Business Process Innovation using the Process Innovation Laboratory

Most organizations today are required not only to establish effective business processes but they are required to accommodate for changing business conditions at an increasing rate. Many business processes extend beyond the boundary of the enterprise into the supply chain and the information infrastructure therefore is critical. Today nearly every business relies on their Enterprise System (ES) for process integration and the future generations of enterprise systems will increasingly be driven by business process models. Consequently process modeling and improvement will become vital for business process innovation (BPI) in future organizations. There is a significant body of knowledge on various aspect of process innovation, e.g. on conceptual modeling, business processes, supply chains and enterprise systems. Still an overall comprehensive and consistent theoretical framework with guidelines for practical applications has not been identified. The aim of this paper is to establish a conceptual framework for business process innovation in the supply chain based on advanced enterprise systems. The main approach to business process innovation in this context is to create a new methodology for exploring process models and patterns of applications. The paper thus presents a new concept for business process innovation called the process innovation laboratory a.k.a. the Ð-Lab. The Ð-Lab is a comprehensive framework for BPI using advanced enterprise systems. The Ð-Lab is a collaborative workspace for experimenting with process models and an explorative approach to study integrated modeling in a controlled environment. The Ð-Lab facilitates innovation by using an integrated action learning approach to process modeling including contemporary technological, organizational and business perspectivesNo; keywords

Moffett and rhetoric

This examination of Moffett's contribution to a theory of school English concentrates on his understanding of rhetoric. It is suggested that the impetus for Teaching the Universe of Discourse is dialectical: he was running against currents in English teaching at the time that were literary and technical, as well as the specific practices of sentence combining and embedding. His introduction of rhetoric into debates about school English was a key move, as rhetoric had been seen by American contemporaries as related to higher education and public discourse (and drawing on classical models). Moffett's more generous notion of rhetoric as the ‘arts of discourse’ helped him chart a ‘larger rhetoric of behaviour’ and map out his curriculum and development model. It is a rhetoric that moves beyond the definition of the ‘art of persuasion’ to one based in drama, dialogue and dialectic

Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement Learning

Finding tight bounds on the optimal solution is a critical element of practical solution methods for discrete optimization problems. In the last decade, decision diagrams (DDs) have brought a new perspective on obtaining upper and lower bounds that can be significantly better than classical bounding mechanisms, such as linear relaxations. It is well known that the quality of the bounds achieved through this flexible bounding method is highly reliant on the ordering of variables chosen for building the diagram, and finding an ordering that optimizes standard metrics is an NP-hard problem. In this paper, we propose an innovative and generic approach based on deep reinforcement learning for obtaining an ordering for tightening the bounds obtained with relaxed and restricted DDs. We apply the approach to both the Maximum Independent Set Problem and the Maximum Cut Problem. Experimental results on synthetic instances show that the deep reinforcement learning approach, by achieving tighter objective function bounds, generally outperforms ordering methods commonly used in the literature when the distribution of instances is known. To the best knowledge of the authors, this is the first paper to apply machine learning to directly improve relaxation bounds obtained by general-purpose bounding mechanisms for combinatorial optimization problems.Comment: Accepted and presented at AAAI'1

Beyond opening up the black box: Investigating the role of algorithmic systems in Wikipedian organizational culture

Scholars and practitioners across domains are increasingly concerned with algorithmic transparency and opacity, interrogating the values and assumptions embedded in automated, black-boxed systems, particularly in user-generated content platforms. I report from an ethnography of infrastructure in Wikipedia to discuss an often understudied aspect of this topic: the local, contextual, learned expertise involved in participating in a highly automated social-technical environment. Today, the organizational culture of Wikipedia is deeply intertwined with various data-driven algorithmic systems, which Wikipedians rely on to help manage and govern the "anyone can edit" encyclopedia at a massive scale. These bots, scripts, tools, plugins, and dashboards make Wikipedia more efficient for those who know how to work with them, but like all organizational culture, newcomers must learn them if they want to fully participate. I illustrate how cultural and organizational expertise is enacted around algorithmic agents by discussing two autoethnographic vignettes, which relate my personal experience as a veteran in Wikipedia. I present thick descriptions of how governance and gatekeeping practices are articulated through and in alignment with these automated infrastructures. Over the past 15 years, Wikipedian veterans and administrators have made specific decisions to support administrative and editorial workflows with automation in particular ways and not others. I use these cases of Wikipedia's bot-supported bureaucracy to discuss several issues in the fields of critical algorithms studies, critical data studies, and fairness, accountability, and transparency in machine learning -- most principally arguing that scholarship and practice must go beyond trying to "open up the black box" of such systems and also examine sociocultural processes like newcomer socialization.Comment: 14 pages, typo fixed in v

Theorizing and Generalizing About Risk Assessment and Regulation Through Comparative Nested Analysis of Representative Cases

This article provides a framework and offers strategies for theorizing and generalizing about risk assessment and regulation developed in the context of an on-going comparative study of regulatory behavior. Construction of a universe of nearly 3,000 risks and study of a random sample of 100 of these risks allowed us to estimate relative U.S. and European regulatory precaution over a thirty-five-year period. Comparative nested analysis of cases selected from this universe of ecological, health, safety, and other risks or its eighteen categories or ninety-two subcategories of risk sources or causes will allow theory-testing and -building and many further descriptive and causal comparative generalizations

Designing an information system for updating land records in Bangladesh: action design ethnographic research (ADER)

Open Access. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.This article has been made available through the Brunel Open Access Publishing Fund.Information Systems (IS) has developed through adapting, generating and applying diverse methodologies, methods, and techniques from reference disciplines. Further, Action Design Research (ADR) has recently developed as a broad research method that focuses on designing and redesigning IT and IS in organizational contexts. This paper reflects on applying ADR in a complex organizational context in a developing country. It shows that ADR requires additional lens for designing IS in such a complex organizational context. Through conducting ADR, it is seen that an ethnographic framework has potential complementarities for understanding complex contexts thereby enhancing the ADR processes. This paper argues that conducting ADR with an ethnographic approach enhances design of IS and organizational contexts. Finally, this paper aims presents a broader methodological framework, Action Design Ethnographic Research (ADER), for designing artefacts as well as IS. This is illustrated through the case of a land records updating service in Bangladesh