Loop Diagrams Research Articles

Business-IT alignment as a coevolution process: An empirical study

In this paper, we provide a detailed insight into the complex coevolution dynamics that shape the alignment process by analyzing how different mechanisms and factors are mutually related in complex networks of feedback loops.We combine insights from the literature on alignment as a (coevolution) process with literature on alignment as a stateto identify the different components of the organization’s socio-technical system that influence alignment, the relationships between these components, and the role that different factors play. In our empirical analysis (based multiple case studies) we then focus on the actual interplay between relevant factors. Using a causal loop diagramming approach - based on system dynamics – we analyze how these factors mutually influence each other through various feedback loops and thus shape the alignment process. We extend previous literature on the alignment process by identifying the way that the complex interplay between different factors shapes this process.By identifying the feedback loops between relevant factors, we also provide more insight into the complex bottom-up and top-down dynamics that shape the process, and that provide explanations for why this process is characterized by transitions between alignment and misalignment. For practice, our paper provides a deeper understanding of the alignment process, which is a precondition for improving alignment practices in organisations.

Improving Euler-Heisenberg-Schwinger Effective Action with Dressed Photons

We implement a longstanding proposal by Weisskopf to apply virtual polarization corrections to the in/out external fields in study of the Euler-Heisenberg-Schwinger effective action. Our approach requires distinguishing the electromagnetic and polarization fields based on mathematical tools developed by Bia{\l}ynicki-Birula, originally for the Born-Infeld action. Our solution is expressed as a differential equation where the one-loop effective action serves as input. As a first result of our approach, we recover the higher-order one-cut reducible loop diagrams discovered by Gies and Karbstein.

Coupling sum rules and oblique corrections in gauge-Higgs unification

Abstract In grand-unified-theory-inspired SO(5) × U(1)X × SU(3)C gauge-Higgs unification (GHU) in the Randall–Sundrum warped spacetime, the W- and Z-couplings of all 4D fermion modes become nontrivial. The W- and Z-couplings of zero-mode quarks and leptons slightly deviate from those in the SM, and the couplings take the matrix form in the space of Kaluza–Klein (KK) states. In particular, the 4D couplings and mass spectra in the KK states depend on the Aharonov–Bohm phase θH in the fifth dimension. Nevertheless there emerge three astonishing sum rules among those coupling matrices, which guarantees the finiteness of certain combinations of corrections to vacuum polarization tensors. We confirm by numerical evaluation that the equality in the sum rules holds with 5- to 7-digit accuracy. Based on the sum rules we propose improved oblique parameters in GHU. Oblique corrections due to fermion 1-loop diagrams are found to be small.

Investigating potential effects of mobility and accessibility services using the avoid-shift-improve framework

Mobility services and accessibility services could contribute to reduced car-dependency and a more sustainable transport system. However, uncertainty remains regarding what the effects will be and further research is needed.In this paper we examine potential effects on passenger car-travel in an urban context. To do so, we actuate the Avoid-Shift-Improve (ASI) framework using a System Dynamics approach and develop thematic Causal Loop Diagrams. We draw on the findings from a literature study and workshops engaging actors involved in creating visions and planning for the future of mobility and accessibility services in Stockholm, Sweden. The effects discovered are categorized as direct, enabling and structural/systemic, using a retrofitted version of the Three-Levels Model.Contributions include the mapping of mechanisms through which the services can have positive and negative effects in relation to ASI, demonstrating a high degree of interconnectedness. This includes potential synergetic and competitive relations between the services. In addition, the approach gives insight to potential cumulative impact of the services, relatable to Mobility as a Service, including ‘user near’ effects regarding, e.g., commuting and leisure travel, as well as systemic and structural level effects. A discussion is conducted on the implications for actors and policy-makers.

