A methodology to rank enterprise application integration platforms from a performance perspective: an analytic hierarchy process-based approach

ABSTRACT

Companies’ software ecosystems comprise applications that support their business processes. Frequently, these applications have been developed with different technologies and with no concern about integration. Integration platforms are tools that facilitate the development and execution of integration solutions. In this article, we propose a methodology to support software engineers in the decision-making process for an integration platform when performance is a central requirement. The proposed methodology adds objective criteria for performance assessment purposes and has been used to rank the five most popular integration platforms in order to prove its feasibility.     

Politische Ökonomie der Rechnungslegung – Bisherige Forschungsergebnisse und künftige Forschungsperspektiven unter besonderer Berücksichtigung des Lobbyingkonzepts

Particularly in the field of German research tradition concerning financial accounting thoughts about interpretation and development of standards are focal points. Along with the appearance of the information economics it became apparent that financial accounting is not only a technical vehicle but a social institution. By making accounting information publicly available it may have an effect on the distribution of economic income. Insofar the presumption is feasible that those players influence standard-setting whose welfare is directly affected by it. The above mentioned view that is rarely noted in the German-speaking countries is followed by the research approach so called ‘‘Political Economy of Accounting’’. Aim of this research approach is to explain the complex standard-setting process by considering the different parties within a society. The article at hand contributes to sum up state-of-the-art advancements in the field of scientific discourse concerned and provides an outlook on perspectives in this research area.     

Business process monitoring via decentralized complex event processing

ABSTRACT

Complex event processing (CEP) techniques have been used for business process (BP) monitoring of large organizations with high number of complex BPs and high rates of BP instance generations resulting in high number of monitoring rules and high rates of events. To circumvent the scale limitation of centralized CEP techniques, we present a decentralized CEP mechanism called dBPM that uses both task parallelism by decomposition and distribution of monitoring rules, and data parallelism by partitioning and dispatching of events. We show that dBPM is more scalable than a general distributed CEP mechanism, called VISIRI, by dynamically adapting to workload changes.     

A methodology proposal for collaborative business process elaboration using a model-driven approach

Business process management (BPM) principles are commonly used to improve processes within an organisation. But they can equally be applied to supporting the design of an Information System (IS). In a collaborative situation involving several partners, this type of BPM approach may be useful to support the design of a Mediation Information System (MIS), which would ensure interoperability between the partners’ ISs (which are assumed to be service oriented). To achieve this objective, the first main task is to build a collaborative business process cartography. The aim of this article is to present a method for bringing together collaborative information and elaborating collaborative business processes from the information gathered (by using a collaborative situation framework, an organisational model, an informational model, a functional model and a metamodel and by using model transformation rules).     

A service governance mechanism based on process mining for cloud-based applications

ABSTRACT

With the widely use of cloud computing in enterprise information systems, service governance becomes critical for an enterprise to adapt to a changing business environment. In order to provide a dynamic strategy for continuous service governance, in this paper a comprehensive service analysis solution is proposed to address both design time and run-time requirements for cloud applications. First, a process-centric Semantic Scene Model is composed to combines static business requirements with dynamic execution information. Then service analysis is conducted referring both to the business process mining results from event logs and the Semantic Scene Model given by business model designers. Service governance strategies are generated from the service analysis results and are performed to qualitatively classify the Quality of Service (QoS) of the services. Finally the approach is verified with a transportation logistics service application in a cloud platform. The result shows that our method can get continuous service governance through combining business processes with run-time service analysis.     

Hicks-Moorsteen versus Malmquist: a connection by means of a radial productivity index

A primal index of productivity change is introduced which decomposes exactly into three components: technical change, technical efficiency change and average scale economies (radial scale change). The productivity index is defined using variations of the distance function along pre-assigned input–output rays and, for this reason, it is deemed a radial productivity index (RPI). It is proven that: first, the RPI index collapses to the Malmquist productivity index when the technology is constant returns to scale (CRS); second the RPI index equals the Hicks-Moorsteen productivity index under homotheticity of technology (and non-CRS). The key to these results is a new definition and measure of the contribution of scale economies to productivity change.     

