Loop Diagrams Research Articles

A system dynamics-based synergistic model of urban production-living-ecological systems: An analytical framework and case study.

Human-land coordination represents urbanization and is a key component of urban modernization. In this study, the theory of system dynamics was introduced, in which a "production-living-ecological" complex system was used based on the human-land coordination concept. Moreover, the characteristics of system dynamics of causal cycle, dynamic and sustainable development, man-land synergy, integrity and openness, and self-organization and adaptability were analyzed by dividing it into three subsystems: urban production, urban living, and urban ecological subsystems. Here, causal feedback and system structure flow diagrams were designed using causal loop diagrams and system structure flow diagrams to evaluate the causal relationships between variables and quantitatively analyzing their interactions between variables and predicting the future development of variables. Changsha City, China was selected as the case study area, where we constructed system dynamics practice equation model was then constructed to determine the interaction between the subsystems. Our findings indicate that by the year 2035 in the future, the overall trend of factors influencing the function of the subsystems such as population, GDP and built-up area are positively correlated with an increasing trend, and there are interactions between. Furthermore, these factors interact with each other, and a mutual correlation was found among the production-living-ecological functions system, Therefore, this study provides a novel perspective and exploratory practice for the study of the synergistic coupling of ecological, production, and living functions of cities and evaluating high-quality development of cities. Thus, the coupling and coordination of urban production, living and ecological functions reflects the coupling and coordination of the "people-land" relationship, which is the key to high-quality urban development.

Adoption and forecasting of technology: modeling the dynamics of cloud adoption using a system approach

PurposeThis paper aims to examine the dynamism of causal relationships among cloud computing (CC) adoption factors in the Indian context, considering the perspectives of both the cloud adopter and cloud provider.Design/methodology/approachThe case-study method has been used to understand the dynamics among the factors. Using data from specific cases in India, causal loop diagrams (CLDs) have been developed. System dynamic modeling (SDM) and simulation are used to study the relationships and their effect on the adoption rate.FindingsThe results revealed that adoption of CC depends on various factors such as persuasion (time-saving, cost-saving and word of mouth) and constraint factors (security and financial loss). However, it is seen that the adoption rate is very sensitive to changes in adoption per contact and word of mouth. Further, the adopter firm has a quicker time to market, which gives an added advantage to the firm. Also, with CC services, a firm can fulfill its projects or clients' requirements with little to no upfront investment in information technology (IT) services.Practical implicationsLack of security, standardization and undefined service-level agreements are a few pressing issues that make it difficult for firms to evaluate the performance and reliability of services. Hence, immediate attention is needed to make transparent policies on CC and its services, thereby building trust.Originality/valueThis is the first and only work that has tried to explore and empirically test the dynamics of critical factors while making an adoption decision, considering both the adopter and provider perspectives. This study shows the journey of a firm, starting from being a prospective adopter to an adopter and continuous user. The work also empirically tested how adopters of technology benefit from the technology.

Unveiling Maternal Health Insights During the COVID-19 Pandemic in Pakistan: Using Causal Loop Diagrams to Illuminate and Prevent Unintended Policy Effects.

Unveiling Maternal Health Insights During the COVID-19 Pandemic in Pakistan: Using Causal Loop Diagrams to Illuminate and Prevent Unintended Policy Effects.

Assessing the Cross-Border Impacts of Climate Change Response Measures on Iran: A Qualitative System Analysis

To achieve Goal 13, which addresses climate change and promotes sustainable development, mitigation policies, and measures have been implemented globally and nationally. However, such practices can lead to unintended side effects, which vary between countries based on their economic structures and governance status and may jeopardise the achievement of other goals. It is vital to alleviate these effects, especially in vulnerable countries. To do so, a comprehensive assessment of the potential impacts of policies must be conducted, and appropriate interventions must be implemented to mitigate the negative effects that have already begun in oil-exporting developing countries. This study aims to assess the cross-border consequences of response measures on Iran’s economic, social, and environmental status using a Causal Loop Diagram (CLD). The findings indicate that these policies directly affect the government’s revenues and expenditures, which in turn affect economic activities and indirectly affect socioeconomic variables.

Sexual risk-taking behavior amongst emerging adults in a tertiary institution of learning in Coastal Kenya: A qualitative study of stakeholders' perspectives using causal loop mapping.