Three-body unitary coupled-channel analysis on η(1405/1475)

The recent BESIII data on $J/\psi\to\gamma(K_SK_S\pi^0)$, which is significantly more precise than earlier $\eta(1405/1475)$-related data, enables quantitative discussions on $\eta(1405/1475)$ at the previously unreachable level. We conduct a three-body unitary coupled-channel analysis of experimental Monte-Carlo outputs for radiative $J/\psi$ decays via $\eta(1405/1475)$: $K_SK_S\pi^0$ Dalitz plot distributions from the BESIII, and branching ratios of $\gamma(\eta\pi^+\pi^-)$ and $\gamma(\gamma\pi^+\pi^-)$ final states relative to that of $\gamma(K\bar{K}\pi)$. Our model systematically considers (multi-)loop diagrams and an associated triangle singularity, which is critical in making excellent predictions on $\eta(1405/1475)\to \pi\pi\pi$ lineshapes and branching ratios. The $\eta(1405/1475)$ pole locations are revealed for the first time. Two poles for $\eta(1405)$ are found on different Riemann sheets of the $K^*\bar{K}$ channel, while one pole for $\eta(1475)$. The $\eta(1405/1475)$ states are described with two bare states dressed by continuum states. The lower bare state would be an excited $\eta^\prime$, while the higher one could be an excited $\eta^{(\prime)}$, hybrid, glueball, or their mixture. This work presents the first-ever pole determination based on a manifestly three-body unitary coupled-channel framework applied to experimental three-body final state distributions (Dalitz plots).

Understanding the system dynamics of obesity-related behaviours in 10- to 14-year-old adolescents in Amsterdam from a multi-actor perspective.

To develop an understanding of the dynamics driving obesity-related behaviours in adolescents, we conducted systems-based analysis on a causal loop diagram (CLD) created from a multi-actor perspective, including academic researchers, adolescents and local stakeholders. The CLD contained 121 factors and 31 feedback loops. We identified six subsystems with their goals: (1) interaction between adolescents and the food environment, with profit maximisation as goal, (2) interaction between adolescents and the physical activity environment, with utility maximisation of outdoor spaces as goal, (3) interaction between adolescents and the online environment, with profit maximisation from technology use as goal, (4) interaction between adolescents, parenting and the wider socioeconomic environment, with a goal focused on individual parental responsibility, (5) interaction between healthcare professionals and families, with the goal resulting in treating obesity as an isolated problem, and (6) transition from childhood to adolescence, with the goal centring around adolescents' susceptibility to an environment that stimulates obesity-related behaviours. Analysis showed that inclusion of the researchers' and stakeholders' perspectives contributed to an understanding of how the system structure of an environment works. Integration of the adolescents' perspective enriched insights on how adolescents interact with that environment. The analysis further showed that the dynamics driving obesity-related behaviours are geared towards further reinforcing such behaviours.

Climate Change: a Multiplier for Terrorist Activity

Over the past ten years, both understanding and awareness of the links between climate change and security have increased. However, those links are not simple and clear. The growing impacts of climate change do not automatically lead to more violence and conflict. Rather, climate change acts as a threat multiplier. The study addresses the question of how the impacts of climate change are a contributing factor in the rise and growth of terrorism and political violence in African regions. To explain the complexity of the problem, a system dynamics model structure is presented in the form of casual loop diagrams. The dynamic behavior in livelihood arises from negative impacts of climate change on livelihoods in many countries and regions through, e.g. water and land scarcity, food insecurity and migration. The affected population groups are becoming more vulnerable not only to negative climate developments but also to recruitments by violent groups such as Al-Qaeda, Islamic State, Al-Shabaab or other militia. These terrorist groups can offer alternative livelihoods, economic motivations, and responses to possible political and economic dissatisfactions. This does not imply that there is a direct link between climate change and terrorists-related violence and conflict. However, environmental impacts and climatic change contributes to creating conditions in which these groups can thrive and facilitate the pursuit of their strategies. Further, violent groups are using natural resources as a weapon of war. In fragile environments, these groups can use water resources as a weapon or reduce access to natural resources. This development creates a dynamic for these groups, considering the fact that the scarcer resources become, the more power is given to those who controls them. Climate change will increasingly challenge the states’ abilities to provide services and stability. In particular, extreme climate events can threaten the relationship between governments and populations. In such a case, a poor and slow government response could contribute to further instability, fragility, violence and strengthening of violent groups.

Conceptualising the drivers of ultra-processed food production and consumption and their environmental impacts: A group model-building exercise

Using group model building we developed a series of causal loop diagrams identifying the environmental impacts of ultra-processed food (UPF) systems, and underlying system drivers, which was subsequently validated against the peer-reviewed literature. The final conceptual model displays the commercial, biological and social drivers of the UPF system, and the impacts on environmental sub-systems including climate, land, water and waste. It displays complex interactions between various environmental impacts, demonstrating how changes to one component of the system could have flow-on effects on other components. Trade-offs and uncertainties are discussed. The model has a wide range of applications including informing the design of quantitative analyses, identifying research gaps and potential policy trade-offs resulting from a reduction of ultra-processed food production and consumption.