Multicriteria framework for selecting a process modelling language

The choice of process modelling language can affect business process management (BPM) since each modelling language shows different features of a given process and may limit the ways in which a process can be described and analysed. However, choosing the appropriate modelling language for process modelling has become a difficult task because of the availability of a large number modelling languages and also due to the lack of guidelines on evaluating, and comparing languages so as to assist in selecting the most appropriate one. This paper proposes a framework for selecting a modelling language in accordance with the purposes of modelling. This framework is based on the semiotic quality framework (SEQUAL) for evaluating process modelling languages and a multicriteria decision aid (MCDA) approach in order to select the most appropriate language for BPM. This study does not attempt to set out new forms of assessment and evaluation criteria, but does attempt to demonstrate how two existing approaches can be combined so as to solve the problem of selection of modelling language. The framework is described in this paper and then demonstrated by means of an example. Finally, the advantages and disadvantages of using SEQUAL and MCDA in an integrated manner are discussed.     

Survey of business process management: challenges and solutions

The current literature shows that creating a good framework on business process model (PM) is not an easy task. A successful business PM should have the ability to ensure accurate alignment between business processes (BPs) and information technology (IT) designs, provide security protection, manage the rapidly changing business environment and BPs, manage customer power, be flexible for reengineering and ensure that IT goals can be easily derived from business goals and hence an information system (IS) can be easily implemented. This article presents an overview of research in the business PM domain. We have presented a review of the challenges facing business PMs, such as misalignment between business and IT, difficulty of deriving IT goals from business goals, creating secured business PM, reengineering BPs, managing the rapidly changing BP and business environment and managing customer power. Also, it presents the limitations of existing business PM frameworks. Finally, we outline several guidelines to create good business PM and the possible further research directions in the business PM domain.     

Customer Lifetime Value: Entwicklungspfade, Einsatzpotenziale und Herausforderungen

Due to an ongoing discussion in the scientific community and in practice about a customer value based corporate management, the valuation and management of customer relationships has gained more and more importance. Thereby a multiplicity of scientific publications emerged, which increasingly dealt with the subject of customer value. In the scientific community the Customer Lifetime Value (CLV) is a widespread and forward-looking valuation concept. For calculating the CLV numerous models have been developed. In addition, the CLV allows companies to answer various corporate issues. In this context, this paper provides an overview about the CLV-research. Extending the existing literature development paths, potential uses, and future challenges of the CLV are illustrated.     

Measuring user similarity using check-ins from LBSN: a mobile recommendation approach for e-commerce and security services

ABSTRACT

Social friendship and geographical position information often reflects individuals’ personal preferences and other types of knowledge that can be used to extract their similarity for recommendation systems. This paper finds that users are more likely to move around some specific centres or check in at some hotspots; a few individuals check in frequently, whereas most locations are rarely visited. Based on these findings, we propose a multi-centre clustering algorithm to capture users’ mobile patterns and develop a user similarity measurement method. Complexity analysis shows the method’s efficiency in handling large datasets and experimental results demonstrate its good applicability.     

Improving the process of process modelling by the use of domain process patterns

The use of business process models has become prevalent in a wide area of enterprise applications. But while their popularity is expanding, concerns are growing with respect to their proper creation and maintenance. An obvious way to boost the efficiency of creating high-quality business process models would be to reuse relevant parts of existing models. At this point, however, limited support exists to guide process modellers towards the usage of appropriate model content. In this paper, a set of content-oriented patterns is presented, which is extracted from a large set of process models from the order management and manufacturing production domains. The patterns are derived using a newly proposed set of algorithms, which are being discussed in this paper. The authors demonstrate how such Domain Process Patterns, in combination with information on their historic usage, can support process modellers in generating new models. To support the wider dissemination and development of Domain Process Patterns within and beyond the studied domains, an accompanying website has been set up.     

