Towards a Reference Ontology for Business Models

In this paper, we propose a novel ontology based distributed personalized searching method. The user's information is distributed among the nodes in a peer-to- peer network to reduce the computational costs of the system. The user profile is modeled as a weighted concept hierarchy. We use weighing methods based on the user's surfing pattern to weigh the concepts in the reference ontology. The ontology is partitioned and each node learns a dimension of the user's interest using one partition, all partitions together form the user's profile. The system adapts itself to the changing interests of the user by means of aging. We use hierarchical neural networks to classify the documents into concepts in reference ontology. To overcome the problem of training in cases where insufficient documents are available for a particular concept and to increase the scalability we propose to use two different hierarchical neural network classifiers, each using a different learning function. Their beliefs are combined using Dempster-Shafer theory to eliminate any weaknesses in classification into concepts in the ontology. Our system has an overall performance improvement of around 20%.

In this paper we propose a novel ontology based personalized searching method called OPSHNN which uses hierarchical neural networks to classify documents into concepts in the reference ontology. The user profile is modeled as a weighted concept hierarchy. We use weighing methods based on the user's surfing pattern to weigh the concepts in the reference ontology. The system adapts itself to the changing interests of the user by means of aging. To overcome the problem of training in cases where insufficient documents are available for a particular concept and to increase the scalability we propose to use two different hierarchical neural network classifiers, each using a different learning function. Their beliefs are combined using Dempster-Shafer theory to eliminate any weaknesses in classification into concepts in the ontology. Results show that our system has superior classification accuracy, convergence and a precision of 16%.

Dear readers of Electronic Markets, Almost 15 years have passed since Electronic Markets published the first special issue on business models in 2001. This was a time where business strategists had difficulties in systematically explaining the essence, logic and ingredients of business models. Compared to the long-term timing that was prevalent in traditional thinking on business strategies, Internet thinkers and practitioners brought a new concept more or less overnight into the business world and caught many strategists by surprise. This does not mean that the new termwas always used precisely and with sufficient “meat”. As described by Magretta (2002, p.86), business models were “one of the great buzzwords of the Internet boom, routinely invoked, [...] to glorify all manner of half-baked plans”. Business model definitions emerged in the late 1990s and we are proud that one of the earliest definitions available was published by Paul Timmers from the European Commission in volume 8 of ElectronicMarkets. He conceived a business model as “an architecture for the product, service and information flows, including a description of the various business actors and their roles; and a description of the potential benefits for the various business actors; and description of the sources of revenues.” (Timmers 1998, p.4). It turns out that this definition was used widely and is still referenced today. Remarkably, the article has received the highest number of downloads and citations of all Electronic Markets articles so far. Following Harzing the article has scored a total of 2’283 citations (as per October 2014), which is considerably more than the second ranked article on citizen adoption of eGovernment (Warkentin et al. 2002) with a total of 434 citations. Another contribution on business models ranks third with some 404 citations. This is the preface to Electronic Markets’ first special issue on business models (Alt and Zimmermann 2001), which not only introduced the four research papers of the special issue at that time, but also aimed at summarizing existing knowledge in business model research. The paper started by analyzing the usage of the term “business model” in various databases and revealed only a limited proliferation. This has changed considerably as Table 1 shows with a sample of the same searches today and a total of 600 mentions in Electronic Markets papers in various contexts of business models since. Another analysis on the number of papers published in Web of Science journals even revealed some 4’000 mentions (DaSilva and Trikman 2013). It is astonishing that despite publications including the title term “business model” have attracted many writers, Teece (2010, p.192) concludes that the “paucity of literature (both theoretical and practical) on the topic is remarkable, given the importance of business design, particularly in the context of innovation.” In view of this statement, let us take the opportunity of this editorial to reflect on some aspects of the business model construct. First, business models are accepted as important elements in the construction of an organization’s strategic positioning and offerings in the market. Following the principle of models, they reduce real world complexity by representing only relevant design elements for a specific design purpose (Baden-Fuller and Morgan 2010). All other intricacies existent in the real world, which might be relevant for other purposes, should be suppressed. Thus, business models are helpful in mapping the specific ingredients and mechanics of understanding how a business works. Due to the obvious link to business strategy, a question that was raised is how business R. Alt (*) Information Systems Institute, University of Leipzig, Grimmaische Str. 12, 04109 Leipzig, Germany e-mail: rainer.alt@uni-leipzig.de