Measuring Shifts in Mental Models in the Prevention of Childhood Obesity in Rural Australia.

Group model building is a participatory workshop technique used in system dynamics for developing community consensus to address complex problems by consensus building on individual assumptions. This study examines changes in individual mental models of the complex problem of childhood obesity following participation in group model building (GMB), as part of a larger community-based system dynamics project. Data are drawn from GMB participants across six community sites in the Whole of Systems Trial of Prevention Strategies for Childhood Obesity (WHO STOPS) in rural and regional Victoria, Australia. Each community participated in two GMB sessions resulting in a causal loop diagram (CLD) of drivers of childhood obesity for each community. Presurvey and postsurvey captured participants' perspectives before and after (n = 25) participation in both GMB sessions and a blend of inductive and deductive qualitative content analysis was used to code individual responses. Three calculations were used to determine the number of responses, whether responses were a result of persuasion from others, and comparison of responses to those found in the CLD. Our study found participant mental models shifted during the course of the GMB sessions, with some responses persuaded by others and 75% of new insights identified in CLDs created by communities. The GMB process created a platform for participants to share ideas and learn from each other. In addition, participants listed new insights about childhood obesity in their community through developing CLDs.

Determinants of pupils' energy drink consumption – Findings from a Hungarian primary school

Consumption of energy drinks is harmful in childhood and adolescence, and its increasing popularity makes it a public health threat in this age group. Our study aimed to assess energy drink (ED) consumption and identify the context and determinants of its consumption at a Hungarian primary school. A mixed-method approach was used for the research, including a survey filled in by 157 10-15-year-old pupils and World Café workshops (WCWs) involving pupils, home-room teachers, and Parental Council representatives (N = 39). The Jamovi 2.2.5. The software was used to perform descriptive statistics and logistic regression, and a causal loop diagram was created based on the results of the WCWs. The survey results revealed that almost one-third of the pupils consumed EDs regularly, and most daily consumers drank high amounts (500ml). Most students considered ED consumption unhealthy, yet every fifth drank them. Buying breakfast on the way to school increased the odds of ED consumption almost threefold. According to the WCWs' findings, the determinants of ED consumption were embedded in two critical contextual sets; one was the need for energy and concentration boost and the Perception of high social acceptance of ED consumption. Our results suggest that interventions to reduce students' ED consumption need to include increased parents' involvement in controlling their children's screen time and encouraging them to provide breakfast at home for their children. There is also an urgent need to restrict the marketing of EDs and strictly regulate access to EDs for under-18s.

Evaluating policy complexity with Causal Loop Diagrams

Methods to capture the complexity of using policy instruments would allow us to better evaluate the reasons for their effectiveness. Drawing from complexity science, we produce a Causal Loop Diagram to analyse the implementation of two informational policy instruments in a tourism destination: the Global Sustainable Tourism Council criteria and the European Tourism Indicator Scheme. To interpret the emerging system structure, we use complexity theory concepts of emergence; interdependence and interconnectivity; co-evolution; self-organisation; feedback; historicity and path dependence. This qualitative methodology sheds light on the interplay of factors that facilitate and impede the continuous use of these policy instruments. It shows how adopting a complexity science approach to evaluation studies can be invaluable to making tourism policy interventions more impactful.

Applying systems thinking to unravel the mechanisms underlying orthostatic hypotension related fall risk

Orthostatic hypotension (OH) is an established and common cardiovascular risk factor for falls. An in-depth understanding of the various interacting pathophysiological pathways contributing to OH-related falls is essential to guide improvements in diagnostic and treatment opportunities. We applied systems thinking to multidisciplinary map out causal mechanisms and risk factors. For this, we used group model building (GMB) to develop a causal loop diagram (CLD). The GMB was based on the input of experts from multiple domains related to OH and falls and all proposed mechanisms were supported by scientific literature. Our CLD is a conceptual representation of factors involved in OH-related falls, and their interrelatedness. Network analysis and feedback loops were applied to analyze and interpret the CLD, and quantitatively summarize the function and relative importance of the variables. Our CLD contains 50 variables distributed over three intrinsic domains (cerebral, cardiovascular, and musculoskeletal), and an extrinsic domain (e.g., medications). Between the variables, 181 connections and 65 feedback loops were identified. Decreased cerebral blood flow, low blood pressure, impaired baroreflex activity, and physical inactivity were identified as key factors involved in OH-related falls, based on their high centralities. Our CLD reflects the multifactorial pathophysiology of OH-related falls. It enables us to identify key elements, suggesting their potential for new diagnostic and treatment approaches in fall prevention. The interactive online CLD renders it suitable for both research and educational purposes and this CLD is the first step in the development of a computational model for simulating the effects of risk factors on falls.