It is known from previous studies that university students in sub-Saharan Africa (sSA) engage in sexual risk-taking behaviour (SRTB). However, there is paucity of data on factors contributing to SRTB among university students (emerging adults) at the Kenyan Coast thus hindering intervention planning. This study seeks to provide an in-depth qualitative understanding of the factors contributing to SRTB and their interconnectedness among university students at the Kenyan Coast combining qualitative research with a systems thinking approach. Using the ecological model, and employing in-depth interviews, we explored the perceptions of twenty-six key informants (twenty-one emerging adults and five other stakeholders) on what constitutes and influences SRTB among emerging adults at a tertiary institution of learning in Coastal Kenya. Data were analysed using a thematic framework approach. A causal loop diagram (CLD) was developed to map the interconnectedness of the correlates of SRTB. Our findings show that unprotected sex, transactional sex, cross-generational sex, multiple sex partnerships, gender-based violence, sex under influence of alcohol/drugs, early sex debut, and sharing sex toys were common SRTBs. Based on the ecological model and CLD, most of the reported risk factors were interconnected and operated at the individual level. Our study shows that emerging adults are frequently engaging in unprotected sex. Enhancing sexuality education programs for students in Kenyan universities and strengthening support systems including counselling for those using alcohol/drugs may help reduce SRTB among emerging adults in Kenyan universities.

Mapping pandemic responses in urban Indigenous Australia: Reflections on systems thinking and pandemic preparedness

ObjectivesWe investigate some of the strengths and challenges associated with Covid-19 responses in urban Indigenous communities in Brisbane, Australia. Our research reflects on the interconnected dynamics that impact health outcomes and mitigate or exacerbate the risk of Covid-19 spreading within urban Indigenous communities. MethodsThree systems thinking workshops were held in 2021 with Indigenous and non-Indigenous stakeholders (N15/workshop) from State and Federal services, along with Aboriginal Community Controlled Health Organisations. All worked in the urban Indigenous health sector. Stakeholders produced a Causal Loop Diagram (CLD) incorporating the critical feedbacks determining the dynamics influencing health outcomes. The aim of the research was to help stakeholders’ build awareness of how the structure of the system influences health outcomes. ResultsStakeholders identified 6 key dynamics which have a negative or positive impact on mitigating risks of Covid-19 infection. By mapping these dynamics within a CLD, 7 intervention points were identified. ConclusionsSystems thinking provides a useful tool in identifying the complexities associated with navigating health challenges, but further research is needed to develop frameworks that work in conjunction with Indigenous Australian methodologies. Implications for public healthIndigenous voices and communities must lie central to health responses/policies for Indigenous peoples. When systems thinking is done by or in collaboration with stakeholders it provides a visual language that can help design public health policy. What can be ascertained is that their effectiveness is predicated on systems thinking’s integration with Indigenous methodologies that acknowledges Indigenous self-determination and challenges Eurocentric representations of health and Indigeneity.

Applications of Participatory System Dynamics Methods to Public Health: A Systematic Review.

System dynamics, and specifically qualitative participatory applications of system dynamics, have potential to benefit public health research, scholarship, and practice. A systematic review was conducted to examine the existing applications of participatory system dynamics (PSD) to public health research. Three databases were searched using unique search terms related to PSD and methodological applications in public health research. A total of 57 unique articles met inclusion criteria and were included for review. The studies included for review were conducted globally and represent a wide breadth of public health issues. The review identified several advantages to adopting PSD methods in public health scholarship and practice. The PSD methods provide innovative frameworks for conceptualizing complex and nuanced public health problems. The participatory nature of PSD allows for increased community engagement and empowerment to address public health problems, as well as to mitigate existing power dynamics between research institutions and marginalized communities that are disproportionately impacted by social and health inequities. Finally, causal loop diagrams developed using PSD methods have unique potential to convey complex concepts to policy makers and interventionists. This systematic review reports evidence for PSD's potential to advance equity in public health research and practice.

