Systems, Volume 9, Issue 3 (September 2021) – 24 articles

Significant universal research regarding causes of delay in road projects has been carried out based on expert opinion. This study classifies and standardizes all road construction delay factors found in the literature by developing a common risk breakdown structure (RBS) to allow for comparison between real project delay factors, and the study also proposes two delay risk assessment models (DRAMs) based on delay information from 120 real projects constructed in a similar environment with akin procurement and contract policies. The first calculates the risk priority number (RPN) and the second applies the Technique for Order Preference by Similarity to Ideal Situation (TOPSIS) multi-criteria decision-making method (MCDM). The results showed that four specific delay factors dominate in Greek road construction for which relevant mitigation proposals are made. The proposed DRAMs, while calibrated for application in Greece, can be adapted to any construction environment for which real project data is available to provide a tool for transferring experience from past projects to future projects and from accomplished to novice public client decision makers. Full article

This article develops a method to model, analyze, and design military microgrids with the objective to improve their resilience in the face of disconnections from the larger electrical grid. Military microgrids provide power to installation and base facilities to enable base mission objective accomplishments that are related to national security. Previous research, tools, and methods for microgrid design and assessment do not adequately address resilience in terms of accomplishing mission objectives and instead primarily focus on economic outcomes. This article proposes a novel metric to quantify microgrid resilience in terms of its ability to minimize the impact of power disruption on missions supported by the microgrid. The metric is used in a novel design method to ensure an islanded military microgrid can continue operations while disconnected for a two-week duration. Our model examines the ability to continue mission operations subject to various microgrid disruptions as well as equipment reliability. Full article

Despite a range of federal and state interventions to slow the spread of COVID-19, the US has seen millions of infections and hundreds of thousands of deaths. Top-down mandates have been ineffective because the community spread of the pandemic has been influenced by complex local dynamics that have evolved over time. Systems thinking approaches, specifically causal loop diagrams, and leverage points, are important techniques for representing complexity at the local level and identifying responsive systems change opportunities. This commentary presents a causal loop diagram highlighting the progressive effects of prolonged state-level COVID-19 mandates at the community level. We also identify potential system leverage points that address these effects and present an imagined future state causal loop diagram in which these solutions are implemented. Our future system demonstrates the importance of collaborations to enable community-driven, bottom-up approaches to public health crises, such as the COVID-19 pandemic, that are adaptive and responsive to local needs. Full article

This paper aims to provide a state-of-the-art overview in research on Accounting Information Systems, analyzing scientific production characteristics and identifying this topic research trends. A quantitative bibliometric analysis is conducted on papers specifically focused on Accounting Information Systems, published in journals indexed on Web of Science database. The research methodology and design were based on an inductive approach of a set of studies with the objective of theoretical development in the field of investigation. We found 144 articles on this subject. The first article was published in 1973. However, most papers were published during the last 10 years although the highest interest in Accounting Information Systems study among scholars concentrates on a short period, which is around 2020. We identify three research topics, as the following research trends: (1) the Accounting Information System impact in the organization (e.g., performance, innovation, reorganization of activities, information reporting); (2) the Accounting Information System Construction, (3) the importance of implementation of the Accounting Information System in small and medium-sized enterprises and Public-Sector; and (4) the factors that contribute to Accounting Information System efficiency/quality. These themes fit into a theoretical framework, in which agency and contingency theory are highlighted. In addition, by promoting the analysis of strict bibliometric tools, we also identified authors, journals, organizations and countries/regions that contributed most to the development of the investigation in this research topic. The results of this research add insights to the existing literature and serve as a guide for future research in Accounting Information Systems context, as well as help organizations, public, private and governments to establish their strategies in this area. Full article

Community coalitions can address local issues with deep, historic, and contextual understanding that enables customized implementation of evidence-based strategies. The individuals within the coalition, their partnerships, and the social context is likely an important component of unraveling the challenges of implementation so interventions reach people in need. We focus on the relevance of baseline coalition-committee network (CCN), the networks of purposely formed subcommittees within community coalitions, structure as one of the moderating, theoretical links between community coalition social networks and intervention success. We explore the baseline composition and characteristics of five CCNs at the beginning of childhood obesity prevention interventions. Using a combination of social network, multidimensional scaling, and correspondence analyses, we examine the structure and heterogeneity of five CCNs, each consisting of a core group of stakeholders in the coalition and sometimes the broader community itself. Cross-sectional analyses are used to examine the composition of coalition-committees related to network density, centralization, hierarchy, and coalition demographics and characteristics. Results indicate that CCNs are patterned in their structure and characteristics, and we discuss whether adjustments to childhood obesity prevention interventions according to baseline structure and characteristics could be advantageous for intervention implementation. Together, these findings can inform future longitudinal investigations into CCN network structure. Full article

