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In the business process lifecycle, models can be approached from two perspectives: on the one hand, models are used to create systems in the design phase, and on the other hand, systems in use produce (event) logs that are used to discover the models representing the structure of the systems. These discovered models can be the starting point of a new cycle of analysis, redesign, implementation, etc. Therefore, proper logging of implemented processes in line with system design is a critical element for process discovery. Recently, the consideration of the integration of data and process aspects has seen a surge in interest in both the model-for-design domain as in the automated-model-discovery domain. However, it seems that these domains use different conceptualizations of data/object-aware systems. A definition of how the captured event logs are related to the structure of the global system they are extracted from or are trying to discover is still missing. Especially the concept of an event needs to be aligned, as this is the main concept that the domains have in common. This paper investigates the concepts and terminology used in the different phases of the business process lifecycle: the design phase, the implementation phase (including the implementation of logging) and the discovery phase. The paper contains an extensive running example that is used to illustrate five misalignment issues. The main contribution of this paper is a meta-model that presents a unified terminology for modelling both domains and is demonstrated using the running example. The paper also shows how the concepts of iDOCEM relate to the concepts of a conceptual modelling approach and several event logging formats. iDOCEM is validated with the implementation of a log generator for the running case, demonstrating the feasibility of generating DOCEL-compliant logs from an application.

PurposeIntegration of city systems is needed to provide flexibility, agility and access to real-time information for the creation and delivery of efficient services in a smart and sustainable city. Consequently, City Process Modelling (CPMo) becomes an essential element of connecting various city sectors. However, to date, there has been limited research on the requirements of an ideal CPMo approach and the usefulness of available Business Process Modelling (BPMo) approaches. This research develops a framework for CPMo to guide smart city developers when modelling city processes.Design/methodology/approachData from literature analysis was gathered to derive capabilities of existing BPMo techniques. Then, semi-structured interviews were conducted to thematically and qualitatively explore the requirements, challenges and success factors of CPMo.FindingsThe interview findings offered 17 requirements to be addressed by a CPMo approach, along with several challenges and success factors to be considered when implementing CPMo approaches. Then, the paper presents the results of mapping these requirements against 12 existing BPMo capabilities, identified from the literature, concluding that a significant number of requirements (which are mainly related to inputs and visualisation) have been left unfulfilled by existing BPMo approaches. Hence, developing an innovative CPMo approach is necessary to address the components of unfulfilled requirements.Originality/valueThe innovative framework presented in this paper justifies the CPMo requirements, which are unexplored in existing SCD frameworks. Moreover, it will act as a guide for smart city developers, to model cross-sectoral city processes, helping them progress their SCD road map and make their cities smart.

The ideology behind process modelling is to visualise lengthy event logs into simple representations interpretable to the end user. Classifying process models as simple or complex is based on criteria that evaluate attributes of models and quantify them on a scale. These metrics measure various characteristics of process models and describe their qualities. Over the years, vast amounts of metrics have been proposed in the community, making it difficult to find and select the appropriate ones for implementation. This paper presents a state-of-the-art meta-review that lists and summarises all the evaluation metrics proposed to date. We have studied the behaviour of the four most widely used metrics in process mining with an experiment. Further, we have used seven healthcare domain datasets of varying natures to analyse the behaviour of these metrics under different threshold conditions. Our work aims to propose and demonstrate the capabilities to use our selected metrics as a standard of measurement for the process mining domain.