Toward political economy of sustainable financing for immunization in the World Health Organization African Region through a systems thinking lens

There is an urgent need for countries in Africa to allocate more domestic financial resources to immunization so that national immunization programmes can attain self-reliance in line with World Health Organization's Immunization Agenda 2030. However, resource allocation is fundamentally a political process because other competing needs exist. Political economy analysis (PEA) can guide policy influencers in their engagement with decision makers to tilt their interest in support of sustainable immunization financing. PEA can provide a deeper understanding of the potential constraints and facilitators of a policy direction to expand the fiscal space for immunization using domestic resources within the context of a country's socioeconomic and political realities. To further advance the usefulness of PEA for decision making, a systems thinking lens should be applied to account for the inherent complexity of the social systems involved in resource allocation and implementation. Several methods and tools of systems thinking already exist and can be employed. Causal loop diagrams, when incorporated in a PEA of sustainable financing for immunization can aid the identification of feedback loops which can be used as leverage points for intervention.

Reinvigorating engineered noise controls: a systems approach.

Hearing loss is a major worldwide health issue affecting an estimated 1.5 billion people. Causes of hearing loss include genetics, chemicals, medications, lifestyle habits such as smoking, and noise. Noise is probably the largest contributing factor for hearing loss. Noise arises from the workplace, ambient environment, and leisure activities. The easiest noise sources to control are workplace and environmental. Workplace noise is unique in that the employer is responsible for the noise and the worker. Also, workers may be exposed to much higher levels of noise than they would accept elsewhere. Employers follow the traditional hierarchy of controls (substitution/engineering, administrative, personal protective equipment [PPE]). Substituting or engineering a lower noise level actually reduces the hazard present to the worker but demand more capital investment. Administrative and PPE controls can be effective, but enforcement and motivation are essential to reducing risk and there is still some hearing loss for a portion of the workers. The challenge is to estimate the costs more clearly for managers. A systems engineering approach can help visualize factors affecting hearing health. In this study, a systems engineering causal loop diagram (CLD) was developed to aid in understanding factors and their interrelationships. The CLD was then modeled in VenSim. The model was informed from the authors' expertise in hearing health and exposure science. Also, a case study was used to test the model. The model can be used to inform decision-makers of holistic costs for noise control options, with potentially better hearing health outcomes for workers. The CLD and cost model demonstrated a 4.3 year payback period for the engineered noise control in the case study. Systems thinking using a CLD and cost model for occupational hearing health controls can aid organizational managers in applying resources to control risk. Int J Occup Med Environ Health. 2023;36(5):672-84.

Exploring causal mechanisms and essential factors in the prevention and control of chlamydia in Guangdong, Southern China: a study protocol

BackgroundChlamydia Trachomatis (CT) is among the most prevalent sexually transmitted diseases (STDs) globally. According to the World Health Organization, more than 131 million people get infected with CT annually. CT is usually transmitted via sexual contact or perinatal exposure and can result in severe long-term complications. In developing nations, particularly, the prevention and control of CT is challenging. Hence, this study will explore the feedback mechanisms of chlamydia prevention and control, as well as identify the essential factors affecting the control and prevention of this infection in China.MethodsOur study will employ a mixed-methods research design that encompasses both qualitative and quantitative methods. Firstly, we will develop a causal loop diagram (CLD) based on the literature review and optimize it via in-depth interviews with stakeholders. Additionally, we will utilize a quantitative method called MICMAC(Impact Matrix Cross-Reference Multiplication Applied to a Classification tool) to obtain consensus among different stakeholders and pinpoint the key information. Next, the CLD will be transformed into a system dynamics model (SDM) to evaluate the feedback mechanisms within the CLD. The causality in the CLD will be modeled using mathematical equations, which facilitate the transformation into an SDM. As such, we will be able to analyze the dynamic behavior of the system and its response to different decisions.DiscussionOur study offers a systematic perspective on the control and prevention of chlamydia infection through system dynamics modeling, examining the dynamic properties and background factors of the system. The creation of the CLD affords stakeholders the chance to comprehend the functionality of their relationships and improve cooperation. Consequently, by evaluating the outcomes of these simulations, it will be possible to analyze and determine potential interventions and their effects on chlamydia infections. This modeling approach can help us gain insight into the dynamic characteristics of the system, evaluate the potential outcomes of different decisions, and design control strategies to either stabilize the system or adjust its behavior.

