Managing Process Variants in the Process Life Cycle

When designing process-aware information systems, often variants of the same process have to be specified. Each variant then constitutes an adjustment of a particular process to specific requirements building the process context. Current Business Process Management (BPM) tools do not adequately support the management of process variants. Usually, the variants have to be kept in separate process models. This leads to huge modeling and maintenance efforts. In particular, more fundamental process changes (e.g., changes of legal regulations) often require the adjustment of all process variants derived from the same process; i.e., the variants have to be adapted separately to meet the new requirements. This redundancy in modeling and adapting process variants is both time consuming and error-prone. This paper presents the Provop approach, which provides a more flexible solution for managing process variants in the process life cycle. In particular, process variants can be configured out of a basic process following an operational approach; i.e., a specific variant is derived from the basic process by applying a set of well-defined change operations to it. Provop provides full process life cycle support and allows for flexible process configuration resulting in a maintainable collection of process variants

Composition and Self-Adaptation of Service-Based Systems with Feature Models

The adoption of mechanisms for reusing software in pervasive systems has not yet become standard practice. This is because the use of pre-existing software requires the selection, composition and adaptation of prefabricated software parts, as well as the management of some complex problems such as guaranteeing high levels of efficiency and safety in critical domains. In addition to the wide variety of services, pervasive systems are composed of many networked heterogeneous devices with embedded software. In this work, we promote the safe reuse of services in service-based systems using two complementary technologies, Service-Oriented Architecture and Software Product Lines. In order to do this, we extend both the service discovery and composition processes defined in the DAMASCo framework, which currently does not deal with the service variability that constitutes pervasive systems. We use feature models to represent the variability and to self-adapt the services during the composition in a safe way taking context changes into consideration. We illustrate our proposal with a case study related to the driving domain of an Intelligent Transportation System, handling the context information of the environment.Work partially supported by the projects TIN2008-05932, TIN2008-01942, TIN2012-35669, TIN2012-34840 and CSD2007-0004 funded by Spanish Ministry of Economy and Competitiveness and FEDER; P09-TIC-05231 and P11-TIC-7659 funded by Andalusian Government; and FP7-317731 funded by EU. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Efficacy-aware Business Process Modeling

In business process design, business objective models can fulfill the role of formal requirement definitions. Matching process models against objective models would, for instance, enable sound comparison of implementation alternatives. For that purpose, objective models should be available independently of their concrete implementation in a business process. This issue is not addressed by common business process management concepts yet. Moreover, process models are currently not sufficiently expressive to determine business process efficacy in the sense of fulfilling a business objective. Therefore, this paper develops and integrates constructs required for efficacy-aware process modeling and apt to extend common modeling approaches. The concept is illustrated with a sample scenario. Overall, it serves as an enabler for progressive applications like automated process optimization

Enabling Process Variants and Versions in Distributed Object-Aware Process Management Systems

Business process variants are common in many enterprises and properly managing them is indispensable. Some process management suites already offer features to tackle the challenges of creating and updating multiple variants of a process. As opposed to the widespread activity-centric process modeling paradigm, however, there is little to no support for process variants in other process support paradigms, such as the recently proposed artifact-centric or object-aware process support paradigm. This paper presents concepts for supporting process variants in the object-aware process management paradigm. We offer insights into the distributed object-aware process management framework PHILharmonicFlows as well as the concepts it provides for implementing variants and versioning support based on log propagation and log replay. Finally, we examine the challenges that arise from the support of process variants and show how we solved these, thereby enabling future research into related fundamental aspects to further raise the maturity level of data-centric process support paradigms

Identifying Variability in Process Performance Indicators

The performance perspective of business processes is concerned with the definition of performance requirements usually specified as a set of Process Performance Indicators (PPIs). Like other business process perspectives such as control-flow or data, there are cases in which PPIs are subject to variability. However, although the modelling of business process variability (BPV) has evolved significantly, there are very few contributions addressing the variability in the performance perspective of business processes. Modelling PPI variants with tools and techniques non-suitable for variability may generate redundant models, thus making it difficult its maintenance and future adaptations, also increasing possibility of errors in its managing. In this paper we present different cases of PPI variability detected as result of the analysis of several processes where BPV is present. Based on an existent metamodel used for defining PPIs over BPs, we propose its formal extension that allows the definition of PPI variability according to the cases identified.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía P12-TIC-1867Junta de Andalucía P10-TIC-590

Supporting Data Collection in Complex Scenarios with Dynamic Data Collection Processes

Nowadays, companies have to report a large number of data sets (e.g., sustainability data) regarding their products to different legal authorities. However, in today's complex supply chains products are the outcome of the collaboration of many companies. To gather the needed data sets, companies have to employ cross-organizational and long-running data collection processes that imply great variability. To support such scenarios, we have designed a lightweight, automated approach for contextual process configuration. That approach can capture the contextual properties of the respective situations and, based on them, automatically configure a process instance accordingly, even without human involvement. Finally, we implemented our approach and started an industrial evaluation

