools for the hotel sector. Some hotels have explored certain sustainable practices such as light-emitting diode lights, T5 fluorescent tubes, motion sensors, the key-card system, and water-cooled chillers. However, several studies have reported low RET adoption in the hotel sector globally. There are limited studies exploring RET adoption in the hotel context. In response to a strong call to action to the hotel sector, this dissertation addresses this gap by identifying key dynamics that underpin RET adoption, how they influence RET adoption rate, and how these dynamics promote sustainability growth of RET adoption while balancing environmental, social and economic risks and benefits. The results of a systematic quantitative literature review indicate that RET adoption comprises interrelated sectors including technology and its economic viability, hotelier and tourist perceptions, the government and the environment. To incorporate complexity associated with interrelated dynamics, a systems thinking approach supported by a mixed method were used. The state of Queensland in Australia was selected as a case study to conceptualise the RET adoption dynamics. Queensland is an important tourism destination within Australia and internationally, and the number of hotels is growing. Despite Queensland having many incentive policies to promote RET uptake, adoption among the hotel sector is low. Thus, understanding the enablers to RET adoption in the context of Queensland could highlight its complexity and assist decisions to adopt RET in the service sector. Following interviews and structural analysis with stakeholders including hoteliers, the government, academics in tourism and engineering, and electrical providers, the complex dynamics associated with RET adoption in the hotel sector was visualised using a mind-mapping technique (i.e., causal loop diagram). The diagram indicates that those who stimulated the transitions were the government through its incentive policies and tourists by selecting or revisiting hotels. These same actors, however, also (unintentionally) formed a barrier. The government barricaded RET adoption by retracting the incentives policies before a wider adoption could take place. The tourists obstructed wider RET adoption by preferring renewable-sourced hotels and leaving hotels that are unable to uptake RET financially disadvantaged. To empirically test the conclusions drawn from causal loop modelling, a quantitative simulation (i.e., stock-and-flow model) was created. The results suggest that the absence of the government incentive policies caused a negligence impact on RET uptake in the hotel sector because the net present value of RET with 12% discount was already lower than those of the grid in the Queensland context. Instead, the results showed the technology price and performance were a better leverage to encourage adoption. This key finding indicates that, in the hotel sector context, where customer satisfaction is vital to business longevity, hotels may dismiss taking up RET despite its proven economic viability because it poses a risk of electricity disruptions and may compromise tourist experience. The quantitative model’s results contradict the causal loop findings, particularly the overconfidence in government policies, highlighting the usefulness of triangulating research qualitative and quantitative methods. Based on these findings, two recommendations were offered. First, the Queensland government is recommended to foster RET innovation and investment by rechannelling fund from programs that promote individuals (business included) RET adoption to programs that invest in RET innovation. Second, the hotel sector needs to take a leadership to adopt RET by creating a roadmap to innovation adoption. This dissertation contributes to the examination of opportunities to promote RET uptake in the hotel sector. It provides the basis with which to better understand the dynamics that could drive RET uptake, while identifying possible leverage points to more sustainable growth of RET uptake. In doing so, this research contributes to ongoing efforts to accelerate the transition towards a more sustainable, low-emissions hotel sector.