Enabling flexible task compositions,orders and granularities for knowledge-intensive business processes

During the last decades, many approaches and tools were developed that enable a flexible enactment of repetitive business processes. By contrast, knowledge-intensive processes (KIPs) have not been effectively supported yet. This paper proposes a data-centric and goal-driven approach that enables flexible KIP enactment with dynamically evolving task structure and varying task granularity. The approach utilises artificial intelligence planning techniques in order to enable recommendations regarding the next tasks to be enacted. Furthermore, recommendations may be dynamically adapted when mismatches between the digital process and the real-world KIP emerge. Overall, the approach provides flexibility and guidance during KIP enactment.     

Process innovation laboratory: a new approach to business process innovation based on enterprise information systems

Most organizations today are required not only to operate effective business processes but also to allow for changing business conditions at an increasing rate. Today nearly every business relies on their enterprise information systems (EIS) for process integration and future generations of EIS will increasingly be driven by business process models. Consequently business process modelling and improvement is becoming a serious challenge. The aim of this paper is to establish a conceptual framework for business process innovation (BPI) in the supply chain based on advanced EIS. The challenge is thus to create a new methodology for developing and exploring process models and applications. The paper outlines the process innovation laboratory (Π-Lab) as a new approach to BPI. The Π-Lab is a comprehensive framework and a collaborative workspace for experimenting with process models. The Π-Lab facilitates innovation by using an integrated action learning approach to process modelling in a controlled environment. The study is based on design science and the paper also discusses the implications to EIS research and practice.     

Investor relations: a comprehensive overview

This paper reviews the existing literature on investor relations. The purpose of investor relations is consistently to provide market participants with decision-relevant information as a result of either mandatory or voluntary information-disclosure policies. A causation chain between investor relations and stock prices is established through the liquidity hypothesis with respect to the depth of analyst coverage. Though a positive association is documented, it is not perfectly linear. After presenting the taxonomy of corporate disclosures, we elaborate on how well the full-disclosure and the discretionary disclosure models fit into reality. In addition, the extant theoretical and empirical literature reports that investor relations policies vary over time, across firms and jurisdictions.     

How strategic considerations influence decision making on e-HRM applications

Although numerous studies indicate that the added value of human resource management is strongest when HRM decisions are linked to the organizational strategy, practical knowledge about how strategic considerations influence decision-making processes relating to e-HRM is limited. Therefore, the purpose of this study is (1) to examine in three case studies how strategic considerations influence the decision-making process around the introduction of e-HRM applications, (2) to present propositions for further research, and (3) to offer recommendations on how to better include strategic considerations in the decision-making process. Three in-depth case studies of companies' e-HRM implementation were performed using a model on e-HRM strategy formulation (Marler, 2009). The case studies reveal that when specific business drivers are absent from the decision-making process, the main role of e-HRM becomes to provide an infrastructure with a focus on preventing dissatisfaction. In order for e-HRM to be used in a more strategic way, business and HRM should be aligned.Based on the findings, we offer research propositions for academics studying this emerging field of the interconnections between strategy, human resource management and IT systems. In addition, we offer recommendations for HR practitioners on how to optimize the match between business and HRM.     

A method towards Web service combination for cross-organisational business process using QoS and cluster

How to quickly combine various Web services to support cross-organisational business processes is the key technical problem in service computing. Because of the changeability of QoS of Web services, the traditional methods are unadaptable to the new environments. In this paper, a new service composition method, called Improved Self-organising neural network Method for Web Service Composition, is proposed to achieve QoS-aware Web service combination, according to using the clustering technology. First, fuzzy mathematics is used to express each QoS attribute and the improved self-organising neural network is used to cluster services to reduce the number of candidate services. Secondly, all the centre of each cluster is selected and formed a composite service by using an exhaustive algorithm. Thirdly, the service cluster that is represented by the concrete services. Finally, the optimal service combination can be selected using integer programming or genetic algorithm. The experimental result shows the efficiency of Web service composition and demonstrates the applicability.     