The complexity, multidimensionality, and persistence of the COVID-19 pandemic have prompted both researchers and policymakers to turn to transdisciplinary methods in dealing with the wickedness of the crisis. While there are increasing calls to use systems thinking to address the intricacy of COVID-19, examples of practical applications of systems thinking are still scarce. We revealed and reviewed eight studies which developed causal loop diagrams (CLDs) to assess the impact of the COVID-19 pandemic on a broader socioeconomic system. We find that major drivers across all studies are the magnitude of the infection spread and government interventions to curb the pandemic, while the most impacted variables are public perception of the pandemic and the risk of infection. The reviewed COVID-19 CLDs consistently exhibit certain complexity patterns, for example, they contain a higher number of two- and three-element feedback loops than comparable random networks. However, they fall short in representing linear complexity such as multiple causes and effects, as well as cascading impacts. We also discuss good practices for creating and presenting CLDs using the reviewed diagrams as illustration. We suggest that increasing transparency and rigor of the CLD development processes can help to overcome the lack of systems thinking applications to address the challenges of the COVID-19 crisis. Full article

This study aims towards identifying and modelling the significant factors which act as enablers for the branded content to be used strategically by marketers as a marketing tool in the COVID-19 era. A qualitative approach was adopted for this study, and significant factors associated with branded content were identified from the literature review and primary survey. The factors were then verified by the experts in the area of branding and digital marketing. Total interpretive structural modelling (TISM) and Decision-making Trial and Evaluation Laboratory (DEMATEL) techniques were used to model the factors as per their contextual relationships. As per the model outcomes from TISM and DEMATEL approaches, branded content is an efficient marketing tool that promises value delivery to stakeholders. This, in turn, depends on the authenticity and transparency in content development and distribution. The most significant driving enablers for the system suggest efficient measurement and evaluation strategies and the customer as co-creator for the branded content. Full article

Within emerging markets, ensuring the competitiveness of manufacturing companies is crucial to their success. The integration of new business possibilities, such as Product-Service-Systems (PSS) can provide one suitable solution. Especially within the architecture development process, large amounts of interconnected data and data types need to be processed and versioned. This leads to a significant lack of data consistency and continuity along the development process of modular PSS architectures. This lack of consistency and continuity leads to a process being prone to errors, representing a significant negative impact onto the company’s value-added stream. We provide one possible solution to these issues by presenting a PSS architecture modularization approach based upon the modularization methods of the Integrated PKT-Approach. Using concepts of Model-Based Systems Engineering (MBSE) for modelling these architectures, automated and dynamic analyses of the architecture for the iteration and harmonization of the PSS architecture under development are enabled. The at first generically described approach is further detailed in the second part of this contribution by applying it to an industry case study for mobile laser welding systems. As a result, a clear support for the visualization of architecture iteration aspects as well as for the enhancement of data consistency and continuity is given. Full article

Reducing car dependency requires orchestrated multi-sectoral, multi-policy action in a complex landscape. Thus, development of proposed interventions to reduce car dependency should be informed by systems thinking, complexity science, and socio-technical transition theory. We aim to co-design sustainable systems-oriented intervention approaches to reduce car dependency in Belfast. The study includes seven integrated tasks—1: Map stakeholders and partnerships influencing car dependency using stakeholder network analysis; 2: A review of systematic reviews regarding interventions to reduce car dependency; 3: Map-related policies via analysis of policy documents and semi-structured interviews; 4: A participatory group model building workshop to co-produce a shared understanding of the complex system perpetuating car dependency and a transition vision; 5: Using Discrete Choice Experiments, survey road users to evaluate the importance of transport infrastructure attributes on car dependency and on alternative modes of travel; 6: Citizen juries will ‘sense-check’ possible actions; and, 7: Stakeholders will interpret the findings, plan orchestrated multi-sectoral action, and agree on ways to sustain collaborations towards the common vision of reducing car dependency. We expect to attain a systemic view of the car dependency issue, potential intervention approaches to reduce it, and a framework for their integration through the co-ordination of stakeholder actions. Full article