Effects of workload on medication administration errors in nursing: an analysis based on system dynamics modeling

Medication administration errors account for a relatively high proportion of medical errors, with more than 50% occurring at the nursing administration stage. Nursing is characterized by a large amount of work, rigid working hours, high information cognitive intensity, and frequent information updates. The high workload of nurses is a significant cause of medication administration errors. In this study, a literature analysis was used to determine the elements of the system dynamics model, and the causal loop diagram was used to draw the relationship framework among the elements. Vensim personal learning edition and interview surveys were then used for model validation and simulation. First, 302 case analyses of medication administration errors collected from the three metropolitan area hospitals were used to construct the causal loop diagram, the stock and flow map of the medication administration error system, and the dynamics model; second, the model was tested from theoretical and historical data simulation perspectives; finally, the system dynamics model proposed in this study was used to simulate a medical institution from overtime and policy perspectives. Through system dynamics modeling, the inducing mechanism of workload on medication administration errors in nursing operations was elucidated, and corresponding suggestions for prevention were provided. In addition, ideas and basis for optimizing the medication administration process, improving workload, and preventing medication administration errors considering workload were provided.

Developing a theoretical framework to assist policymaking for retrofitting residential buildings using system player analysis and causal loop diagrams

Retrofit of urban residential buildings (RURB) has great potential for improving energy conservation and sustainability, but it encounters challenges due to the lack of incentive policy and the unwillingness of residents. The RURB retrofitting process is a complex system involving anthropic factors such as proper definition, components, and unclear problems. This study aims to clarify its complex nature concerning the cognition and interactions of the RURB system so to develop a theoretical framework by applying the system thinking approach of System Player Analysis (SPA) with realistic qualitative data collected from four defined main players in the RURB system. Semi-structured interviews and questionnaire surveys were conducted to collect information from RURB policymakers, designers and engineers, scholars, and residents. The Hot Summer and Cold Winter climate zone (HSCW) in China was selected as the case study area. Roles, outputs, issues, demands, and features of individual RURB system players are revealed with unique local retrofit preferences whilst system cognition is clearly defined to create Causal Loop Diagrams (CLD) for RURB to help understand the interactions between system variables. The discussion based on SPA and CLD results provides valuable suggestions for addressing the identified systemic problems of RURB and an extensive theoretical basis for future retrofitting of residential buildings.

Viewing the Role of Alternate Care Service Pathways in the Emergency Care System through a Causal Loop Diagram Lens

Globally, Emergency Care Systems (ECS) are a critical resource that needs to be used judiciously as demand can easily exceed supply capacity. Sub-optimal ECS use contributes to Emergency Department (ED) crowding; this adversely affects ECS as well as system-wide service performance. Alternate Care Service Pathways (ACSPs) are innovations intended to mitigate ED crowding by re-routing less-urgent cases to sites of care other than the ED. As in other countries, policymakers in Singapore need to respond to increasing ED utilization and are evaluating the introduction of ACSPs. However, developing ACSPs is costly, entails tinkering with established critical services, and runs the risk of unintended adverse consequences. Through a Causal Loop Diagram (CLD) developed in four stages, we present a view of the current Singapore ECS and the intended role of ACSPs in relieving its stress. This exercise suggests that to be successful ACSPs must change the prevailing mental model of the ED as a “one-stop shop” but should focus on integrating with primary care. The discussions stimulated by the development, critiquing, and revision of the CLD highlighted the importance of accounting for the reservations of stakeholders for changes. The CLD has enhanced shared understanding and will be used to guide quantitative simulation modeling to promote informed policy.

