The Resource-Based Perspective An Assessment and Diagnosis of Problems

The resource-based approach to strategy, which reaches back to the contributions of Penrose, Selznick and Chandler, has gradually become the dominant perspective in strategy (content) research, arguably because it combines realism with relative rigour. The present paper presents the main themes of the contemporary version of the resource-based perspective (Wernerfelt, Rumelt, Barney....) and diagnoses a number of problems, such as the lack of a clear terminology, unclarity as to what really is the unit of analysis, the role of the environment, and the seemingly different versions that exist of the perspective. The perhaps deepest problem, however, is the lack of theorizing with respect to the creation of new resources, which tends to give the perspective a retrospective character and makes its application to managerial practice. It is suggested that resource-based scholars may draw upon work relating to real options, complementarities and organizational learning if they wish to remedy this deficiency.Organizational learning strategy

Incorporation of ontologies in data warehouse/business intelligence systems - A systematic literature review

Semantic Web (SW) techniques, such as ontologies, are used in Information Systems (IS) to cope with the growing need for sharing and reusing data and knowledge in various research areas. Despite the increasing emphasis on unstructured data analysis in IS, structured data and its analysis remain critical for organizational performance management. This systematic literature review aims at analyzing the incorporation and impact of ontologies in Data Warehouse/Business Intelligence (DW/BI) systems, contributing to the current literature by providing a classification of works based on the field of each case study, SW techniques used, and the authors’ motivations for using them, with a focus on DW/BI design, development and exploration tasks. A search strategy was developed, including the definition of keywords, inclusion and exclusion criteria, and the selection of search engines. Ontologies are mainly defined using the Ontology Web Language standard to support multiple DW/BI tasks, such as Dimensional Modeling, Requirement Analysis, Extract-Transform-Load, and BI Application Design. Reviewed authors present a variety of motivations for ontology-driven solutions in DW/BI, such as eliminating or solving data heterogeneity/semantics problems, increasing interoperability, facilitating integration, or providing semantic content for requirements and data analysis. Further, implications for practice and research agenda are indicated.info:eu-repo/semantics/publishedVersio

Artificial virtuous agents in a multi‐agent tragedy of the commons

Although virtue ethics has repeatedly been proposed as a suitable framework for the development of artificial moral agents (AMAs), it has been proven difficult to approach from a computational perspective. In this work, we present the first technical implementation of artificial virtuous agents (AVAs) in moral simulations. First, we review previous conceptual and technical work in artificial virtue ethics and describe a functionalistic path to AVAs based on dispositional virtues, bottom-up learning, and top-down eudaimonic reward. We then provide the details of a technical implementation in a moral simulation based on a tragedy of the commons scenario. The experimental results show how the AVAs learn to tackle cooperation problems while exhibiting core features of their theoretical counterpart, including moral character, dispositional virtues, learning from experience, and the pursuit of eudaimonia. Ultimately, we argue that virtue ethics provides a compelling path toward morally excellent machines and that our work provides an important starting point for such endeavors