Although the importance of edaphic factors and habitat structure for plant growth and survival is known, both are often neglected in favor of climatic drivers when investigating the spatial patterns of plant species and diversity. Yet, especially in mountain ecosystems with complex topography, missing edaphic and habitat components may be detrimental for a sound understanding of biodiversity distribution. Here, we compare the relative importance of climate, soil and land cover variables when predicting the distributions of 2,616 vascular plant species in the European Alps, representing approximately two-thirds of all European flora. Using presence-only data, we built point-process models (PPMs) to relate species observations to different combinations of covariates. We evaluated the PPMs through block cross-validations and assessed the independent contributions of climate, soil, and land cover covariates to predict plant species distributions using an innovative predictive partitioning approach. We found climate to be the most influential driver of spatial patterns in plant species with a relative influence of ~58.5% across all species, with decreasing importance from low to high elevations. Soil (~20.1%) and land cover (~21.4%), overall, were less influential than climate, but increased in importance along the elevation gradient. Furthermore, land cover showed strong local effects in lowlands, while the contribution of soil stabilized at mid-elevations. The decreasing influence of climate with elevation is explained by increasing endemism, and the fact that climate becomes more homogeneous as habitat diversity declines at higher altitudes. In contrast, soil predictors were found to follow the opposite trend. Additionally, at low elevations, human-mediated land cover effects appear to reduce the importance of climate predictors. We conclude that soil and land cover are, like climate, principal drivers of plant species distribution in the European Alps. While disentangling their effects remains a challenge, future studies can benefit markedly by including soil and land cover effects when predicting species distributions.

PurposeThe childbirth process is a complex and vital event that requires careful analysis and improvement. This experience can shape a woman's perspective on motherhood and even affect her mental health. Healthcare providers must prioritize improving the birth experience for women. In this interdisciplinary research, a combination of business process modeling (BPM) and medicine have been used with the aim of realizing an improved delivery experience and increased maternal satisfaction.Design/methodology/approachThe data collection of this study was done by observing 518 childbirth processes and interviewing the chief of labor, chief residents, and midwives in the obstetrics and gynecology department of a hospital in Tehran from October 2022 to February 2023.FindingsThe research has been done in four main stages. The first phase is to model the primary process and sub-processes of normal vaginal delivery (NVD). The second phase is validation using expert confirmation and process mining (PM). The third phase is the analysis of the causes of maternal dissatisfaction in labor. The fourth phase of the heuristics redesigning and improving the process, in which for the first time three new categories have been presented including hospital-based, patient-based, and medical technique-based results show BPM intervention effect can be far-reaching in improving patient care and optimizing operational efficiency.Originality/valueThis study is one of only a few to adopt a process-oriented perspective to show how BPM can be used in clinical processes and has specifically examined an essential clinical process, i.e. childbirth.Highlights Developing business process management (BMP) applications in a medical special process related to childbirth as interdisciplinary research.A combination of qualitative and quantitative techniques contains engineering software and management approaches for a Case study, Implementation of BPM lifecycle in the women's hospital in Iran, Tehran, for a clinical process, which is called, normal vaginal delivery (NVD) process for fetal expulsion normally.Modeling NVD clinical process and sub-process for the first time by BPMN2.0 notations in visual paradigm (VP) software and Validation of the made model with process mining (PM), by Disco process mining software. This was done through event log collection from HIS at the hospital.Improving the childbirth process by redesigning heuristics and Introducing two new categories special for clinical process improvement for the first time.Clinical process improvement heuristics obtained in this research are not consistent with the previous seven categories presented in previous studies such as Marlon Dumas' book. Therefore, we have introduced two new heuristics to redesign clinical processes compatible with medical centers, including hospital-based, patient-based, and medical technique-based.Providing a framework for clinical process modeling and improvement containing steps and tools.