Within the field of chronic disease prevention, research efforts have moved to better understand, describe, and address the complex drivers of various health conditions. Change-making is prominent in this paper, and systems thinking and systems change are prioritised as core elements of prevention research. We report how the process of developing a theory of systems change can assist prevention research to progress from understanding systems, towards impactful action within those systems. Based on Foster-Fishman and Watson’s ABLe change framework, a Prevention Systems Change Framework (PSCF) was adapted and applied to an Australian case study of the drivers of healthy and equitable eating as a structured reflective practice. The PSCF comprises four components: building a systemic lens on prevention, holding a continual implementation focus, integrating the systemic lens and implementation focus, and developing a theory of change. Application of the framework as part of a systemic evaluation process enabled a detailed and critical assessment of the healthy and equitable eating project goals and culminated in the development of a theory of prevention systems change specific to that project, to guide future research and action. Arguably, if prevention research is to support improved health outcomes, it must be more explicitly linked to creating systems change. Full article

Background: The UK was one of the countries worst affected by the COVID-19 pandemic in Europe. A strict lockdown from early 2021 combined with an aggressive vaccination programme enabled a gradual easing of lockdown measures to be introduced whilst both deaths and reported case numbers reduced to less than 3% of their peak. The emergence of the Delta variant in April 2021 has reversed this trend, and the UK is once again experiencing surging cases, albeit with reduced average severity due to the success of the vaccination rollout. This study presents the results of a modelling exercise which simulates the progression of the pandemic in the UK through projection of daily case numbers as lockdown lifts. Methods: A simulation model based on the Susceptible-Exposed-Infected-Recovered structure was built. A timeline of UK lockdown measures was used to simulate the changing restrictions. The model was tailored for the UK, with some values set based on research and others obtained through calibration against 16 months of historical data. Results: The model projects that if lockdown restrictions are lifted in July 2021, UK COVID-19 cases will peak at hundreds of thousands daily in most viable scenarios, reducing in late 2021 as immunity acquired through both vaccination and infection reduces the susceptible population percentage. Further lockdown measures can be used to reduce daily cases. Other than the ever-present threat of the emergence of new variants, the most significant unknown factors affecting the profile of the pandemic in the UK are the length and strength of immunity, with daily peak cases over 50% higher if immunity lasts 8 months compared to 12 months. Another significant factor is the percentage of unreported cases. The reduced case severity associated with vaccination may lead to a higher proportion of unreported mild or asymptomatic cases, meaning that unmanaged infections resulting from unknown cases will continue to be a major source of infection. Conclusions: Further research into the length and strength of both recovered and vaccinated COVID-19 immunity is critical to delivering more accurate projections from models, thus enabling more finely tuned policy decisions. The model presented in this article, whilst by no means perfect, aims to contribute to greater transparency of the modelling process, which can only increase trust between policy makers, journalists and the general public. Full article

Customized pharmaceutical products aim to comply with the individual needs of a patient to enhance the treatment outcome. The current pharmaceutical production paradigm is, however, dominated by mass production, where the pharmaceutical products embrace a one-size-fits-all design with a low possibility of treatment optimization to patient needs. This production paradigm is not designed or intended for customized pharmaceutical products and operating this production context for customized pharmaceutical products is argued to be cost-inefficient. To address this challenge of inefficient production of customized pharmaceutical products, this study proposes an approach to modular pharmaceutical product design. As a mass customization strategy, product modularization enables serving customers with customized products cost-efficiently. The proposed modular pharmaceutical products integrate three product design requirements originating from patient needs: a scalable dose strength, a flexible target release profile, and a scalable treatment size. An approach to assess the value of these product designs is presented, by means of proposing three benefit metrics complying with respective design requirements and a cost metric assessing the cost of producing these modular pharmaceutical product designs. Results suggest that pharmaceutical product modularization can, by keeping the number of produced components low, substantially increase the external product variety and, hence, enhance the treatment outcome of patients. Furthermore, results indicate that the achieved benefit for the patient through product modularization increases beyond additional costs arising during production. However, a careful modularization must be performed to optimize the tradeoff between the increased benefit and cost. Full article

Even though recent studies designate that sustainability should be integrated in project management, this integration remains a complex issue. Hence, there is a need to develop a new approach that would assess the organizational sustainability and reveal to what extent sustainable project management practices are effective. The aim of this research is to propose a Multi-Criteria Decision Analysis-based method to assess the integration of the sustainability philosophy in large-scale organizations via the utilization of sustainable project management-related indicators. By utilising the proposed approach to compare internal organizational structures, the researchers aim to reveal the sustainability integration level within different business units, in order to allow organizations to make decisions toward sustainable practices. The indicators used in the proposed model are related to key aspects of organizations and they measure how the departments’ staff utilize sustainable project management processes in their construction projects. The case study was conducted in a market-leading design, engineering, and project management consultancy organization. Evaluating organizational sustainability can help organizations target their efforts in certain areas (enhancing sustainable outcomes). It can also facilitate data collection, analysis, and future projections. Full article