Dryland river regime shifts in Iran: Drivers and feedbacks

AbstractIn the Anthropocene, human activities have created unprecedented changes and nonlinear relationships between humans and nature. These changes can be much faster and more intense in arid and semiarid areas that have been affected by intense human activities. Iran has climates from very humid to very dry, but arid and semiarid climates cover the country's largest area. Many of these arid areas have undergone severe changes in their surface and groundwater ecosystems in recent years, which have caused severe damage to humans and the environment in the area and surrounding areas. Therefore, in this study, using the theory of regime shifts, the time series of the Zayandeh‐Rud River Basin in the center of Iran were analyzed. First, the data of the desired time series in the period of 1986–2018 was arranged seasonally. Then, using the sequential t‐test method, regime shifts in these time series were identified, and then, causal loop diagrams of these shifts and their drivers and feedbacks were interpreted. The results showed that in the time series of quantity and quality of surface water and groundwater level in the studied stations and aquifers, regime shifts can be identified. Regime shifts were also identified in the time series of agricultural land area. These shifts have occurred with the increase in human activities since the early 1950s in the metropolis of Isfahan, the increase in agricultural and industrial exploitation, and consequently, the increase in population. When this reinforcing feedback loop becomes dominant, the Zayandeh‐Rud River system has shifted from a regime of rich water resources to a regime of poor water resources. However, by recognizing and systematically analyzing these shifts, the Zayandeh‐Rud River system can be directed toward a sustainable system through structural reform, negotiation, and redefining goals.

Informing adaptation strategy through mapping the dynamics linking climate change, health, and other human systems: Case studies from Georgia, Lebanon, Mozambique and Costa Rica

While scientific research supporting mitigation of further global temperature rise remains a major priority, CoP26 and CoP27 saw increased recognition of the importance of research that informs adaptation to irreversible changes in climate and the increasing threats of extreme weather events. Such work is inevitably and appropriately contextual, but efforts to generalise principles that inform local strategies for adaptation and resilience are likely crucial. Systems approaches are particularly promising in this regard. This study adopted a system dynamics framing to consider linkages between climate change and population health across four low- and middle-income country settings with a view to identifying priority inter-sectoral adaptation measures in each. On the basis of a focused literature review in each setting, we developed preliminary causal loop diagrams (CLD) addressing dynamics operating in Mozambique, Lebanon, Costa Rica, and Georgia. Participatory workshops in each setting convened technical experts from different disciplines to review and refine this causal loop analysis, and identify key drivers and leverage points for adaptation strategy. While analyses reflected the unique dynamics of each setting, common leverage points were identified across sites. These comprised: i) early warning/preparedness regarding extreme events (thus mitigating risk exposure); ii) adapted agricultural practices (to sustain food security and community livelihoods in changing environmental conditions); iii) urban planning (to strengthen the quality of housing and infrastructure and thus reduce population exposure to risks); iv) health systems resilience (to maintain access to quality healthcare for treatment of disease associated with increased risk exposure and other conditions for which access may be disrupted by extreme events); and v) social security (supporting the livelihoods of vulnerable communities and enabling their access to public services, including healthcare). System dynamics modelling methods can provide a valuable mechanism for convening actors across multiple sectors to consider the development of adaptation strategies.

Revisiting the matching of black hole tidal responses: A systematic study of relativistic and logarithmic corrections

The worldline effective field theory (EFT) gives a gauge-invariant definition of black hole conservative tidal responses (Love numbers), dissipation numbers, and their spin-0 and spin-1 analogs. In the first part of this paper we show how the EFT allows us to circumvent the source/response ambiguity without having to use the analytic continuation prescription. The source/response ambiguity appears if relativistic corrections to external sources overlap with the response. However, these corrections can be clearly identified and isolated using the EFT. We illustrate that by explicitly computing static one-point functions of various external fields perturbing the four-dimensional Schwarzschild geometry. Upon resumming all relevant Feynman diagrams, we find that the relativistic terms that may mimic the response actually vanish for static black holes. Thus, the extraction of Love numbers from matching the EFT and general relativity (GR) calculations is completely unambiguous, and it confirms previous results that the Love numbers vanish identically for all types of perturbations. We also study in detail another type of fine-tuning in the EFT, the absence of Love numbers' running. We show that logarithmic corrections to Love numbers do stem from individual loop diagrams in generic gauges, but cancel after all diagrams are summed over. In the particular cases of spin-0 and spin-2 fields the logarithms are completely absent if one uses the Kaluza-Klein metric decomposition. In the second part of the paper we compute frequency-dependent dissipative response contributions to the one-point functions using the Schwinger-Keldysh formalism. We extract black hole dissipation numbers by comparing the one-point functions in the EFT and GR. Our results are in perfect agreement with those obtained from a manifestly gauge-invariant matching of absorption cross sections.