Event Abstract Back to Event OntoCATI: Towards an ontology of neuroimaging measures in the CATI Platform Lydie EDWARD1, 2*, Grégory Operto2, 3, Sylvain Poret1, 2, Yann Cointepas2, 3, Nader Cheaib2, 3, Leila Makkaoui2, 3 and Bénédicte M. Batrancourt1, 2 1 CRICM UPMC/INSERM UMR_S975, France 2 CATI, France 3 CEA, UNATI/NeuroSpin/I2BM, France CATI (Acquisition Centre and Image Processing, a French national platform supported by the Alzheimer’s Foundation [1]) provides software solutions for automatic measurement of different biomarkers related to specific modalities (Figure 1). CATI provides assistance for acquiring, analyzing, organizing and sharing neuroimaging data in the context of multi-centric clinical research studies. Our goal is to support the scientific study of the different working groups (neurologist, MRI PET physician, quality check operations engineer, engineer developing brain imaging tools) and help them to model the knowledge linked to their domain of interest. We proposed a structured metadata hierarchy for storing information relevant to various aspects of a project (e.g. study, subject, dataset, etc.) along with derived data and process in order to develop improved semantic request and reasoning tools for knowledge extraction on the derived data (for example we would like to compare the hippocampal volumes obtained on different time points). We developed a database schema CATISchema and an ontology OntoCATI [2]. At this stage, the first module of OntoCATI supports the information concerning acquisition, raw data (clinical and neuroimaging), and image processing. This module uses DOLCE [3] as its upper ontology. The image processing generates a multitude of data and derived measures. These measures are potential biomarkers for the Alzheimer’s disease (AD). In order to build the second module of OntoCATI dedicated to these measurements we first focus on the data issued from the modality T1 MRI and on three types of measures: rate of hippocampal atrophy with the longitudinal version of SACHA [4], cortical thickness reduction with Freesurfer (http://ftp.nmr.mgh.harvard.edu/) and opening of primary cortical folds using the longitudinal version of Morphologist-2012 pipeline [5]. An important point in our modeling consists in distinguishing the concept of measure and biomarker. For example, hippocampal volume is considered as the most widely used and admitted biomarkers in the AD to monitor its progression [6]. Therefore in OntoCATI this measure belongs to the sub-class of biomarker. Concerning the other measures the ontology will allow us to determine what measures become biomarkers using queries. To model the different measurements that are the assignment of numbers to anatomical entities, we need to describe the brain anatomy (e.g., hippocampus), the measure (magnitude, dimensions (units) and uncertainty) and the disease concepts and their codification. This module of OntoCATI uses the Basic Formal Ontology (BFO) as its upper level ontology [7]. For the anatomy domain we refer to the Foundational Model of Anatomy ontology (FMA) [8], which adopts and extends into BFO [9], a domain-independent, spatio-temporal theory that provides a rigorous ontological framework. Concerning the pathology domain we rely on ICD-10 [10] and UMLS standard [11]. For example to describe the hippocampus, according to FMA, we define hippocampus as a ‘gyrus of limbic lobe' that is a ‘segment of cerebral hemisphere’ that is a subClass of ‘Anatomical Entity’ that is a subclass of the BFO concept 'independent continuant'. To represent the volume of the hippocampus we create the relation has for volume that is linking the concept of ‘hippocampus’ to the BFO concept ‘three dimensional region’ (Figure 2). This is the first step in our work. In the future, we will integrate other concepts to represent the other measures (cortical thickness, opening of primary cortical folds, etc.). We will also work on the other modalities presented in Figure 1 and we will develop the queries to cross the frontier between measures and biomarkers. Figure 1 Figure 2 Acknowledgements This work is funded by the French Foundation Plan Alzheimer and was realized in the CATI study group. The authors gratefully acknowledge all contributors.

