A Logic Based Modeling Approach to Managing Workflow Policy Changes

Workflow management systems are becoming increasingly important in the automation of business processes. In order to ensure proper workflow execution, workflow policies must be specified with respect to users, roles, and tasks. In today’s dynamic business environment, successful organizations must be able to respond to new customer demands and market opportunities with flexibility and speed. However, without systematic management of workflow policies, changes in organizational structure and process models can lead to inconsistent workflow specifications. Thus far, research in the change management of workflow policies has been scant. In this paper, we propose a logic-based approach to address this problem. Our contribution is three-fold: 1) a modeling language based on predicate logic is proposed, which is succinct and expressive enough to represent process model, organization model, and workflow polices; 2) workflow policy consistency in a dynamic changing environment is formally defined and analyzed based on the proposed language. 3) two algorithms are developed to check and enforce the policy consistency. To the best of our knowledge, this is the first work focuses on the formal analysis of workflow policy change management

Discovering Determinants of Project Participation in an Open Source Social Network

Successful open source software projects often require a steady supply of self motivated software developers. However, little work has been done from a relational/network perspective to study the factors that drive the developers to participate in OSS projects. In this paper, we investigate the participation dynamics in a social network, particularly in an online open source community called Ohloh. Through a REST-based API, we collected information about 11,530 open source software projects involving 94,330 developers. Using social network analysis and statistical analysis methods, we examine a set of social and technical factors in the Ohloh dataset, which we define as the determinants that significantly influence the developers’ participation choices. We found that the determinants include (1)homophily in programming language, (2)project mutual acquaintance, and (3)project age. In addition, our research findings provide the possibility of predicting developers’ participation choices based on the discovered determinants, and therefore can have important implications for OSS project management and in designing social network enabled recommendation systems

A Comparison of Evaluation Networks and Collaboration Networks in Open Source Software Communities

The open source software (OSS) development communities have experienced rapid growth in recent years. Previous social network studies on OSS communities focused on collaboration relationships. However, information about how OSS community members perceive each other is largely ignored. In this study, we report an empirical investigation of the evaluation network in an online OSS community which includes over 11,800 OSS projects and more than 94,330 developers. A collaboration network is modeled from this data set and analyzed for comparison purposes. We find the evaluation network is significantly different from collaboration network in average degree, average path length and fragmentation rate. Furthermore, we argue that the evaluation networks can be used to locate expertise - skillful developers in OSS communities and capture important social relationships among the developers missed in the collaboration network. These characteristics of the evaluation network may benefit the research of OSS development communities and expert recommendation systems

A FRAMEWORK TO SUPPORT SERVICE-ORIENTED ARCHITECTURE INVESTMENT DECISION

Service-oriented architecture (SOA) is a system paradigm that structures business functions as loosely coupled services to enable business agility. SOA requires significant up-front investments, and in return, promises a vast array of benefits. Unfortunately, in contrast to the costs of the investment, monetary benefits associated with SOA are more difficult to measure. For one reason, benefits such as increased agility or improved flexibility are elusive in nature, making it harder to define metrics for their calculation. For another, SOA value is realized in long term under uncertainty, and traditional capital budgeting methods often fail to capture uncertainty when valuing investments. In this paper, we provide a decision framework to analyze the monetary impact of SOA investment in an organization. Combining traditional NPV analysis with option pricing models, our framework accounts for operational and strategic costs and benefits of SOA and proposes an extended investment value to support managerial investment decision

Online Leadership for Open Source Project Success: Evidence from the GitHub Blockchain Projects

Blockchain technology has become increasingly popular in recent years. However, only 8% of blockchain open source projects are maintained actively on GitHub. Drawing on the online leadership literature, this study seeks to understand the correlation between leader characteristics and success of blockchain open source projects from the behavioral (knowledge contribution), structural (social capital) and cognitive (openness orientation) dimensions. Considering the unique decentralization nature of blockchain, this study further investigates the contingency effect of blockchain archetypes with empirical evidence from GitHub. Our findings provide novel insights for understanding the determinants of blockchain open source project success and leadership behaviors in the online community

Medical Information Filtering Using Rule-based and Content-based Approaches

Healthcare professionals need to keep themselves updated with the latest medical developments by finding and reading relevant articles in order to provide the best possible care to their patients. The most popular technique for retrieving relevant articles from a digital library is keyword matching, which is known to retrieve a large amount of irrelevant articles without taking into account the knowledge requirements the user. Currently, the research community is making progress, but is still far from resolving this problem. In this paper, we propose a new method for generating rule-based stereotypical profiles to capture the knowledge requirements based on user roles, and an information filtering technique that combine content-based and rule-based filtering to deliver relevant articles to a user

A Workflow-centric Study of Organizational Knowledge Distribution

Organizations require mechanisms to efficiently distribute knowledge such as news releases, seminar announcements, and memos. While the machinery for information storage, manipulation. and retrieval exists, research dealing directly with knowledge distribution in an organizational context is scarce. In this paper, we address this need by first examining the pros and cons of the conventional "mailing lists" approach and then proposing new workflow mechanisms that improve the efficiency and effectiveness of knowledge distribution. The main contributions of this study include: (I) a workflow perspective on organizational knowledge distribution. (2) workflow analysis of two new knowledge distribution methods based on dynamic mailing lists and profile matching, respectively, and (3) a new way of matching knowledge supply and demand that extends existing information filtering algorithms.Information Systems Working Papers Serie

A Cooporative Analysis Framework for Investment Decisions in Community Source Partnerships

Community source development has emerged as a new way of developing enterprise applications, leading to a unique type of open source practice involving partnership and investments from multiple organizations. A critical research question in community source development is concerned with the rationale and the economic incentives behind investments from partnering organizations. In this paper, we examine a real world case, the Kuali community source project, and propose a cooperative decision framework to analyze investment decisions made by various types of organizations involved in community source. We analyze joint investment decisions and adopt the Black-Scholes model to capture individual organizations’ decision-making in risky environments. Our analytical results are able to explain an array of observed investment behavior from community-source partners and reveal useful insights to help these organizations make decisions. Our results also facilitate a general understanding of the emerging community source development landscape