Towards a taxonomy of process quality characteristics for assessment

Previous assessment of process quality have focused on process capability (i.e. the ability of a process to meet its stated goals). This paper proposes a taxonomy of alternative process quality characteristics based on intrinsic and extrinsic quality attributes. The ultimate goal of this taxonomy is to provide a framework to conduct process assessments using different process quality aspects. Such a framework would considerably broaden process quality perspectives beyond the primary measure of process capability. It would also allow practitioners to identify and evaluate relevant quality characteristics for processes based on specific contexts and implications. For the process assessment model developers, it offers a list of process quality characteristics that could be used to develop relevant process measurement frameworks

A Qualitative Comparison of Approaches Supporting Business Process Variability

The increasing adoption of process-aware information systems, together with the reuse of process knowledge, has led to the emergence of process model repositories with large process families, i.e., collections of related process model variants. For managing such related model collections two types of approaches exist. While behavioral approaches take supersets of variants and derive a process variant by hiding and blocking process elements, structural approaches take a base process model as input and derive a process variant by applying a set of change operations to it. However, at the current stage no framework for assessing these approaches exists and it is not yet clear which approach should be better used and under which circumstances. Therefore, to give first insights about this issue, this work compares both approaches in terms of understandability of the produced process model artifacts, which is fundamental for the management of process families and the reuse of their contained process fragments. In addition, the comparison can serve as theoretical basis for conducting experiments as well as for fostering the development of tools managing business process variability

Enhancing modeling and change support for process families through change patterns

The increasing adoption of process-aware information systems (PAISs), together with the variability of business processes (BPs), has resulted in large collections of related process model variants (i.e., process families). To effectively deal with process families, several proposals (e.g., C-EPC, Provop) exist that extend BP modeling languages with variability-specific constructs. While fostering reuse and reducing modeling efforts, respective constructs imply additional complexity and demand proper support for process designers when creating and modifying process families. Recently, generic and language independent adaptation patterns were successfully introduced for creating and evolving single BP models. However, they are not sufficient to cope with the specific needs for modeling and evolving process families. This paper suggests a complementary set of generic and language-independent change patterns specifically tailored to the needs of process families. 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A multiobjective model for passive portfolio management: an application on the S&P 100 index

This is an author's accepted manuscript of an article published in: “Journal of Business Economics and Management"; Volume 14, Issue 4, 2013; copyright Taylor & Francis; available online at: http://dx.doi.org/10.3846/16111699.2012.668859Index tracking seeks to minimize the unsystematic risk component by imitating the movements of a reference index. Partial index tracking only considers a subset of the stocks in the index, enabling a substantial cost reduction in comparison with full tracking. Nevertheless, when heterogeneous investment profiles are to be satisfied, traditional index tracking techniques may need different stocks to build the different portfolios. The aim of this paper is to propose a methodology that enables a fund s manager to satisfy different clients investment profiles but using in all cases the same subset of stocks, and considering not only one particular criterion but a compromise between several criteria. For this purpose we use a mathematical programming model that considers the tracking error variance, the excess return and the variance of the portfolio plus the curvature of the tracking frontier. The curvature is not defined for a particular portfolio, but for all the portfolios in the tracking frontier. This way funds managers can offer their clients a wide range of risk-return combinations just picking the appropriate portfolio in the frontier, all of these portfolios sharing the same shares but with different weights. An example of our proposal is applied on the S&P 100.García García, F.; Guijarro Martínez, F.; Moya Clemente, I. (2013). A multiobjective model for passive portfolio management: an application on the S&P 100 index. Journal of Business Economics and Management. 14(4):758-775. doi:10.3846/16111699.2012.668859S758775144Aktan, B., Korsakienė, R., & Smaliukienė, R. (2010). TIME‐VARYING VOLATILITY MODELLING OF BALTIC STOCK MARKETS. 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V., & Stasytyte, V. (s. f.). Decision Making Strategies in Global Exchange and Capital Markets. Advances and Innovations in Systems, Computing Sciences and Software Engineering, 17-22. doi:10.1007/978-1-4020-6264-3_4Tabata, Y., & Takeda, E. (1995). Bicriteria Optimization Problem of Designing an Index Fund. Journal of the Operational Research Society, 46(8), 1023-1032. doi:10.1057/jors.1995.139Teresienė, D. (2009). LITHUANIAN STOCK MARKET ANALYSIS USING A SET OF GARCH MODELS. Journal of Business Economics and Management, 10(4), 349-360. doi:10.3846/1611-1699.2009.10.349-36