Carlo Cipolla’s stupidity quadrant and his five laws of stupidity were proposed for the first time in 1976. Exposed in a humorous mood by the author, these concepts describe the interactions among human beings in terms of a semiquantitative model based on the gains and losses of the agents engaged in a process. Here, we propose a new interpretation of Cipolla’s ideas in a biophysical framework, using the well known “predator–prey”, or “Lotka–Volterra”, model. We find that there is indeed a correspondence between Cipolla’s approach, based on economics and biophysical economics. We propose a “sixth law of stupidity”, additional to the five proposed by Cipolla, stating that “humans are the stupidest species in the whole ecosystem” because of their tendency of overexploiting natural resources. Full article

Using Indian free-ranging dogs (FRD) as a case study, we propose a novel intervention of social integration alongside previously proposed methods for dealing with FRD populations. Our study subsumes population dynamics, funding avenues, and innovative strategies to maintain FRD welfare and provide societal benefits. We develop a comprehensive system dynamics model, featuring identifiable parameters customizable for any management context and imperative for successfully planning a widescale FRD population intervention. We examine policy resistance and simulate conventional interventions alongside the proposed social integration effort to compare monetary and social rewards, as well as costs and unintended consequences. For challenging socioeconomic ecological contexts, policy resistance is best overcome by shifting priority strategically between social integration and conventional techniques. The results suggest that social integration can financially support a long-term FRD intervention, while transforming a “pest” population into a resource for animal-assisted health interventions, law enforcement, and conservation efforts. Full article

This research aims to explore which kinds of metrics are more valuable in making investment decisions for a venture capital firm using machine learning methods. We measure the fit of developed companies to a venture capital firm’s investment thesis with a balanced scorecard based on quantitative and qualitative characteristics of the companies. Collaborating with the management team of Rose Street Capital (RSC), we explore the most influential factors of their balanced scorecard using their retrospective investment decisions of successful and failed startup companies. Our study employs six standard machine learning models and their counterparts with an additional feature selection technique. Our findings suggest that “planning strategy” and “team management” are the two most determinant factors in the firm’s investment decisions, implying that qualitative factors could be more important to startup evaluation. Furthermore, we analyzed which machine learning models were most accurate in predicting the firm’s investment decisions. Our experimental results demonstrate that the best machine learning models achieve an overall accuracy of 78% in making the correct investment decisions, with an average of 87% and 69% in predicting the decision of companies the firm would and would not have invested in, respectively. Our study provides convincing evidence that qualitative criteria could be more influential in investment decisions and machine learning models can be adapted to help provide which values may be more important to consider for a venture capital firm. Full article

The biology literature presents allometric relations for the specific metabolic rate (SMR_k) of an organ k of mass mk within the body of mass m_B: SMR_k ∝ m_B^fk (body mass allometry, BMA). Wang et al. used BMA, summed-up energy from all organs and validated Kleiber’s law of the whole body: SMR_M ∝ m_B^b’, b’ = −0.25. The issues raised in biology are: (i) why f_k and b’ < 0, (ii) how do the organs adjust f_k to yield b’? The current paper presents a “system” approach involving the field of oxygen deficient combustion (ODC) of a cloud of carbon particles and oxygen deficient metabolism (ODM), and provides partial answers by treating each vital organ as a cell cloud. The methodology yields the following: (i) a dimensionless “group” number G_OD to indicate extent of ODM, (ii) SMR_k of an organ in terms of the effectiveness factor; (iii) curve fitting of the effectiveness factor to yield the allometric exponents for the organ mass-based allometric laws (OMA); (iv) validation of the results with data from 111 biological species (BS) with m_B ranging from 0.0075 to 6500 kg. The “hypoxic” condition at organ level, particularly for COVID-19 patients, and the onset of cancer and virus multiplication are interpreted in terms of ODM and glycolysis. Full article

Data-centric models of COVID-19 have been attempted, but have certain limitations. In this work, we propose an agent-based model of the epidemic in a confined space of agents representing humans. An extension to the SEIR model allows us to consider the difference between the appearance (black-box view) of the spread of disease and the real situation (glass-box view). Our model allows for simulations of lockdowns, social distancing, personal hygiene, quarantine, and hospitalization, with further considerations of different parameters, such as the extent to which hygiene and social distancing are observed in a population. Our results provide qualitative indications of the effects of various policies and parameters, for instance, that lockdowns by themselves are extremely unlikely to bring an end to an epidemic and may indeed make things worse, that social distancing is more important than personal hygiene, and that the growth of infection is significantly reduced for moderately high levels of social distancing and hygiene, even in the absence of herd immunity. Full article