As the global response to anthropogenic climate change evolves, centralised electricity supply systems have become a key focus for emission reduction efforts. While governments and industry mobilise to decarbonise the electricity sector, substantial opportunities have also begun to emerge at the residential level. Recent dramatic growth in the rate of rooftop solar photovoltaic (PV) adoption in Australia epitomises the opportunity, and the disruption, that can occur in response to falling technology costs, increasing retail electricity prices, and the emergence of more active and engaged electricity consumers. Residential battery energy storage is now on the threshold of mass-market uptake. When coupled with solar PV, battery technology could enable potentially millions of small-scale electricity end-users to participate in the market as both generators and consumers, reducing total system demand while challenging the business models of incumbent utilities. This development will not only amplify existing operational complexity in Australian electricity markets, but if the technology is poorly integrated, negatively impact the efficient provision of electricity, an essential service that underpins the structure and function of modern economies. There is a clear imperative for government and industry to proactively manage the integration of residential PV and battery energy storage to avoid adverse or unintended consequences. A number of these risks have received considerable academic and industry attention, particularly from a techno-economic viewpoint. However, there exists a substantial gap in the literature regarding research into battery adoption dynamics from a whole-of-system perspective addressing the multi-causal, socially complex nature of the problem. This dissertation aims to address this gap by identifying the key dynamics that will underpin battery adoption, how they could influence battery deployment rates and how these dynamics will manifest along the broader electricity supply chain. To most effectively incorporate the substantial uncertainty and complexity associated with consumer-led electricity sector transitions in this regard, a systems thinking methodology supported by a mixed method approach to data collection has been used. To generate meaningful results at an appropriate level of granularity, the state of Queensland in Australia is used as a case study to conceptualise and model battery dynamics. Queensland has many of the preconditions necessary for rapid residential battery uptake, and with a centralised electricity sector worth more than AU$30 billion, understanding the drivers that may underpin disruption to this system is critical. Casual loop modelling, informed by an extensive participatory data collection exercise involving interviews with nearly 70 energy sector experts, was initially used to map the complex dynamics associated with residential battery adoption. This research found that a range of non-financial and financial reinforcing feedback loops encouraging battery adoption are currently dominant in Queensland. Should battery prices continue to fall as forecast – a necessary precondition for mass-market uptake – the causal loop diagram demonstrates that multiple paths to market targeting a highly motivated consumer-base would make rapid battery uptake highly likely in coming years. To empirically test the conclusions drawn from causal loop modelling, and to more accurately understand the strength and influence of battery adoption drivers, a stock-and-flow simulation model was created. The model demonstrated that across all scenarios tested, battery adoption in Queensland is likely to achieve mass-market uptake prior to the end of the 30 year simulation period. The base-case simulation found that by 2036, approximately 570,000 batteries would be installed representing 5,444 megawatt hours of capacity. This outcome would see substantial private sector investment, exceeding $8 billion, while achieving material contributions to greenhouse gas emission mitigation equivalent to approximately 6.2 million tonnes of carbon dioxide. The results of scenario analysis show that rates of battery adoption are a function of complex interactions between endogenous and exogenous variables. Impacts in one part of the supply chain, be it the unilateral action of a market participant, introduction of government policy or a completely exogenous influence such as an extreme weather event, not only increase battery adoption in their own right but can also reinforce several endogenous feedback loops. This affects electricity prices and strengthens non-financial motivations, driving even larger increases in battery adoption. Importantly, the model also shows that proactive efforts to integrate the technology in an efficient manner can drive beneficial outcomes along the supply chain, particularly where batteries are installed to help improve utilisation of the existing network. The potential risks and opportunities of residential PV and battery energy storage in coming years could be substantial. This dissertation makes an important contribution in this regard. It provides the basis with which to better understand the dynamics that could drive battery uptake while identifying possible leverage points to more effectively integrate the technology. In doing so, this research will help contribute to ongoing efforts to accelerate the transition towards a more sustainable, low-emission electricity supply system.

