Activity Relations: A Dataflow Approach to Workflow Design

A key step in workflow design is to determine the activity sequences, which are often driven by the dataflow constraints in a business process. Therefore, the literature has suggested that workflow design can start with dataflow analysis. However, no formalism exists for deriving activity sequences from a set of identified activities and their input and output data. In this paper, we formalize the problem of workflow design on the basis of dataflow analysis. We tackle the problem by using the concept of “activity relations” as an intermediate step for identifying the possible activity execution sequences from dataflow. We investigate how to derive activity relations from dataflow and discuss their implication in workflow design

Policy-Driven Process Mapping (PDPM): Towards Process Design Automation

Recently, many organizations are investing a great amount to revamp their business policies in order to comply with the new regulations related to Sarbanes-Oxley. For organizations with large-scale business processes, maintaining those processes to meet the changing policies is a non-trivial problem. In this paper, we present an innovative process mapping methodology named Policy-Driven Process Mapping (PDPM) that takes advantage of detailed organizational policies. In particular, we show how narrative process-related policies can be formalized and how process maps can be systematically created via a set of rules and algorithms. Our research contributes to business process management by providing a theoretical foundation for the development of advanced process mapping tools, thereby taking the first step toward automatable process design procedures

Knowledge Management and Organizational Learning in Workflow Systems

In the last few years, a new type of information system called a workflow management system is being deployed in many organizations (Georgakopoulos, et al., 1995). This new system is especially suited for actualizing organizational memory because workflow systems enable the automation of business processes across teams, functional departments, and suppliers in order to reduce product or service cycle times, to decrease costs, and to minimize duplication of effort. Workflow systems integrate the people, the organizational structure, and the information sources such as databases, file systems, emails, image repositories, computer-aided design tools, and desktop applications (Stohr and Zhao, 1997). That is, workflow systems are the ideal systems to house the business logic and bring the business logic into better view

Process Logic for Verifying the Correctness of Business Process Models

Process verification is a key step in business process management. In this paper, we propose process logic as a new logical formalism and mathematical method to enable advanced process verification. We formally define the syntax and semantics of process logic, establish a formal relationship between process logic and graphical representation of process models, and transform the problem of verifying the correctness of process models into a problem of determining the validity of logic argument forms

Hyperparameter Learning via Distributional Transfer

Bayesian optimisation is a popular technique for hyperparameter learning but typically requires initial exploration even in cases where similar prior tasks have been solved. We propose to transfer information across tasks using learnt representations of training datasets used in those tasks. This results in a joint Gaussian process model on hyperparameters and data representations. Representations make use of the framework of distribution embeddings into reproducing kernel Hilbert spaces. The developed method has a faster convergence compared to existing baselines, in some cases requiring only a few evaluations of the target objective

The Impact of Online Harassment on the Performance of Projects in Crowdfunding

In the consequence-free and anonymous online environment, online harassment has become a serious problem. In many crowdfunding platforms, there exists offensive speech on the project pages, which might force potential funders to leave the discussion and to give up investment. The effect of online harassment on project performance remains unknown. This study attempts to investigate to what extent the textual online harassment score and the project creator’s attitude towards textual online harassment might affect project performance. We constructed a Kickstarter panel dataset consisting of 388,100 projects and designed a novel framework and an algorithm BiLSTM-CNN to extract the textual online harassment score from comments, which can reach column-wise mean ROC AUC of 0.9463. This study contributes to crowdfunding and online harassment literature and provides important implications for reputation management of projects and crowdfunding platform design

Systemic Decision Making for Liquidity Risk Management in Banks

The outbreak of the recent financial crisis reveals significant problems in current bank practices in conventional liquidity risk management. To avoid catastrophic consequences, a holistic view, which captures the dynamic interactions between liquidity and other financial variables, should be taken to help banks make business decisions. However, few studies in the literature have addressed this problem. To fill the research gap, we present a Systemic decision making approach for Liquidity Risk Management (SLRM) as a more advanced alternative to Conventional Liquidity Risk Management (CLRM) by capturing dynamic factors, offering logic visibility, and considering rare but fatal events. We show that SLRM can be used to support managerial decisions in developing contingency plans for liquidity management. SLRM is validated by using real data from Washington Mutual, a US bank failed during the 2008 financial tsunami. Further, we demonstrate that SLRM can also help banks conform to regulatory changes in Basel III