The Coronavirus pandemic of 2019–20 (COVID-19) affected multiple social determinants of health (SDH) across the globe, including in New Zealand, exacerbating health inequities. Understanding these system dynamics can support decision making for the pandemic response and recovery measures. This study combined a scoping review with a causal loop diagram to further understanding of the connections between SDH, pandemic measures, and both short- and long-term outcomes in New Zealand. The causal loop diagram showed the reinforcing nature of structural SDH, such as colonization and socio-economic influences, on health inequities. While balancing actions taken by government eliminated COVID-19, the diagram showed that existing structural SDH inequities could increase health inequities in the longer term, unless the opportunity is taken for socio-economic policies to be reset. Such policy resets would be difficult to implement, as they are at odds with the current socio-economic system. The causal loop diagram highlighted that SDH significantly influenced the dynamics of the COVID-19 impact and response, pointing to a need for purposeful systemic action to disrupt the reinforcing loops which increase health inequities over time. This will require strong systems leadership, and coordination between policy makers and implementation at local level. Full article

The ability to solve modern complex systems becomes a necessity of the 21st century. The purpose of this study is the development of an instrument that measures an individual’s perception toward solving complex problems. Based on literature and definitions, an instrument with four stages named perceived complex problem-solving (PCPS) was designed through exploratory and confirmatory stages. The instrument is validated and scaled through different models, and the final model is discussed. After completing validation and scale development of the PCPS instrument, the final model of the PCPS instrument was introduced to resolve the gap in the literature. The final model of the PCPS instrument is able to find and quantify the degree of perception an individual holds in dealing with complex problems and can be utilized in different settings and environments. Further research about the relationship between Systems Thinking and CPS revealed individuals with a high level of systems thinking have a better understanding of the characteristics of complex problems and so better perception of CPS. Full article

Tourism provides many advantages for Sweden and the whole world, as well as its travelers. Since almost all types of tourism are currently in crisis as a result of the current COVID-19 pandemic, information and communication technology is expected to play a role, not only during the crisis but also in the post-COVID-19 era. Thus, with no expectations from types of tourism, Sweden needs to broaden its digital tours. As a result, this letter aims to classify the transition readiness of industry clusters for this digitalization move. An extended version of the TOPSIS technique was formulated and validated, plus a new framework for measuring digitalization readiness for this purpose. Lastly, analysis of the collected data proves that business tourism could lead the change, though adventure and rural tourism are at the farthest point from being considered ready to change. Full article

This paper discusses the coordinated use of the Soft Systems Methodology (SSM) learning cycle with additional bodies of knowledge. This approach furthers focused understanding and appreciation for taking action within social systems. Adapting the SSM learning cycle extends the richness of the real-world situation understood from an analytic soft systems perspective to encompass the appreciation of a problematical situation using additional bodies of knowledge to explain and explore. Examples illustrate using SSM to foster learning and improve teaching in a research education practice, in a national level research project and, further, in professional in-service at advanced level education. Full article

Cyberspace is a new frontier, not just for hackers, but for engineers. It is a digital ecosystem, the next generation of Internet and network applications, promising a whole new world of distributed and open systems that can interact, self-organize, evolve, and adapt. These ecosystems transcend traditional collaborative environments, such as client-server, peer-to-peer, or hybrid models (e.g., web services), to become a self-organized, evolving, interactive environment. Understanding cyberspace as a system is critical if we are to properly design systems to exist within it. Considering it to be a digital ecosystem, where systems can adapt and evolve, will enable systems engineering to become more effective in the future of networks and the Internet. While most systems engineers have only anecdotal experience with large segments of this ecosystem, in today’s world all of them must come to understand it. Engineering any system, or portion of a system, begins with an understanding of the system. This paper presents two interrelated yet distinct foundational models of the ecosystem of cyberspace: a Systemigram to narrate the cyclical nature of cyber warfare, and a modified predator–prey model, as a mathematical model. Systems engineers can utilize these models to design digital “species” that function and adapt within this ecosystem. Full article

In this paper, we explore the need to improve systems awareness to support early-phase decision-making. This research uses the Norwegian energy industry as context. This industry deals with highly complex engineering systems that shall operate remotely for 25+ years. Through an in-depth study in a systems supplier company, we find that engineers are not sufficiently aware of the systems operational context and do not focus on the context in the early phase. We identified the lack of a holistic mindset and the challenge of balancing internal strategy and customers’ needs as the prevalent barriers. To support the concept evaluation, the subsea system suppliers need to raise systems awareness in the early phase. The study identifies four aspects that are important to consider when developing and implementing approaches to improve systems awareness in the early phase. Full article