<p>Green hydrogen produced through electrolysis using renewable energy has the potential to decarbonize many sectors by replacing fossil fuels. Although production is currently marginal, green hydrogen projects are initiated and assessed all around the globe, ranging from small energy systems to large-scale production units. Previous studies have identified a wide range of key stakeholders that influence the diffusion of green hydrogen technologies. However, an understanding of the overall complexity of the emerging hydrogen sector regarding techno-economic, social, and environmental aspects is needed. The main objective of this study is to provide a depiction of an emerging sustainable technology sector by integrating various stakeholders’ perspectives. Based on this mapping key mechanisms that foster or hinder the production of green hydrogen will be identified. To perform our study, we chose a green hydrogen production project at the Hellisheiði geothermal power plant (Iceland) to construct a causal loop diagram (CLD) of the Icelandic green hydrogen production sector. Seven semi-structured interviews and one e-mail interview were conducted with relevant stakeholders. The National Innovation System was taken as a conceptual model in order to encourage the participants to answer in a systemic manner. Variables and causal links were then extracted from the interview transcripts using a coding process adapted from the literature. An overall CLD was constructed, showing the dynamic complexity of the system. The results show that mobility and export are the main sources for enhanced demand. Since most power companies in Iceland are state owned, green hydrogen supply comes mainly from energy companies, and strongly depends on political support. The importance of civil society, especially concerning the topics of nature protection and climate awareness, is also depicted. Additionally, a range of social, technical, and economical factors are identified, as well as their impact on the system’s behavior. The diagram allows for comprehension of stakeholders’ expectations and concerns with their potential consequences on the diffusion on green hydrogen technologies. The use of system dynamics and causal loop modelling provides a comprehensive view on the problem and helps to address issues that could be overlooked without it. Some of these causal chains could potentially lead to policy failure if not addressed early enough. The findings can be used to enhance cooperation between stakeholders and guide decision-making processes.</p>

Purpose Systemic risks affect financial market participants in many ways. However, the literature insists firmly that they are and, in fact, should be of little concern to (private) banks (as opposed to regulators). The purpose of this paper is to argue for the relevance of systemic risks for private banks as opposed to regulators only by making use of causal loop models as being traditionally used in the discipline of systems dynamics. In contrast to the starting point for all common risk-management frameworks in banks, which is the classification of risks into risk categories, the authors show that risk has been compartmentalized too much and provide a strong case for a really holistic approach.Design/methodology/approach Systems thinking, causal loop models and conceptual approach.Findings Relevance of systemic risks for private banks as opposed to regulators only. In contrast to the starting point for all common risk-management frameworks in banks, which is the classification of risks into risk categories, the authors show that risk has been compartmentalized too much and provide a strong case for a really holistic approach, which stems from using explanatory models such as causal loop diagrams. On top of that more explanatory models ought to be used for risk management purposes while banks currently rely too much on statistical-descriptive approaches.Originality/value Integration of systems thinking into risk management, which is novel: in contrast to the starting point for all common risk-management frameworks in banks, which is the classification of risks into risk categories, the authors show that risk has been compartmentalized too much and provide a strong case for a really holistic approach.

Enterprise modelling techniques support business process (re)engineering by capturing existing processes and based on perceived outputs, support the design of future process models capable of meeting enterprise requirements. System dynamics modelling tools on the other hand are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of enterprise and system dynamics modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise during the production of composite bearings. The case study testing reported has led to the specification of a new modelling methodology for analysing and managing dynamics and complexities in production systems. This methodology is based on a systematic transformation process, which synergises the use of a selection of public domain enterprise modelling, causal loop and continuous simulation modelling techniques. The success of the modelling process defined relies on the creation of useful CIMOSA process models which are then converted to causal loops. The causal loop models are then structured and translated to equivalent dynamic simulation models using the proprietary continuous simulation modelling tool iThink.

