Applying a Structured Industry Model Development Process to Support Digital Transformation Efforts

While business models transformed how we describe organizations, the authors apply equivalent modeling to describe industries. Specifically, the authors propose and implement a structured industry model development process (SIMDP) based on the design science research methodology (DSRM). Moreover, our novel approach conceptualizes an industry model scaffolded through academic research and managerial guidance. An industry model creates a holistic view of any target industry to a) guide digital transformation efforts, b) reveal model components and linkages that may not be immediately evident, and c) support strategic decision-making within organizations considering the expansion and refinement of existing business models. The authors demonstrate the SIMDP’s efficacy using a case study of the online learning industry and evaluate the resulting industry model. Finally, the authors suggest future research directions and discuss the practical implications of the SIMDP and its resulting artifacts.

Strategic Business Model Development in Ecosystems

<p>Designing and strategically developing viable business models is vital for value creation and capture and in turn for the survival and performance of entrepreneurial ventures. However, the widely held firm-centric and static business model perspective appears inadequate to reflect the realities of increasingly blurred industry boundaries, interconnected economies, and the resulting collapse of incumbent value chains. This PhD thesis adds understanding of the dynamic business model development process from an ecosystem perspective. The evolution of ten entrepreneurial ventures’ business models was documented and investigated through longitudinal in-depth case studies over twelve months. Analysing and comparing the cases revealed strategies that resulted in the development of effective interactive structures and robust value co-creation and capture mechanisms. The development of interactive structures, i.e. firm-ecosystem fits, was either supported by a focused or diversified ecosystem integration approach underpinned by heterogeneous interdependencies of value proposition and business model components across ecosystems. The obtained insights allowed the derivation of sets of capabilities that supported the business model development process and enhanced entrepreneurial ventures’ chances of survival. The findings have several implications for advancements of the business model theory. In particular they indicate what integration strategies can inform entrepreneurs’ and managers’ business model design and execution strategies for operating in increasingly complex ecosystems.</p>

Strategic Business Model Development in Ecosystems

<p>Designing and strategically developing viable business models is vital for value creation and capture and in turn for the survival and performance of entrepreneurial ventures. However, the widely held firm-centric and static business model perspective appears inadequate to reflect the realities of increasingly blurred industry boundaries, interconnected economies, and the resulting collapse of incumbent value chains. This PhD thesis adds understanding of the dynamic business model development process from an ecosystem perspective. The evolution of ten entrepreneurial ventures’ business models was documented and investigated through longitudinal in-depth case studies over twelve months. Analysing and comparing the cases revealed strategies that resulted in the development of effective interactive structures and robust value co-creation and capture mechanisms. The development of interactive structures, i.e. firm-ecosystem fits, was either supported by a focused or diversified ecosystem integration approach underpinned by heterogeneous interdependencies of value proposition and business model components across ecosystems. The obtained insights allowed the derivation of sets of capabilities that supported the business model development process and enhanced entrepreneurial ventures’ chances of survival. The findings have several implications for advancements of the business model theory. In particular they indicate what integration strategies can inform entrepreneurs’ and managers’ business model design and execution strategies for operating in increasingly complex ecosystems.</p>

A Survey of Domain Knowledge Elicitation in Applied Machine Learning

Eliciting knowledge from domain experts can play an important role throughout the machine learning process, from correctly specifying the task to evaluating model results. However, knowledge elicitation is also fraught with challenges. In this work, we consider why and how machine learning researchers elicit knowledge from experts in the model development process. We develop a taxonomy to characterize elicitation approaches according to the elicitation goal, elicitation target, elicitation process, and use of elicited knowledge. We analyze the elicitation trends observed in 28 papers with this taxonomy and identify opportunities for adding rigor to these elicitation approaches. We suggest future directions for research in elicitation for machine learning by highlighting avenues for further exploration and drawing on what we can learn from elicitation research in other fields.

GAMES: A dynamic model development workflow for rigorous characterization of synthetic genetic systems

Mathematical modeling is invaluable for advancing understanding and design of synthetic biological systems. However, the model development process is complicated and often unintuitive, requiring iteration on various computational tasks and comparisons with experimental data. Ad hoc model development can pose a barrier to reproduction and critical analysis of the development process itself, reducing potential impact and inhibiting further model development and collaboration. To help practitioners manage these challenges, we introduce GAMES: a workflow for Generation and Analysis of Models for Exploring Synthetic systems that includes both automated and human-in-the-loop processes. We systematically consider the process of developing dynamic models, including model formulation, parameter estimation, parameter identifiability, experimental design, model reduction, model refinement, and model selection. We demonstrate the workflow with a case study on a chemically responsive transcription factor. The generalizable workflow presented in this tutorial can enable biologists to more readily build and analyze models for various applications.