A Bayesian method for dam failure risk analysis using causal loop diagrams and word frequency analysis

A Bayesian method for dam failure risk analysis using causal loop diagrams and word frequency analysis

Group Model Building on causes and interventions for falls in Singapore: insights from a systems thinking approach

BackgroundFalls in older adults are the result of a complex web of interacting causes, that further results in other physical, emotional, and psychological sequelae. A conceptual framework that represents the reciprocal dynamics of these causal factors can enable clinicians, researchers, and policymakers to clarify goals in falls intervention in older adults.MethodsA Group Model Building (GMB) exercise was conducted with researchers and clinicians from academic units and public healthcare institutes in Singapore. The aim of the exercise was to produce a shared visual representation of the causal structure for falls and engage in discussions on how current and future falls intervention programmes can address falls in the older adults, especially in the Asian context. It was conducted in four steps: 1) Outlining and prioritising desirable patient outcomes, 2) Conceptual model building, 3) Identifying key intervention elements of effective falls intervention programmes, 4) Mapping of interventions to outcomes. This causal loop diagram (CLD) was then used to generate insights into the current understanding of falls causal relationships, current efforts in falls intervention in Singapore, and used to identify gaps in falls research that could be further advanced in future intervention studies.ResultsFour patient outcomes were identified by the group as key in falls intervention: 1) Falls, 2) Injurious falls, 3) Fear of falling, and 4) Restricted mobility and life space. A CLD of the reciprocal relationships between risk factors and these outcomes are represented in four sub-models: 1) Fear of falling, 2) Injuries associated with falls, 3) Caregiver overprotectiveness, 4) Post-traumatic stress disorder and psychological resilience. Through this GMB exercise, the group gained the following insights: (1) Psychological sequelae of falls is an important falls intervention outcome. (2) The effects of family overprotectiveness, psychological resilience, and PTSD in exacerbating the consequences of falls are not well understood. (3) There is a need to develop multi-component falls interventions to address the multitude of falls and falls related sequelae.ConclusionThis work illustrates the potential of GMB to promote shared understanding of complex healthcare problems and to provide a roadmap for the development of more effective preventive actions.

Exploring decision making factors in public buildings’ energy efficiency projects

This study aims to better understand the components of energy efficiency project systems and the decision factors influencing the adoption of energy efficiency projects in Indonesia. This study utilizes qualitative data analysis using content analysis on semi-structured interview transcripts. The variables identified are modeled in systemigram and causal loop diagrams to provide the components of the system and to illustrate the interrelationship of the decision factors based on the grounded theory approach. The study generates the system's components illustration explaining the stakeholders, policies, structures, activities, and resources that create the systems. Furthermore, the study found 32 decision factors modeled in the causal loop diagram and showed three dominant factors influencing the EE project adoption. Those are the organizational commitment, financial resources, and technical drivers.

Understanding the links between human health, ecosystem health, and food systems in Small Island Developing States using stakeholder-informed causal loop diagrams.

Globalized food systems are a major driver of climate change, biodiversity loss, environmental degradation, and the increasing prevalence of overweight and obesity in society. Small Island Developing States (SIDS) are particularly sensitive to the negative effects of rapid environmental change, with many also exhibiting a heavy reliance on food imports and high burdens of nutrition-related disease, resulting in calls to (re)localize their food systems. Such a transition represents a complex challenge, with adaptation interventions in one part of the food system contingent on the success of interventions in other parts. To help address this challenge, we used group model-building techniques from the science of system dynamics to engage food system stakeholders in Caribbean and Pacific SIDS. Our aim was to understand the drivers of unhealthy and unsustainable food systems in SIDS, and the potential role that increased local food production could play in transformative adaptation. We present two causal loop diagrams (CLDs) considered helpful in designing resilience-enhancing interventions in local food systems. These CLDs represent 'dynamic hypotheses' and provide starting points that can be adapted to local contexts for identifying food system factors, understanding the interactions between them, and co-creating and implementing adaptation interventions, particularly in SIDS. The results can help guide understanding of complexity, assist in the co-creation of interventions, and reduce the risk of maladaptive consequences.