BackgroundTuberculosis (TB) is a major public health concern in South Africa and TB-related mortality remains unacceptably high. Numerous clinical studies have examined the direct causes of TB-related mortality, but its wider, systemic drivers are less well understood. Applying systems thinking, we aimed to identify factors underlying TB mortality in South Africa and describe their relationships. At a meeting organised by the ‘Optimising TB Treatment Outcomes’ task team of the National TB Think Tank, we drew on the wide expertise of attendees to identify factors underlying TB mortality in South Africa. We generated a causal loop diagram to illustrate how these factors relate to each other.ResultsMeeting attendees identified nine key variables: three ‘drivers’ (adequacy & availability of tools, implementation of guidelines, and the burden of bureaucracy); three ‘links’ (integration of health services, integration of data systems, and utilisation of prevention strategies); and three ‘outcomes’ (accessibility of services, patient empowerment, and socio-economic status). Through the development and refinement of the causal loop diagram, additional explanatory and linking variables were added and three important reinforcing loops identified. Loop 1, ‘Leadership and management for outcomes’ illustrated that poor leadership led to increased bureaucracy and reduced the accessibility of TB services, which increased TB-related mortality and reinforced poor leadership through patient empowerment. Loop 2, ‘Prevention and structural determinants’ describes the complex reinforcing loop between socio-economic status, patient empowerment, the poor uptake of TB and HIV prevention strategies and increasing TB mortality. Loop 3, ‘System capacity’ describes how fragmented leadership and limited resources compromise the workforce and the performance and accessibility of TB services, and how this negatively affects the demand for higher levels of stewardship.ConclusionsStrengthening leadership, reducing bureaucracy, improving integration across all levels of the system, increasing health care worker support, and using windows of opportunity to target points of leverage within the South African health system are needed to both strengthen the system and reduce TB mortality. Further refinement of this model may allow for the identification of additional areas of intervention.

BackgroundAround 40% of mortality after injuries is avoidable with access to quality care. Investments in interventions which maximise the number of injured persons who access and receive quality care are paramount, especially in low-resourced settings. Selecting such interventions within complex adaptive health systems is challenging due to the multiple interactions within these systems.MethodsWe created a conceptual map, or causal loop diagram (CLD), representing the health system for injury care, focused on challenges to improving patient outcomes in low- or middle-income countries (LMICs). We used the stages of seeking, reaching, receiving and remaining in care as the care pathway framework to conceptualise the diagram. Based on expert opinion and literature searches, we elicited micro (patient and their family), meso (health service) and macro (country context) factors which affect access to quality care at each stage of the care pathway and mapped interactions between them. Factors and their interactions were adjusted during a workshop with external experts. A CLD was created using Vensim to show relationships between all factors at all stages of the care pathway. Feedback loops within the CLD which are either reinforcing (perpetuating positive or negative change) or balancing (limiting change) were elicited. Leverage points were identified as factors which are present in multiple causal loops and are potential intervention points for maximal change.ResultsWe initially identified 41 factors affecting stage 1, 13 affecting stage 2, 51 affecting stage 3 and 49 affecting stage 4. Consolidating factors of a similar theme gave 45 unique factors for the overarching model; 13 micro, 20 meso and 12 macro. We constructed two CLDs—one for the overarching health system and the other focused on healthcare services at facilities. The health service-specific map contained 22 meso factors. We identified 928 reinforcing or balancing causal loops acting within the health system for injury care affecting health outcomes. Factors acting as leverage points involved in the largest number of feedback loops relate to trust in or perceptions of the health system (748 loops and 694 loops, respectively) and willingness to seek care (636 loops). The health service-focused CLD identified funding and the provision of quality care as the main leverage points (112 loops each).DiscussionOur work, using injury care as an exemplar, moves beyond understanding the impact of factors on patient outcomes in silos. Rather, in considering comprehensive connections between all factors on outcomes, we show interactions which could lead to unintended consequences and rapidly worsen or improve health outcomes. Our identification of trust and willingness to seek care as key leverage points suggests these should be focal points for research and investment.

