Inside the Black Box of Dictionary Building for Text Analytics: A Design Science Approach

The purpose of this paper is to develop and demonstrate a dictionary building process model for text analytics projects following the design science methodology. Using inductive consensus-building, we examined prior research to develop an initial process model. The model is subsequently demonstrated and validated by using data to develop an environmental sustainability dictionary for the IT industry. To our knowledge, this is an initial attempt to provide a normalized dictionary building process for text analytics projects. The resulting process model can provide a road map for researchers who want to use automated approaches to text analysis but are currently prevented by the lack of applicable domain dictionaries. Having a normalized design process model will assist researchers by legitimizing their work requiring dictionary building and help academic reviewers by providing an evaluation framework. The resulting environmental sustainability dictionary for IT industry can be used as a starting point for future research on Green IT and sustainability management

Approaches for Business Model Representation: An Overview

Explicitly representing a business model facilitates the understanding, analysis, and innovation of its underlying logic. For representing business models, numerous approaches have been suggested in the literature. They differ greatly in their understanding of the business model concept, the approach for representation, the terminology, and the notational elements they use. This impedes the diffusion of the representational approaches in business practice and the development of a cumulative research tradition. Our contributions are twofold: Based on a comprehensive literature review, we provide (I) a synthesizing framework for classifying approaches for business model representation, and (II) a terminological and conceptual synthesis of the notational elements. Thereby, practitioners are supported in selecting the most suitable representation for a specific purpose. For researchers, our work provides the basis to develop a more cumulative stream of research

Modeling Business Models: A cross-disciplinary Analysis of Business Model Modeling Languages and Directions for Future Research

Modeling languages for business models are a powerful and flexible means of representing and communicating knowledge related to business models. More than fifteen years after Osterwalder et al. (2005) clarified the ontology for the business model concept in this journal, we offer a systematic and cross-disciplinary assessment of the literature on business model modeling languages (BMMLs) that facilitate the visualization of this concept. In so doing, we synthesize and organize the knowledge dispersed across different disciplines in which BMMLs have originated and highlight the potential weaknesses in this literature to offer solid insights for future research. Our analysis reveals the existence of 17 BMMLs that have originated in traditional domains such as strategy and information systems, but also emerging domains such as sustainability. We contrast and compare these BMMLs along three dimensions: semantics, syntax, and pragmatics. We also analyze research that has made use of these BMMLs, differentiating between research that is conducted with a given BMML and research that is conducted about a given BMML. We conclude by offering a research agenda in which we illustrate the main challenges associated with the lack of well-accepted semantic, syntactic, and pragmatic foundations of BMMLs and outline opportunities for future research

On Guidelines for Representing Business Models - A Design Science Approach

Business models describe the modus operandi of a firm and reflect the activities and value streams from an abstract viewpoint. This paper proposes a set of guidelines for the representation of business models. Based on recent conceptualizations of business models and argumentation theory, we develop a comprehensive framework for the representation of a business model’s structure and the logic of how the individual parts are assembled. We argue that adhering to these guidelines untangles the visualization of business models. In addition this approach also propels a comprehensible design process since the structure of the argumentation is laid down explicitly, thereby supporting critical reflection. In a similar way, applying our approach to existing business models helps evaluating them critically since new vantage points within the argumentation can be revealed with ease