Enacting business processes in process engines requires the coverage of control flow, resource assignments, and process data. While the first two aspects are well supported in current process engines, data dependencies need to be added and maintained manually by a process engineer. Thus, this task is error-prone and time-consuming. In this report, we address the problem of modeling processes with complex data dependencies, e.g., m:n relationships, and their automatic enactment from process models. First, we extend BPMN data objects with few annotations to allow data dependency handling as well as data instance differentiation. Second, we introduce a pattern-based approach to derive SQL queries from process models utilizing the above mentioned extensions. Therewith, we allow automatic enactment of data-aware BPMN process models. We implemented our approach for the Activiti process engine to show applicability.

Businesses consistently work on new projects, products, and workflows to remain competitive and successful in the modern business environment. To remain zealous, businesses must employ the most effective methods and tools in human resources, project management, and overall business plan execution as competitors work to succeed as well. Advanced Methodologies and Technologies in Business Operations and Management provides emerging research on business tools such as employee engagement, payout policies, and financial investing to promote operational success. While highlighting the challenges facing modern organizations, readers will learn how corporate social responsibility and utilizing artificial intelligence improve a company’s culture and management. This book is an ideal resource for executives and managers, researchers, accountants, and financial investors seeking current research on business operations and management.

This book constitutes the proceedings of the 11th International Conference on Business Process Management, BPM 2013, held in Beijing, China, in August 2013. The 17 regular papers and 8 short papers included in this volume were carefully reviewed and selected from 118 submissions. The papers are organized in 7 topical sections named: process mining; conformance checking; process data; process model matching; process architectures and collaboration; as well as alternative perspectives, and industry paper.

This two volume set LNCS 8644 and LNCS 8645 constitutes the refereed proceedings of the 25th International Conference on Database and Expert Systems Applications, DEXA 2014, held in Munich, Germany, September 1-4, 2014. The 37 revised full papers presented together with 46 short papers, and 2 keynote talks, were carefully reviewed and selected from 159 submissions. The papers discuss a range of topics including: data quality; social web; XML keyword search; skyline queries; graph algorithms; information retrieval; XML; security; semantic web; classification and clustering; queries; social computing; similarity search; ranking; data mining; big data; approximations; privacy; data exchange; data integration; web semantics; repositories; partitioning; and business applications.

In the increasingly competitive corporate sector, businesses must examine their current practices to ensure business success. By examining their social, financial, and environmental risks, obligations, and opportunities, businesses can re-design their operations more effectively to ensure prosperity. Sustainable Business: Concepts, Methodologies, Tools, and Applications is a vital reference source that explores the best practices that promote business sustainability, including examining how economic, social, and environmental aspects are related to each other in the company’s management and performance. Highlighting a range of topics such as lean manufacturing, sustainable business model innovation, and ethical consumerism, this multi-volume book is ideally designed for entrepreneurs, business executives, business professionals, managers, and academics seeking current research on sustainable business practices.