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Domain-specific process modeling has been proposed in the literature as a solution to several problems in business process management. The problems arise when using only the generic Business Process Model and Notation (BPMN) standard for modeling. This language includes domain ambiguity and difficult long-term model evolution. Domain-specific modeling involves developing concept definitions, domain-specific processes and eventually industry-standard BPMN models. This entails a multi-layered modeling approach, where any of these artifacts can be modified by various stakeholders and changes done by one person may influence models used by others. There is therefore a need for tool support to keep track of changes done and their potential impacts. The paper aims to discuss these issues.

The authors use a multi-context systems-based approach to infer the impacts that changes may cause in the models; and alsothe authors incrementally map components of business process models to ontologies.

Advantages of the framework include: identifying conflicts/inconsistencies across different business modeling layers; expressing rich information on the relations between two layers; calculating the impact of changes taking place in one layer to the rest of the layers; and selecting incrementally the most appropriate semantic models on which the transformations can be based.

The authors consider this work as one of the foundational bricks that will enable further advances toward the governance of multi-layer business process modeling systems. Extensive usability tests would enable to further confirm the findings of the paper.

The approach described here should improve the maintainability, reuse and clarity of business process models and in extension improve data governance in large organizations. The approaches described here should improve the maintainability, reuse and clarity of business process models. This can improve data governance in large organizations and for large collections of processes by aiding various stakeholders to understand problems with process evolutions, changes and inconsistencies with business goals.

This paper fulfills an identified gap to enabling semantically aided domain–specific process modeling.

This paper aims to present how iterative round‐trip modelling between two different business process modelling tools can be enabled on a conceptual level. Iterative round‐trip modelling addresses model transformations between high‐level business and executable process models, and how to maintain these transformations in change time. Currently, the development of these process models is supported by different tools. To the authors' best knowledge, no coherent collaborative tool environment exists that supports iterative round‐trip modelling.

This paper is primarily based on a literature review of state‐of‐the‐art business to IT transformations regarding business process modelling. The architecture of integrated information systems (ARIS) and Cordys tools are used as an example case in this research. ARIS is a business process analysis (BPA) tool suited for analyzing and designing business processes, while the execution and monitoring of these processes is allowed by Cordys, a business process management suite (BPMS). The theory is used for transforming between ARIS event‐driven process chains from the business perspective and business process modelling notation in Cordys from the IT perspective.

A conceptual framework is proposed to couple a BPA and BPMS tool for round‐trip business process modelling. The framework utilizes concepts from the model‐driven architecture for structurally addressing interoperability and model transformations. Ensuring iterative development with two tools requires traceability of model transformations.

In many organizations, BPA and BPMS tools are used for business process modelling. These are in practice often two different worlds, while they concern around the same business processes. Maintaining multiple versions of the same process models across two tools is a considerable task, as they often are subject to design changes. Interoperability between a BPA and BPMS tool will minimize redundant activities, and reduce business to IT deployment time.

This research provides a theoretical base for coupling a BPA and BPMS tool regarding iterative round‐trip modelling. It provides an overview of the current state‐of‐the‐art literature of business process modelling transformations, and what is necessary for maintaining interoperability between tools. The findings indicate what is expected in tool support for iterative development in business process modelling from analysis and design to execution.

Governmental institutions must cooperate with other organizations across institutional boundaries to achieve high-quality service offerings. The required cooperation may lead to complex networks, including several of the thousands of public administrations in the many federal layers of a single country. This paper aims to address the key challenge of the proper management of the information exchange between networked actors, which is generally conducted by means of forms.

Following the design science research paradigm, this research develops a method that assists in the design and maintenance of forms in public administrations.

Discussions in the project’s focus groups add evidence to the researchers’ expectation that the method developed in this study improves the quality of forms while reducing the effort required for their design and maintenance.

This paper includes an evaluation of the approach based on qualitative feedback from the project’s stakeholders, although the implementation of the workflows and procedures is subject to future work that evaluates the approach in a variety of practical settings.

