Smart data and business analytics: A theoretical framework for managing rework risks in mega-projects

2022 | International Journal of Information Management | Citations: 0

Authors: Matthews, Jane; Love, Peter E.D.; Porter, Stuart R.; Fang, Weili

Abstract: Within construction, we have become increasingly accustomed to relying on the be ... Expand

Abstract: Within construction, we have become increasingly accustomed to relying on the benefits of digital technologies, such as Building Information Modelling, to improve the performance and productivity of projects. We have, however, overlooked the problems that technology is unable to redress. One such problem is rework, which has become so embedded in practice that technology adoption alone can not resolve the issue without fundamental changes in how information is managed for decision-making. Hence, the motivation of this paper is to bring to the fore the challenges of classifying and creating an ontology for rework that can be used to understand its patterns of occurrence and risks and provide a much-needed structure for decision-making in transport mega-projects. Using an exploratory case study approach, we examine ‘how’ rework information is currently being managed by an alliance that contributes significantly to delivering a multi-billion dollar mega-transport project. We reveal the challenges around location, format, structure, granularity and redundancy hindering the alliance’s ability to classify and manage rework data. We use the generative machine learning technique of Correlation Explanation to illustrate how we can make headway toward classifying and then creating an ontology for rework. We propose a theoretical framework utilising a smart data approach to generate an ontology that can effectively use business analytics (i.e., descriptive, predictive and prescriptive) to manage rework risks. Collapse

Topics: knowledge representation decision making analytical information system information management big data

Methods: ontological modelling computational algorithm machine learning natural language processing case study

Attention to Exploration: The Effect of Academic Entrepreneurship on the Production of Scientific Knowledge

2022 | Organization Science | Citations: 17

Authors: Fini, Riccardo; Perkmann, Markus; Ross, Jan-Michael

Abstract: We study how becoming an entrepreneur affects academic scientists’ research. We ... Expand

Abstract: We study how becoming an entrepreneur affects academic scientists’ research. We propose that entrepreneurship will shift scientists’ attention away from intradisciplinary research questions and toward new bodies of knowledge relevant for downstream technology development. This will propel scientists to engage in exploration, meaning they work on topics new to them. In turn, this shift toward exploration will enhance the impact of the entrepreneurial scientist’s subsequent research, as concepts and models from other bodies of knowledge are combined in novel ways. Entrepreneurship leads to more impactful research, mediated by exploration. Using panel data on the full population of scientists at a large research university, we find support for this argument. Our study is novel in that it identifies a shift of attention as the mechanism underpinning the beneficial spillover effects from founding a venture on the production of public science. A key implication of our study is that commercial work by academics can drive fundamental advances in science. Collapse

Topics: entrepreneurship productivity database system research and development accounting

Methods: longitudinal research robustness check qualitative interview descriptive statistic literature sample

Phishing video game to validate the principles of persuasion in university students

2021 | Americas Conference on Information Systems | Citations: 0

Authors: Abrahamzon Garcia, Valeria; Parra, Raul Diaz

Abstract: ... Expand

Abstract: Collapse

Topics: phishing email phishing IT career pandemic social media

Methods: survey survey design parametric test survival analysis Student's t-test

A hybrid approach of modular Planning – synchronizing factory and building planning by using component based synthesis

2020 | HICSS | Citations: 0

Authors: Winkels, Jan; Graefenstein, Julian; Lenz, Lisa; Weist, Kai; Krebil, Kevin; Gralla, Mike

Abstract: The more and more rising complexity of the industrial environment is triggering ... Expand

Abstract: The more and more rising complexity of the industrial environment is triggering companies in a way that is more challenging than ever before. Not only are factory planning projects difficult to handle because of the dynamics and complexity also the necessary planning of the accompanied building gets more and more difficult. To handle this complexity and reduce time and effort for planning as a major factor of success the mainly separately done planning aspects needs to be synchronized. This paper will show an approach of a hybrid factory-building planning method in order to be able to shorten planning time and effort. By using a constraint solving technique the necessary planning tasks are aligned partly automatically and will be processed as a useful planning workflow in form of a gantt diagram for the overall project management. Collapse

Topics: manufacturing information system robotic programming language

Methods: synthesis

Computational Intelligence for Engineering Design Applications: A Case Study in Structural Engineering

2019 | Americas Conference on Information Systems | Citations: 0

Authors: Kamat, Anuja; Deokar, Amit

Abstract: In this interdisciplinary study, we present a framework for applying computatio ... Expand

Abstract: In this interdisciplinary study, we present a framework for applying computational intelligence techniques to address structural engineering design problems that are ill-structured and do not have well-established and tested theoretical models. The framework is presented as a design artifact that is validated through a case study in structural engineering using a large set of experimental data on shear failure of reinforced concrete beams. Collapse

Topics: knowledge base database system open source Python knowledge work

Methods: case study computational algorithm machine learning feature engineering descriptive statistic

Learning by Seconding: Evidence from National Science Foundation Rotators

2019 | Organization Science | Citations: 0

Authors: Kolympiris, Christos; Hoenen, Sebastian; Klein, Peter G.