Africa’s growth in public infrastructure provision has been fueled by the collective effort of the government authority and foreign private investors. China, through state-owned corporations, has become one of the leading infrastructure financier springing up numerous projects in transport, energy, oil and gas, water, and sewage sectors in Africa. Infrastructure procurement in developing countries comes with complexities and uncertainties. While Sino-Africa transnational public–private partnerships (TPPP) are becoming an increasingly popular route for public infrastructure procurement, their specific project risks and dynamics are not yet fully understood due to the typical assessment of risk autonomously. This paper identifies pertinent project risks in Sino-Africa TPPPs and applies system thinking in evaluating their behaviour and dynamics. An extensive review of literature and expert opinion employing semi-structured interviews was adopted in the identification and assessment of risk factors. Additionally, the study applied causal loop and interpretive structural modelling as an integrated approach in the assessment of risk behaviour from a systems perspective. Results indicate that risk factors associated with Sino-Africa TPPPs are interactive and portray curious systemic behaviour. Risk factors like force majeure and others associated with the governance structure and stability of the host African country are most influential, and their occurrence could inhibit project success. The study recommends that in conjunction with the conventional risk assessment by impact, systems thinking can be adopted to evaluate and comprehend the dynamics and interactions amongst the risk factors. This will improve risk assessment efficiency and fair allocation and treatment of risks as a conduit for project success and promote a win–win partnership for project actors.

BackgroundThe number of people living with dementia and mild cognitive impairment (MCI) is increasing. A supportive urban environment can prevent or delay the progress of cognitive decline. There is evidence...

This case study investigated the imperative of research transformation amongst academics at the selected Mangosuthu University of Technology (MUT) in South Africa, considering its low ranking of research output amongst 26 public higher education institutions (HEIs) by the South African Department of Higher Education and Training. The research problem for this case study was designed to investigate the main mitigating factors and barriers that inhibited academic careers of staff at this institution to transform to become productive researchers from a system dynamics perspective. Hence, the significance of this study was to address one of the three pillars of HEIs in terms of its research transformation and research productivity at this institution. Furthermore, this case study established how environmental dynamics holistically influenced academic staff to engage or not engage in research transformation. This was despite lucrative financial benefits offered, namely, research funding and study leave including other concrete incentives associated with research transformation. This was initiated for academic staff to inter alia, improving staff qualifications towards Master’s and Doctoral qualifications, conference presentations, technology transfer and knowledge production, and publications in accredited journals to produce the anticipated measured research output. Whilst there are a few prolific researchers within a few departments, it is alarmingly short in its endeavour towards attaining DHET research output goals and research transformation holistically at MUT. The aim of this study was to explore and develop an original system dynamics causal loop model with various components underscored by critical systems thinking and its impact of the holistic study per se. The research design for this study adopted a qualitative interpretative paradigm linked to system dynamics and the variables of the Causal Loop Diagram Model with an Interviewing Schedule. Thus, data was collected using a semi-structured interviewing schedule with open-ended questions in sync with a qualitative research design. Individual interviews were conducted with five academic staff members from each of the three faculties. Additionally, interviews with a focus group of six participants with similar interests were also included for the interviews. The key variables of the Causal Loop Model were tabulated and linked to research transformation from the participants at MUT. The data analysis collected from the interviews and policy documents were analysed under each of the research questions. Both participants’ reflections and institutional factors were also assimilated for the data analysis, vis-à-vis, research transformation at MUT. The findings revealed several individual and institutional factors contributing to low research transformation at this institution, namely, a small number of academic staff with PhDs, an uneven staff to student ratio, heavy workloads on teaching staff with limited time to engage in research productivity, unawareness of available incentives, lack of retention strategies of talented staff, poaching of academic staff, the interpretation of sabbatical leave and mentoring and supervision support initiatives. Furthermore, the study found several enablers aligned to research capacity building initiatives and critical factors to support a research culture at this institution. The main recommendations suggested were, inter-alia a buy-into research transformation by Executive Management and academic staff, improvement of vertical qualifications, supplementing academic support staff and tutors, employment of additional retired research professors, offering of structured mentoring and supervision assistance, specific training related to research productivity, review of the teaching workloads, implementation of sabbatical leave and retention policies. Finally, this case study has shown empirical evidence for further research opportunities related to research transformation in the higher education sector that could interface with the perceptions of research productivity and accelerate research outputs in peer reviewed accredited journals.