This paper presents a method to validate the insertion of a new concept in an ontology. This method is based on our previous works which add new concepts in a basic ontology using a general ontology (genaral ontology contains all the concepts of the basic ontology). To verify the semantic relevance of an ontology, we have proposed a method with three steps. First, we have found the neighborhood of the concept C in the basic ontology Ob and we store their semantic similarity values in a stack. The neighbourhood represents the concepts which are more similar to C in Ob. Secondly, we have assessed in the general ontology Og the semantic similarity between C and its neighbourhood found in the first step. Finally, we have evaluated the correlation between values found in the previous steps. We have considered the basic ontology as ontology with which we work and the general ontology as ontology used to align concepts with the basic ontology. The result obtained thanks to the method is a validated ontology after an update by adding a new concept. To illustrate our method, we have used the whole WordNet as the reference ontology and a branch of WordNet as basic ontology.

In most ontology-based scholar’s recommender systems, profiling approaches employ a reference ontology as a backbone hierarchy to learn the topics of scholar’s interests. It often works on the assumption that the reference ontology contains possible topics of scholars’ preferences. However, such single reference ontologies lack sufficient ontological concepts and poor ontological concepts, which unable to capture the entire scholars’ interests in terms of academic knowledge. In this paper, we extract, select, and merge heterogeneous subjects from different taxonomies on the Web and enrich by Wikipedia to constructs an OWL reference ontology for Computer Science domain. Compared to similar reference ontologies, our ontology purely supports the structure of scholars’ knowledge, contains richer topics of the domain, and best fits for profiling the scholars’ knowledge.

Context: Nowadays, software development organizations have adopted agile practices and data-driven software development aiming at a competitive advantage. Moving from traditional to agile and data-driven software development requires changes in the organization´s culture and structure, which may not be easy. The Stairway to Heaven Model (StH) describes this evolution path in five stages. Objective: We aimed to investigate how Systems Theory tools, GUT Matrix, and reference ontologies can help organizations in the first transition of StH, i.e., moving from traditional to agile development. Method: We performed a participative case study in a Brazilian organization that develops software in partnership with a European organization. We applied Systems Theory tools (systemic maps and archetypes) to understand the organization and identify undesirable behaviors and their causes. Thus, we used GUT Matrices to decide which ones should be addressed first and we defined strategies to change the undesirable behaviors by implementing agile practices. We also used the conceptualization provided by reference ontologies to share a common understanding of agile and help implement the strategies. Results: By understanding the organization, a decision was made to implement a combination of agile and traditional practices. The implemented strategies improved software quality and project time, and cost. Problems due to misunderstanding agile concepts were solved by using reference ontologies, process models, and other diagrams built based on the ontologies conceptualization, allowing the organization to experience agile culture and foresee changes in its business model. Conclusion: Systems Theory tools and GUT Matrix aid organizations to move from traditional to agile development by supporting better understanding the organization, finding leverage points of change, and enabling to define strategies aligned to the organization characteristics and priorities. Reference ontologies can be useful to establish a common understanding about agile, enabling teams to be aware of and, thus, more committed to agile practices and concepts. The use of process models and other diagrams can favor learning the conceptualization provided by the ontologies.

The aim of this research is to investigate the use of natural language processing techniques for ontology modelling that would address semantic interoperability problems arising due to terminological and semantic differences during information extraction from documents. These documents contain terminologies that are specific to the group and experts involved in creating them. As manual extraction is a tedious process, natural language processing techniques are suggested in this work. Text from different documents describing new terms are taken as input. These texts are processed to establish either semantic equivalence of the new term with concepts in reference ontology or add the term as a new concept if appropriate. Semantic role labelling is used for concept modelling and semantic role labelling tool is used in deriving the concept instances from the text, which are matched against concepts in the reference ontology to establish equivalence. If instances of attributes are equivalent, then concepts are said to be equivalent and if equivalence is limited to attributes, then ontology is populated with new concept. Results on technical text are presented with discussion on how the limitations observed can be removed.