The method developed in this paper allows public administrations and legislative authorities to design and manage forms in a cooperative way. Software developers can assume the existence of information structures. The approach extends the BOMOS standardization framework to the operational level.

The main contribution of this paper is the development of a novel method that will change how information exchange is managed in public administrations.

The purpose of this paper is to propose a solution for automating the task of matching business process models and search for correspondences with regard to the model semantics, thus improving the efficiency of such works.

A method is proposed based on combining several semantic technologies. The research follows a design-science-oriented approach in that a method together with its supporting artifacts has been engineered. It application allows for reusing legacy models and automatedly determining semantic similarity.

The method has been applied and the first findings suggest the effectiveness of the approach. The results of applying the method show its feasibility and significance. The suggested heuristic computing of semantic correspondences between semantically heterogeneous business process models is flexible and can support domain users.

Even though a solution can be offered that is directly usable, so far the full complexity of the natural language as given in model element labels is not yet completely resolvable. Here further research could contribute to the potential optimizations and refinement of automatic matching and linguistic procedures. However, an open research question could be solved.

The method presented is aimed at adding to the methods in the field of business process management and could extend the possibilities of automating support for business analysis.

The suggested combination of semantic technologies is innovative and addresses the aspect of semantic heterogeneity in a holistic, which is novel to the field.

Automating the task of identifying process weaknesses using process models is promising, as many organizations have to manage a large amount of process models. The purpose of this paper is to introduce a pattern-based approach for automatically detecting potential process weaknesses in semantic process models, thus supporting the task of business process improvement.

Based on design research, combined with a case study, the authors explore the design, application and evaluation of a pattern-based process weakness detection approach within the setting of a real-life case study in a German bank.

Business process weakness detection can be automated to a remarkable extent using pattern matching and a semantic business process modeling language. A case study provided evidence that such an approach highly supports business process analysts.

The presented approach is limited by the fact that not every potential process weakness detected by pattern matching is really a weakness but just gives the impression to be one. Hence, after detecting a weakness, analysts still have to decide on its authenticity.

Applying weakness patterns to semantic process models via pattern matching allows organizations to automatically and efficiently identify process improvement potentials. Hence, this research helps to avoid time- and resource-consuming manual analysis of process model landscapes.

The approach is not restricted to a single modeling language. Furthermore, by applying the pattern matching approach to a semantic modeling language, the authors avoid ambiguous search results. A case study proves the usefulness of the approach.

The purpose of this paper is to integrate business process management (BPM) and accounting on a conceptual level in order to account for the economic implications of process-state changes in process design-time and process run-time.

The paper adopts a design science research paradigm. The research, grounded in an “events” approach to accounting theory, builds on the REA accounting model that has been adapted for the design of a process accounting model (PAM).

The paper presents a PAM that can be used to structure event records in process-aware information systems (PAIS) to enable process-oriented accounting. The PAM is specified as a light weight data structure that is intended for the integration of PAIS and accounting information systems.

As this paper is technical in nature, more research is needed to evaluate more thoroughly its approach in naturalistic settings.

The PAM can support traditional accounting approaches, and because of the adopted events approach, it readily supports use cases related to real-time analytics in BPM and accounting.

The PAM presents a novel approach to integrating BPM and accounting. The novelty of this approach lies in its use of event records to document flows of economic resources.

From knowledge management point of view, business process models and ontologies are two essential knowledge artifacts for organizations that consume similar information sources. In this study, the PROMPTUM method for integrated process modeling and ontology development that adheres to well-established practices is presented. The method is intended to guide practitioners who develop both ontologies and business process models in the same or similar domains.

The method is supported by a recently developed toolset, which supports the modeling of relations between the ontologies and the labels within the process model collections. This study introduces the method and its companion toolset. An explanatory study, that includes two case studies, is designed and conducted to reveal and validate the benefits of using the method. Then, a follow-up semi-structured interview identifies the perceived benefits of the method.