Cultural adaptations and methodological innovations to group model building for the systems actions to reduce malnutrition in all its forms in Southeast Asian countries and China (SYSTAM CHINA-SEACS International Consortium) project

BackgroundGroup Model Building (GMB) is a participatory system dynamics method increasingly used to address complex public health issues like obesity. GMB represents a set of well-defined steps to engage key stakeholders to identify shared drivers and solutions of a given problem. However, GMB has not yet been applied specifically to develop multi-duty interventions that address multiple inter-related issues such as malnutrition in all its forms (MIAIF). Moreover, a recent systematic review of empirical applications of a systems approach to developing obesity interventions found no published work from non-western, low- and middle-income countries (LMICs). In this paper we describe adaptations and innovations to a common GMB process to co-develop systemic MIAIF interventions with Chinese decision-makers.MethodsWe developed, piloted and implemented multiple cultural adaptations and two methodological innovations to the commonly used GMB process in Fang Cheng Gang city, China. We included formal, ceremonial and policy maker engagement events before and between GMB workshops, and incorporated culturally tailored arrangements during participant recruitment (officials of the same seniority level joined the same workshop) and workshop activities (e.g., use of individual scoring activities and hand boards). We made changes to the commonly used GMB activities which enabled mapping of shared drivers of multiple health issues (in our case MIAIF) in a single causal loop diagram. We developed and used a ‘hybrid’ GMB format combining online and in person facilitation to reduce travel and associated climate impact.ResultsOur innovative GMB process led to high engagement and support from decision-makers representing diverse governmental departments across the whole food systems. We co-identified and prioritised systemic drivers and intervention themes of MIAIF. The city government established an official Local Action Group for long-term, inter-departmental implementation, monitoring and evaluation of the co-developed interventions. The ‘hybrid’ GMB format enabled great interactions while reducing international travel and mitigating limitations of fully online GMB process.ConclusionsCultural and methodological adaptations to the common GMB process for an Asian LMIC setting were successful. The ‘hybrid’ GMB format is feasible, cost-effective, and more environmentally friendly. These cultural adaptations could be considered for other Asian settings and beyond to address inter-related, complex issues such as MIAIF.

Using System Dynamics to Understand Transnational Corporate Power in Diet-Related Non-communicable Disease Prevention Policy-Making: A Case Study of South Africa.

Complex interactions between political economy factors and corporate power are increasingly recognized to prevent transformative policy action on non-communicable disease (NCD) prevention. System science offers promising methods for analysing such causal complexity. This study uses qualitative system dynamics methods to map the political economy of diet-related NCD (DR-NCD) prevention policy-making aiming to better understand the policy inertia observed in this area globally. We interviewed 25 key policy actors. We analysed the interviews using purposive text analysis (PTA). We developed individual then combined casual loop diagrams to generate a shared model representing the DR-NCD prevention policy-making system. Key variables/linkages identified from the literature were also included in the model. We validated the model in several steps including through stakeholder validation interviews. We identified several inter-linked feedback processes related to political economy factors that may entrench different forms of corporate power (instrumental, structural, and discursive) in DR-NCD prevention policy-making in South Africa over time. We also identified a number of feedback processes that have the potential to limit corporate power in this setting. Using complex system methods can be useful for more deeply understanding DR-NCD policy inertia. It is also useful for identifying potential leverage points within the system which may shift the existing power dynamics to facilitate greater political commitment for healthy, equitable, and sustainable food system transformation.

Constructing causal loop diagrams from large interview data sets

Abstract“Tackling the Root Causes Upstream of Unhealth Urban Development” is a trans‐disciplinary research project seeking to map and understand urban development decision‐making, visualise stakeholder mental models and codevelop improvement interventions. The project's primary data was gathered through 123 semistructured interviews. This article applies, compares, and discusses four variations on a method for constructing causal loop diagrams to illuminate mental models and collective decision‐making, based on manual and semiautomated processes applied to individual interview transcripts and datasets collected by thematic analysis. It concludes that while semiautomated approaches offer some time saving over manual approaches when applied to large data sets, care is required in interpreting and including peripheral contextual variables at the boundaries of the thematic analysis. Decisions regarding automation depend on the purpose of the modelling. Finally, the article recommends future applications record quantitative descriptors characterising the process of constructing CLDs from large qualitative data sets. © 2023 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

O.6.3-2 Implementation of a systems approach for co-creating actions to promote vocational students’ physical activity and wellbeing