Business actors must understand the importance of a business model in entrepreneurship; a business strategy is needed. There are several business models, but the one most often used by business actors is the Business Model Canvas or what we usually know (BMC). According to several studies, the Business Model Canvas can still be a business model that can still be developed into a more detailed business model and better mapping. Then from the Business Model Canvas, a new business model was developed, namely the Business Road Map, to win the market competition. Business Road Map is a pattern or Business Mapping Method to build a business model/business plan capable of creating growth over time. It was found that there was a significant increase in turnover after implementing the Business Roadmap. The actual Business Road Map is a development of the Business Model Canvas. Compared to other business models, the Business Road Map is considered to be much more detailed in business mapping and can also check the business's growth.

Business models are oftentimes considered as “the most discussed and least understood aspect of the web” (Rappa 2001). Despite a rough understanding that seems to be widespread – namely an aggregation of essential, relevant aspects from economic branches providing a compressed overview on business activities – dimensions, components, perspectives and core issues are depicted non-uniformly and confusing [PeKT01; Wirt01]. In particular, literature lacks contributions that particularly consider business model frameworks for networked economies, especially newly emerging loosely-coupled configurations as assumed in the business web theory. In order to address these shortcomings, we introduce a business model framework for business value networks as a result from an extensive literature review comprising two areas. Firstly, I conduct a state-of-the-art analysis of existent definitions of the term “business model” with emphasize on the elements that should be included, i.e. the relevant aspects of business activity. The study confirms the statements made by several authors: Some elements are broadly accepted – a description of created and offered value, revenue models, and business actors was included in more than 75% of the literature contributions. However, there are substantial differences in other components, e.g. market consideration, cost structure, or technology. In this connection, I also present a segregation of the concept business model from related concepts. Secondly, I outline the characteristics of business value networks as a newly emerging organizational form of loosely-coupled business networks. As a result, the partner network and the roles of these actors, their core competencies, and the role of the customer are identified as crucial elements that are to be considered in business models of companies acting in business value networks. Resulting from the literature analysis and a brief outlook how the customers are likely to be integrated in value creation processes in future, I propose a business model framework for business value networks comprising the five basic pillars value creation model, partner model, value offering model, customer model, and profit model. These pillars are decomposed into eleven business model components value configuration, core competencies, position in value system, partners and their roles, service/product portfolio, target customer, distribution channel, customer integration, revenue, pricing, and cost structure. Thus, the contribution of this article is twofold. On the one hand an updated understanding of the concept of business models within business value networks shall be established. On the other hand, I provide a framework which shall serve as a basis for further research, be it for the creation of a business model taxonomy in networked economies, the analysis of existent networked business models, or the development of concrete business models in the business value network context.

In doing business, business actors must understand the importance of a business model in entrepreneurship; a business strategy is needed. There are several business models, but the one most often used by business actors is the Business Model Canvas or what we usually know (BMC). According to several studies, the Business Model Canvas is a business model that can still be developed into a more detailed business model and better mapping. Then from the Business Model Canvas, a new business model was developed, namely the Business Road Map, to win the market competition. Business Road Map is a pattern or Business Mapping Method to build a business model/business plan capable of creating growth over time.