Automating GIS input for distributed urban drainage modelling

The development of distributed urban drainage models is becoming more important as cities prepare for the challenges associated with climate change such as more intense precipitation events (McCarthy et al. 2010; Allan, 2011; Simõeset et al. 2011; Blumensaat et al. 2012; Leitãoet al. 2012). GIS-based tools were developed to generate input datasets for a 1-D distributed urban drainage model for part of Toronto's combined area, resulting in an efficient model development process compared to those utilizing manual approaches. These automatic GIS-based tools included the delineation of Wet Weather Flow (WWF) subcatchments (stormwater) and Dry Weather Flow (DWF) subcatchments (sanitary). It also included the determination of the intensity of rainfall on a more detailed scale than the coarse coverage provided by the City's rain gauges and the traditional Thiessen polygon interpolation method. Through testing the new tools designed in ModelBuilder, it was determined that 66% and 52% of DWF and WWF subcatchments respectively, were automatically delineated to a degree where they would be "Acceptable" for input into the urban drainage model, InfoWorks CS. Although the rainfall tools were able to continuously interpolate measured rainfall (on a seemingly unprecedented basis),and generate over 700 virtual rain gauges, the validity of the approach remains imperfect due to irresolvable inconsistencies between the City's gauges and those used for validation purposes.

Automating GIS input for distributed urban drainage modelling

The development of distributed urban drainage models is becoming more important as cities prepare for the challenges associated with climate change such as more intense precipitation events (McCarthy et al. 2010; Allan, 2011; Simõeset et al. 2011; Blumensaat et al. 2012; Leitãoet al. 2012). GIS-based tools were developed to generate input datasets for a 1-D distributed urban drainage model for part of Toronto's combined area, resulting in an efficient model development process compared to those utilizing manual approaches. These automatic GIS-based tools included the delineation of Wet Weather Flow (WWF) subcatchments (stormwater) and Dry Weather Flow (DWF) subcatchments (sanitary). It also included the determination of the intensity of rainfall on a more detailed scale than the coarse coverage provided by the City's rain gauges and the traditional Thiessen polygon interpolation method. Through testing the new tools designed in ModelBuilder, it was determined that 66% and 52% of DWF and WWF subcatchments respectively, were automatically delineated to a degree where they would be "Acceptable" for input into the urban drainage model, InfoWorks CS. Although the rainfall tools were able to continuously interpolate measured rainfall (on a seemingly unprecedented basis),and generate over 700 virtual rain gauges, the validity of the approach remains imperfect due to irresolvable inconsistencies between the City's gauges and those used for validation purposes.

Learning Model Development of Memorizing The Qur'an Through Integration of Internal and External Representation

This research aims to create a learning model of memorization of the Qur'an based on the nature of the brain that tends to require relevance between the projection of information that occurred internally in the brain (internal representation) and externally presented information outside the brain (external representation). Integration of the two modes of representation was carried out through a developmental study by adopting Research and Development (R &amp; D) from Borg and Gall as a reference for the development of conceptual frameworks and memory models of Y Wang as a reference framework of the development of operational stages. From the model development process, several components of the model implementation have successfully been developed. The model implementation was operationally integrated with internal and external representation modes such as Phase I: the formulation of indicators, Phase II diagnostic assessment dealing with prior al-Qur’an memorizing ability, Phase III Conditioning students, Phase IV Coding memorizing materials, and Phase V repetition and recalling memorizing outcomes.

Pengembangan Media Belajar Audiovisual Untuk Pembelajaran Memperbaiki Motor Listrik di SMK Negeri 1 Sarolangun

Learning process for repairing electricity motor competency at skill competency of Installation Electric Power Technique at SMK Negeri 1 Sarolangun has not been run effectively. In fact, learning material in repairing electricity motor just used modul as teaching materi and media learning. While, to get the competency thad needed, learning process should be supported by leaning tool well. For answer the problem above, teacher as a fasilitator in achievment of students competency is demanded to creative in learning management. One of them is by finding alternative solution that is by develop audiovisual media for learning of repairing electricity motor that can give solution in lerning process. Development of this media aim to product efective media in learning material of repairing electricity motor at SMK Negeri 1 Sarolangun. Development model that chosen is based on Borg and Gall model that adapted lerning design Dick and Carey model. Development process is done by 5 main steps: (1) Doing analysis, (2) Design pre product, (3) Validation and revision, (4) Try out at small scale field and, (5) Try out big group field. Based on the try out of audiovisual media for learning of repairing electricity motor at the SMK, responden give suggestion that the media can be benefit in learning process at school. The reason is that media can give information about the jobs steps clearly at matery of repairing electricity motor so give ease in learning. This ease in proved by the result of try out at big group that give conclution, there is increasingly at the result of study. There by, the media can comprehand learning material fast.