Abstract Purpose Participatory systems approaches are suggested to address the complexity of health promotion in communities but has not been tested and adapted to school settings. The Data-driven Health Promotion at Vocational schools (Data Health) study aims to test and evaluate a systems approach to create collective actions to promote health among students. Three Group Model Building (GMB1-3) sessions were applied at eight vocational schools, with involvement from the local community, to develop a causal loop diagram (CLD), prioritise evidence-informed actions, and develop implementation strategies. This process evaluation aimed to determine if the GMB sessions were implemented as intended across intervention sites. Methods According to the Medical Research Council guidelines, six components were assessed: recruitment, reach, fidelity, dose delivered and received and context. Data included registration and observation notes from the workshops (n = 24) and recorded and transcribed qualitative interviews with the school programme-coordinators (n = 8). All data were analysed thematically. Results At all intervention sites GMB sessions were completed in 2022, with representation of students, school staff and managers, the municipal staff and local community actors. Based on local data, four intervention sites chose to target physical activity and four sites chose wellbeing. At most intervention sites, attendance (reach) from all participant groups fell below expectation. Especially recruitment of school staff (average no. of participants n = 1.75; range 0-3) and managers (average no. of participants n = 0.63; range 0-2) was challenging, with lack of time as the main reason for non-attendance. The expected 'dose' of the GMB sessions was delivered to participants, whereas fidelity, conceptualised as consistency in delivery, was mixed due to contextual circumstances e.g. school size. The school programme coordinators were generally positive about the GMB sessions but indicated mixed opinions about the value of CLDs to guide the discussion in this setting. Conclusions The Data Health study is the first to apply a systems approach to health promotion among vocational students and adapt GMB methodologies to school settings. Understanding the implementation of a systems approach in a school setting provides vital knowledge for researchers and practitioners regarding enablers and barriers of this approach. Funding Sources The Danish Regions, Tværspuljen, Helsefonden.

The Hidden Power of Sustainable Tourism Indicator Schemes: Have We Been Measuring Their Effectiveness All Wrong?

Evaluating whether sustainability indicator schemes contribute to better sustainable destination management has proven challenging. We adopt a systems thinking approach to shed light on the elusive impacts of sustainable tourism indicator schemes. We conduct online participatory workshops with 19 experts in sustainable tourism monitoring, to produce a causal loop diagram that illustrates how destination systems behave when indicator schemes are implemented. The results show that until now, these schemes have been expected to follow utopian, evidence-based, policy pathways to change, but we now understand that this linear-thinking approach fails to recognize the complex interplay of factors that occur during implementation. We find that indicator schemes can spark a rich, yet unappreciated, series of conceptual, instrumental, and structural dynamics. We conclude that the hidden power of these schemes lies in their ability to foster dialog, stimulate learning, incentivize network development, challenge stakeholder worldviews, and steer systems change toward sustainable destination management.

Great Resignation and Quiet Quitting as Post-pandemic Dangers to Knowledge Management

COVID-19 pandemic aftermaths include the emergence of new tendencies, such as the Quiet Quitting, and continuation of trends such as the Great Resignation, both of which have multiple knowledge-related impacts on individual, organizational and even national level. The aim of this paper is to show the mechanisms behind the Quiet Quitting and the Great Resignation from individual and organizational perspectives. Understanding them is the first step to developing remedies and building business resilience. The paper uses systems thinking approach to analyse the phenomena of the Quiet Quitting. Causal loop diagrams are used to show the mechanisms behind those tendencies, their antecedents and the impact they have on several aspects of business operation and management. The Quiet Quitting and the Great Resignation are multifaceted phenomena and pose several knowledge-related dangers to organizations, including disturbed knowledge flows, knowledge loss, diminished efficiency, lost informal friendship networks, and knowledge leakage to competition. Causal loop diagram indicates that complicated relations between various elements may produce surprising and unexpected outcomes. It presents also opportunities to use leverage points in order to substantially reduce negative outcomes. The paper is of a conceptual nature. In order to transform causal loop diagrams into full systems thinking models extensive data is required. Hence this paper is intended as a basis for further research. The understanding of mechanisms behind the Great Resignation and the Quiet Quitting is crucial for managers trying to develop strategies that would tackle those problems. The papers shows what leverage points can be used to mitigate risks of their adverse impact on business organizations. The Great Resignation and the Quiet Quitting are often perceived as results of the COVID-19 pandemic, yet data suggest they remain strong also in the post-pandemic business reality. The paper offers a holistic approach to those phenomena using individual and organisational perspectives. It provides important insights into their nature, which can be useful to numerous stakeholders, including knowledge workers, managers and business owners.