Preference Revelation in Multi-Attribute Reverse English Auctions: A Laboratory Study

The effects of preference revelation on allocational and Pareto efficiency are studied in a multi-attribute reverse English auction. Multi-attribute reverse auctions have been proposed as market institutions for electronic request for quotation buying processes. Preference revelation is a crucial question in multi-attribute reverse auctions in terms of the efficiency of auction outcomes. Results from a computer-based laboratory experiment are reported and auction outcomes are analyzed regarding the buyer’s and suppliers’ surplus, efficiency, and Pareto efficiency. The results show that suppliers make more profits when preferences are revealed, but not at the expense of the buyer, and that full revelation of the buyer’s preferences significantly increases allocational and Pareto efficiency

Integration Deficits of IT Controlling – Historical Background, Analysis of Integration Potentials and Method Integration

The paper is based on the thesis that IT controlling suffers from two integration deficits with regard to its methods base: On the one hand, this is a lack of synchronization between research on IT controlling methods and developments in practice; on the other hand, a lack of integration of IT controlling methods with methods of business and information systems engineering (BISE). Based on this assumption, the paper investigates historical developments in IT controlling research and practice to derive theses about the present state of method integration. The analysis finds indications for further potential for method integration and identifies these potentials. Requirements towards method integration are derived from an analysis of the identified integration potentials and two examples illustrate how to realize further integration

Toward a Taxonomy of Modeling Difficulties: A Multi-Modal Study on Individual Modeling Processes

Conceptual modeling is an essential activity during information systems development and, accordingly, a learning task faced by students of Information Systems. Presently, surprisingly little is known about how learning processes of conceptual modeling proceed, and about modeling difficulties learners experience. In this study, we integrate complementary modes of observation of learners\u27 modeling processes to identify modeling difficulties these learners face while performing a data modeling task using a modeling tool. We use the concept of cognitive breakdowns to analyze verbal protocols, recordings of learner-tool interactions and video recordings of learners\u27 modeling processes and survey learners about modeling difficulties. Our study identifies five types of modeling difficulties relating to different aspects of constructing conceptual data models, i.e., entity types, relationship types, attributes, and cardinalities. The identified types of modeling difficulties motivate a taxonomic theory of modeling difficulties intended to inform design science research on tool support for learners of conceptual modeling

Modeling styles in conceptual data modeling: Reflecting observations in a series of multimodal studies

A modeling style characterizes a modeler’s sequencing of processing a modeling task in terms of applying the modeling language and its language concepts while constructing a conceptual model. Presently, surprisingly little is known about the different modeling styles modelers exhibit when performing conceptual data modeling. In this research, we combine complementary modes of observation including audio-visual protocols, recorded modeler-tool interactions, and pre-/post-modeling surveys of modelers to identify modeling styles in 24 data modeling processes performed by modelers at different stages of experience in data modeling. Our study identifies and characterizes three distinct modeling styles refining our current knowledge about data modeling processes and informing design science research on style-specific, targeted modeling (software tool) support for data modelers

Business Process Simulation: A Systematic Literature Review

Business process simulation marks an essential Business Process Management technique for analysing business processes and for reasoning about process improvement. Despite its importance, literature is lacking a comprehensive, updated overview of research contributions to the field of business process simulation. In this systematic literature review, we assess the present state of research on business process simulation including prior work between 1990 and 2016. Results reported in the present study assist in advancing the discussion on future research on business process simulation by compiling and analysing prior work. The present literature review focuses on prior research involving conceptual business process models, e.g., BPMN models, with a graphical model representation as a starting point for business process simulation and excludes other foundations to build simulation models

A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach

How do we learn conceptual modeling? What are common learning difficulties? Which tool support assists learners in what respect? The paper at hand reports on the design and development of a browser-based modeling tool integrated with a learning observatory in support of learning conceptual modeling and of studying the learning of conceptual modeling. Implementing a multimodal data collection approach, the learning observatory tracks learner-tool interactions, records verbal data from learners and surveys learners about their learning processes to provide for analyses at the individual and aggregate learner levels in the quest for identifying patterns of learning processes, learning barriers and difficulties. We report on the current state of prototype development, discuss its software architecture and outline future development steps

Experimental research on bilateral negotiations

Research on bilateral negotiation