PurposeThe primary concern of quality improvement in processes is not the input–output conversion but the information that enables and controls process. This paper presents process fragments for dimensions of information quality (IQ).Design/methodology/approachResearch is based on the design science paradigm to create four fragments of reusable processes, that contemplate the following dimensions of IQ: accessibility, completeness, accuracy and consistency.FindingsThere is a theoretical discussion of the concept of IQ in process models, in which the fragments presented provide designers with a reduction in modeling time through reuse. Therefore, the designer has the flexibility to improve the IQ according to the context of each process.Practical implicationsThe discussion is relevant for both researchers and business designers because it shows that IQ is essential to guarantee the efficient execution of processes.Social implicationsProcesses modeling can be a challenge for inexperienced designers as they always try to solve a problem from the start, without worrying about the IQ dimensions in process models. Fragments here presented can be (re)used to guide these designers in processes modeling with more IQ.Originality/valueProcess modeling approaches provide expressive techniques but do not guarantee IQ in the models. However, these approaches present process fragments that can be easily used to contemplate IQ in process models. In this context, process fragments reuse stands out as an innovative solution to mitigate the shortcomings of process models related to IQ.

Purpose – The purpose of this paper is to introduce a novel role model-based approach for modelling collaborative business processes. The authors present an architecture for subject-oriented business process modelling relying on the role concept and the demonstration of collaboration patterns expressed by role models. Design/methodology/approach – The authors present a literature review and they identify requirements for collaborative business process modelling. Moreover, roles are introduced as the enabling concept for collaborative business process modelling. The concept of roles offers a dynamic type aspect as a linking element to business process modelling as well as the ability to model collaboration aspects as they are central elements of social software. Findings – The authors propose a role-based approach to use the potential of social media for business process modelling of collaborative processes. The approach helps to overcome traditional business process modelling drawbacks like “model-reality divide” and “lost innovations.” Research limitations/implications – The proposed approach and derived prototype architecture have not been tested yet and therefore still need to be empirically proved and verified. However, the conceptual work will help other researchers as well as practitioners to further elaborate the model and to develop prototypes. Practical implications – The paper includes implications for the improvement of business process modelling in team-based and knowledge-centric organizations, which strive for an optimization of collaboration management. Originality/value – This work is the first to introduce a role model-based approach to overcome traditional drawbacks of business process modelling.

Endodormancy and the related chilling requirement synchronize the seasonal development of trees from the boreal and temperate regions under the climatic conditions prevailing at their native growing sites. The phenomenon of endodormancy has been known at the whole-plant level for 100 years, and in the last couple of decades, insights into the physiological and molecular basis of endodormancy and its release have also been obtained. Intriguingly, recent studies have shown experimentally that subtropical trees also show endodormancy and a chilling requirement. Motivated by the climatic differences between the subtropical and more northern zones, here we address the similarities and differences in endodormancy between trees growing in the subtropical zone and those growing in more northern zones.

After observing various inexperienced modelers constructing a business process model based on the same textual case description, it was noted that great differences existed in the quality of the produced models. The impression arose that certain quality issues originated from cognitive failures during the modeling process. Therefore, we developed an explanatory theory that describes the cognitive mechanisms that affect effectiveness and efficiency of process model construction: the Structured Process Modeling Theory (SPMT). This theory states that modeling accuracy and speed are higher when the modeler adopts an (i) individually fitting (ii) structured (iii) serialized process modeling approach. The SPMT is evaluated against six theory quality criteria.

We aimed to evaluate the importance of modulations of within-tree carbon (C) allocation by water and low-temperature stress for the prediction of annual forest growth with a process-based model. A new C allocation scheme was implemented in the CASTANEA model that accounts for lagged and direct environmental controls of C allocation. Different approaches (static vs dynamic) to modelling C allocation were then compared in a model–data fusion procedure, using satellite-derived leaf production estimates and biometric measurements at c. 104 sites. The modelling of the environmental control of C allocation significantly improved the ability of CASTANEA to predict the spatial and year-to-year variability of aboveground forest growth along regional gradients. A significant effect of the previous year's water stress on the C allocation to leaves and wood was reported. Our results also are consistent with a prominent role of the environmental modulation of sink demand in the wood growth of the studied species.Data available at large scales can inform forest models about the processes driving annual and seasonal C allocation. Our results call for a greater consideration of C allocation drivers, especially sink–demand fluctuations, for the simulations of current and future forest productivity with process-based models.