Application of the method revealed several benefits including the improvements observed in the consistency and completeness of the process models and ontologies. The method is bringing the best practices in two domains together and guiding the use of labels within process model collections in ontology development and ontology resources in business process modeling.

The proposed method with its tool support is a pioneer in enabling to manage the labels and terms within the labels in process model collections consistently with ontology resources. Establishing these relations enables the definition and management of process model elements as resources in domain ontologies. Once the PROMPTUM method is utilized, a related resource is managed as a single resource representing the same real-world object in both artifacts. An explanatory study has shown that improvement in consistency and completeness of process models and ontologies is possible with integrated process modeling and ontology development.

The purpose of this paper is to identify the benefits of an approach in which document management systems (DMSs) are based on a formal and explicit document model, primarily in terms of facilitating domain-specific customization.

Within this paper, a generic document model is proposed. The model consists of two layers. A general purpose layer, which represents common features of the documents, and a domain-specific layer, modeling properties particular to application domain. The general purpose layer is based on ISO 82045, providing high degree of interoperability with other systems developed with respect to this set of standard.

Splitting document model into the layers enables DMSs to be tailored for each particular domain of application, depending on the general purpose layer. The existence of domain-specific layer allows documents to be interpreted differently in different domains of application.

In order to enable customization of DMS for a particular domain, the implementation of domain-specific document layer is required. Also, the proposed model does not explicitly deal with document dynamics.

The proposed document ontology is general enough to provide the representation of documents not depending on a specific scope of application, yet flexible enough to enable extensions through which domain-specific document features can be expressed. The separation of document model enables development of core DMS offering services relying explicitly on the general purpose layer on one hand, as well as domain-specific customization of DMS on the other.

Since the publication of Van Raaij and Verhallen’s seminal work in European Journal of Marketing in 1994, identifying the domain-specific market segmentation approach as one of the most feasible for segmenting markets, there has been surprisingly limited development in this field, with the food domain as the only exception. This study aims to develop a methodological approach using latent class mixture modelling as contribution in the domain-specific market segmentation field.

This study captures the AIO lifestyle perspective using a domain-specific 80-item algorithm which has the wine (product) domain as its focus. A sample size of 811 consumers is used from data collected by means of the CATI approach.

The authors use four criteria for model selection: comparison of the Bayesian information criterion (BIC) statistic, comparison of classification error, verification of the interpretation of the derived segments and, finally, use of the conditional bootstrap procedure to test whether the selected model provides a significant improvement over the previous model. The five-segment model option yields a minimum BIC, the classification error measure is minimal and is easier to interpret than the other models. Segment descriptions for the five identified lifestyle-based segments are developed.

Segmentation by traditional k-means clustering has proven to be less useful than the more innovative alternative of mixture regression modelling; therefore, the authors identify segments in the market on the basis of individuals’ domain-specific lifestyle characteristics using a latent class mixture modelling approach.

Following the attainment of a clear and robust market segmentation structure, the simultaneous analysis of the lifestyles, demographics and behaviours of consumers as nexus of the domain-specific segmentation approach, provides rich and valid information accurately informing the market segment descriptions.

The authors make a substantive contribution by developing a methodological approach using latent class mixture modelling; the first of its kind in the area of domain-specific segmentation. Next, they use the discriminant and/or predictive validity of the 80-scale items to predict cluster membership using the WRL algorithm. Finally, the authors describe the identified market segments in detail and outline the practical implications.

Internet shopping is becoming more prevalent and popular in Turkey, one of the fastest growing e-commerce markets in Eastern Europe. The growth of internet usage has focused academic attention on the factors that drive the adoption of internet shopping. The purpose of this study is to investigate how opinion leadership and open processing innovativeness influence internet shopping behavior through the mediating variable of domain-specific innovativeness.

The data for this study were collected via face-to-face contact with consumers in Eskisehir. A total of 275 usable responses were obtained.

The results reveal that opinion leadership induces positive internet shopping behavior through domain-specific innovativeness, whereas open processing innovativeness has no significant impact.

The study makes an important contribution by offering theoretical and managerial implications for internet marketers.