A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand

Water supply and demand management (WSDM) is essential for developing sustainable cities and societies. WSDM is only effective when tackled from the perspective of a holistic system understanding that considers social, environmental, hydrological, and economic (SEHEc) sub-systems. System dynamics modeling (SDM) is recommended by water resource researchers as it models the biophysical and socio-economic systems simultaneously. This study presents a comprehensive literature review of SDM applications in sustainable WSDM. The reviewed articles were methodologically analyzed considering SEHEc sub-systems and the type of modeling approach used. This study revealed that problem conceptualization using the causal loop diagram (CLD) was performed in only 58% of the studies. Moreover, 70% of the reviewed articles used the stock flow diagram (SFD) to perform a quantitative system analysis. Furthermore, stakeholder engagement plays a significant role in understanding the core issues and divergent views and needs of users, but it was incorporated by only 36% of the studies. Although climate change significantly affects water management strategies, only 51% of the reviewed articles considered it. Although the scenario analysis is supported by simulation models, they further require the optimization models to yield optimal key parameter values. One noticeable finding is that only 12% of the articles used quantitative models to complement SDM for the decision-making process. The models included agent-based modeling (ABM), Bayesian networking (BN), analytical hierarchy approach (AHP), and simulation optimization multi-objective optimization (MOO). The solution approaches included the genetic algorithm (GA), particle swarm optimization (PSO), and the non-dominated sorting genetic algorithm (NSGA-II). The key findings for the sustainable development of water resources included the per capita water reduction, water conservation through public awareness campaigns, the use of treated wastewater, the adoption of efficient irrigation practices including drip irrigation, the cultivation of low-water-consuming crops in water-stressed regions, and regulations to control the overexploitation of groundwater. In conclusion, it is established that SDM is an effective tool for devising strategies that enable sustainable water supply and demand management.

Using dynamic modelling to enhance the assessment of the beef water footprint

Current water footprint assessment methods make a meaningful assessment of livestock water consumption difficult as they are mainly static, thus poorly adaptable to understanding future water consumption and requirements. They lack the integration of fundamental ruminant nutrition and growth equations within a dynamic context that accounts for short- and long-term behaviour and time delays associated with economically significant beef-producing areas. The current study utilised the System Dynamics methodology to conceptualise a water footprint for beef cattle within a dynamic and mechanistic modelling framework. The problem of assessing the water footprint of beef cattle was articulated, and a dynamic hypothesis was formed to represent the Texas livestock water use system as the initial step in developing the Dynamic Beef Water Footprint model (DWFB). The dynamic hypothesis development resulted in three causal loop diagrams (CLD): cattle population, growth and nutrition, and the livestock water footprint, that captured the daily water footprint of beef (WFB). Simulations and sensitivity analysis from the hypothesised CLD structures indicated that the framework was able to capture the dynamic behaviour of the WFB system. These behaviours included key reinforcing and balancing feedback processes that drive the WFB. It is extremely difficult to identify policy interventions (i.e., management strategies) for complex systems, like the U.S. beef cattle system, because there are many actors (i.e., cow-calf, stocker, feedlot) and interrelated variables that have delayed effects within and across the supply chain. Identification and understanding of feedback processes driving water use over time will help to overcome policy resistance for more sustainable beef production. Thus, the causal loops identified in the current study provide a system-level insight for the drivers of the WFB within and across each major segment of the beef supply chain to address freshwater concerns more adequately. Further, the nutrient scenarios and sensitivity analysis revealed that the high versus low nutrient composition of pasture, hay, and concentrates resulted in a significant difference in the WFB (2 669 L/kg boneless beef, P < 0.05). The WFB was sensitive to changes in nutrient composition and specific water demand (m3/t) for each production phase, not only phases with high levels of concentrate feed use. As models evolve, there is potential for the DWFB to integrate precision livestock data, further improving quantification of the WFB, precision water-efficient strategies, and selection of water-efficient livestock.