Business process optimization using the ant colony system

Process optimization is a key consideration in workflow management. Implementing an efficient workflow may improve customer satisfaction and enhance productivity of an enterprise. Many optimization tools have been introduced to solve scheduling problems in the manufacturing environment, but most of them have not drawn much attention of decision makers for workflow analyses. This is mainly due to the difference between business operations and manufacturing processes that the process optimization tools cannot be directly applied for analyzing business workflows. Scholars have associated the attributes of workflow in the business environment with those of scheduling concepts to facilitate the use of job shop scheduling techniques for solving workflow problems. However, there is still not much discussion on the use of metaheuristic algorithms for workflow analyses. This paper proposes the use of a systematic approach that entails the ant colony optimization algorithm for identifying the best task sequence in support of processing time analyses. The applicability of the proposed approach is demonstrated with a case example. The result shows that a better operation sequence in terms of shorter processing duration can be obtained by the proposed approach.     

A conceptual framework and classification of capability areas for business process maturity

The article elaborates on business process maturity, which indicates how well an organisation can perform based on its business processes, i.e. on its way of working. This topic is of paramount importance for managers who try to excel in today's competitive world. Hence, business process maturity is an emerging research field. However, no consensus exists on the capability areas (or skills) needed to excel. Moreover, their theoretical foundation and synergies with other fields are frequently neglected. To overcome this gap, our study presents a conceptual framework with six main capability areas and 17 sub areas. It draws on theories regarding the traditional business process lifecycle, which are supplemented by recognised organisation management theories. The comprehensiveness of this framework is validated by mapping 69 business process maturity models (BPMMs) to the identified capability areas, based on content analysis. Nonetheless, as a consensus neither exists among the collected BPMMs, a classification of different maturity types is proposed, based on cluster analysis and discriminant analysis. Consequently, the findings contribute to the grounding of business process literature. Possible future avenues are evaluating existing BPMMs, directing new BPMMs or investigating which combinations of capability areas (i.e. maturity types) contribute more to performance than others.     

Business process architectures: overview,comparison and framework

With the uptake of business process modelling in practice, the demand grows for guidelines that lead to consistent and integrated collections of process models. The notion of a business process architecture has been explicitly proposed to address this. This paper provides an overview of the prevailing approaches to design a business process architecture. Furthermore, it includes evaluations of the usability and use of the identified approaches. Finally, it presents a framework for business process architecture design that can be used to develop a concrete architecture. The use and usability were evaluated in two ways. First, a survey was conducted among 39 practitioners, in which the opinion of the practitioners on the use and usefulness of the approaches was evaluated. Second, four case studies were conducted, in which process architectures from practice were analysed to determine the approaches or elements of approaches that were used in their design. Both evaluations showed that practitioners have a preference for using approaches that are based on reference models and approaches that are based on the identification of business functions or business objects. At the same time, the evaluations showed that practitioners use these approaches in combination, rather than selecting a single approach.     

Aligning observed and modelled behaviour based on workflow decomposition

When business processes are mostly supported by information systems, the availability of event logs generated from these systems, as well as the requirement of appropriate process models are increasing. Business processes can be discovered, monitored and enhanced by extracting process-related information. However, some events cannot be correctly identified because of the explosion of the amount of event logs. Therefore, a new process mining technique is proposed based on a workflow decomposition method in this paper. Petri nets (PNs) are used to describe business processes, and then conformance checking of event logs and process models is investigated. A decomposition approach is proposed to divide large process models and event logs into several separate parts that can be analysed independently; while an alignment approach based on a state equation method in PN theory enhances the performance of conformance checking. Both approaches are implemented in programmable read-only memory (ProM). The correctness and effectiveness of the proposed methods are illustrated through experiments.