The idea that the real-world entities referred to by Information Systems are determinate and uniquely identifiable is a commonly held assumption in the fields of Software Engineering and Database Systems. The concept of identity is also a central topic in Formal Ontology, a discipline that finds application in the field of Information Systems through the use of Foundational Ontologies (FOs). However, while most central concepts of Formal Ontology are, in general explicitly addressed in FOs, the concept of identity has received relatively little attention. The lack of a proper ontological characterization of identity in FOs hinders their application to the analysis of issues related to identification in Information Systems, such as those that arise in conceptual modeling or in database design. This work proposes two distinct, but logically equivalent, formal characterizations of the notion of individual determinacy. Moreover, these characterizations are independent of the particularities of a FO's theory and are defined solely in terms of the structure of the FO's models of portions of reality. Finally, it also introduces a few concepts that are useful in the analysis of identity criteria for the individuals represented using a FO's theory.

PurposeSurvival challenges compel construction firms to change their business thinking on adapting business models (BMs). Unlike in the other fields, in the construction field, it is still a novel concept, probably because BM adaptation in the industry has not been sufficiently studied. Hence, the purpose of this study is to set a roadmap for the effective adaptation of the BM concept in the construction industry.Design/methodology/approachTo develop a roadmap, this study analysed BM literature through a comprehensive literature review by finding the BM research development stages using studies done in other fields and locating construction industry BM literature.FindingsNo stage-wise development of BM research has taken place in the construction industry. The four BM research development stages, namely, defining BMs, listing BM components, describing BM components and modelling BM components as a business model ontology (BMO) in relation to the construction industry have to be followed for proper BM adaptation in the construction industry.Originality/valueThis study provided an overview of and a roadmap for BM adaptation in the construction industry for the benefit of future researchers. The proper adaptation of the BM concept through a BMO will enable construction business managers to easily innovate, design and change construction BMs to streamline their business thinking.

PurposeContemporary public service innovations to an important degree are initiated and enabled by digitalization. Digitalization stimulates entry of new firms (start-ups) based on innovative implementation of digital technology for public services. The interwoven digitalization and innovation processes involve interaction and interdependencies between private business actors and public service providing actors. In this paper, the authors take the perspective of a start-up business actor that tries to develop and implement a viable business model in the very dynamic context of digital transformation of public education. The purpose of this paper is to analyze how the instability of a startup firm’s business model during public service innovation can be explained. The research question is: “How can business modeling by a start-up firm be explained by tensions between its business model and public service provision models?”Design/methodology/approachBased on an abductive logic, the authors choose a single-case study of a start-up firm’s development in 2010-2018 and its interaction with public actors. Information about the firm acquired in the first phase of the study showed that it frequently changed its business model. A general analytical framework was developed to aid in efforts to answer the research question.FindingsThe case showed that a business model could be seen as a temporary outcome of a business modeling process, and that also concurrently public actors change their public actors’ service provisioning models. Public-private interaction reveals tensions that drive business modeling.Originality/valueThe study contributes to empirical knowledge about private-public interaction in the dynamic and complex context in which digital transformation in society drives public service innovations. The conceptual contribution rests more generally in the analytical framework and how it frames public actor’s “service provision modeling” as a driver of business modeling.

Purpose: To facilitate the design of viable business models by proposing a novel business model design framework for viability. Design: A design science research method is adopted to develop a business model design framework for viability. The business model design framework for viability is demonstrated by using it to design a business model for an energy enterprise. The aforementioned framework is validated in theory by using expert opinion. Findings: It is difficult to design viable business models because of the changing market conditions, and competing interests of stakeholders in a business ecosystem setting. Although the literature on business models provides guidance on designing viable business models, the languages (business model ontologies) used to design business models largely ignore such guidelines. Therefore, we propose a business model design framework for viability to overcome the identified shortcomings. The theoretical validation of the business model design framework for viability indicates that it is able to successfully bridge the identified shortcomings, and it is able to facilitate the design of viable business models. Moreover, the validation of the framework in practice is currently underway. Originality / value: Several business model ontologies are used to conceptualise and evaluate business models. However, their rote application will not lead to viable business models, because they largely ignore vital design elements, such as design principles, configuration techniques, business rules, design choices, and assumptions. Therefore, we propose and validate a novel business model design framework for viability that overcomes the aforementioned shortcomings.