Abstract: We study knowledge flows between organizations through secondments, short-term e ... Expand

Abstract: We study knowledge flows between organizations through secondments, short-term employee assignments at an organization different from the home institution. Secondments allow the sending organization to capture knowledge and network resources from the receiving organization without an organization-level contract, alliance, or colocation, a process we term learning by seconding. We focus on the National Science Foundation (NSF) rotation program, under which the NSF employs academics, called rotators, on loan from their university, to lead peer reviews. We ask how rotators affect the behavior of their academic colleagues after returning from a secondment. Using difference in differences estimations, we show that rotators’ colleagues raise considerably more research funds than similar scientists who do not have a rotator colleague. Additional quantitative and qualitative evidence implies that the treatment effect occurs via knowledge transfer, as rotators help generate ideas, frame proposals, and explain processes, rather than rent-seeking on the part of the rotator. Overall, the results suggest that strong ties and shared social identity play an important role in organizational knowledge acquisition. The online appendix is available at https://doi.org/10.1287/orsc.2018.1245. Collapse

Topics: knowledge sharing productivity website LinkedIn social identity

Methods: qualitative interview experimental group longitudinal research difference in differences robustness check

THE FUTURE OF DIGITAL WORK - USE CASES FOR AUGMENTED REALITY GLASSES

2019 | European Conference On Information Systems | Citations: 0

Authors: Kortekamp, Sarah-Sabrina; Werning, Sebastian; Thomas, Oliver; Ickerott, Ingmar

Abstract: Microsoft’s HoloLens enables true augmented reality (AR) by placing virtual obje ... Expand

Abstract: Microsoft’s HoloLens enables true augmented reality (AR) by placing virtual objects within the real world. This paper aims at presenting trades (based on ISIC) that can benefit from AR as well as possible use cases. Firstly, the authors conducted a systematic literature search to identify relevant papers. Six databases (including EBSCOhost, ScienceDirect and SpringerLink) were scanned for the term “HoloLens”. Out of 680 results, two researchers identified 150 articles as thematically relevant. Secondly, these papers were analysed utilising qualitative content analysis. Findings reveal 26 trades where AR glasses are in use for practice or research purposes. The most frequent are human health, education and research. In addition, we provide a catalogue of 7 main use cases, such as Process Guidance or Data Access and Visualisation as well as 27 sub use cases addressing corresponding functionalities in more detail. The results of this paper are trades and application scenarios for AR glasses. Thus, this article contributes to research in the field of service systems design, especially AR glasses-based service systems, and provide evidence for the future of digital work. Collapse

Topics: logistics management IT work smart device augmented reality systems design

Methods: literature study literature sample design artifact qualitative content analysis theoretical contribution

The Role of Application Domain Knowledge in Using OWL DL Diagrams: A Study of Inference and Problem-Solving Tasks

2016 | International Conference on Information Systems | Citations: 0

Authors: Leukel, Joerg; Sugumaran, Vijayan; Hubl, Marvin

Abstract: Diagrammatic conceptual schemas are an important part of information systems ana ... Expand

Abstract: Diagrammatic conceptual schemas are an important part of information systems analysis and design. For effectively communicating domain semantics, modeling grammars have been proposed to create highly expressive conceptual schemas. One such grammar is the Web Ontology Language (OWL), which relies upon description logics (DL) as a knowledge representation mechanism. While an OWL DL diagram can be useful for representing domain semantics in great detail, the formal semantics of OWL DL places a burden on diagram users. This research investigates how user’s prior knowledge of the application domain impacts solving inference tasks as well as schemabased problem-solving tasks using OWL DL diagrams. Our empirical validation shows that application domain knowledge has no effect on inference performance but enhances schema-based problem-solving performance. We contribute to the conceptual modeling literature by studying task performance for a highly expressive modeling grammar and introducing inference tasks as a new task type. Collapse

Topics: problem solving task productivity project management knowledge representation website

Methods: experiment statistical hypothesis test conceptual modelling statistical power analysis longitudinal research

Theories: cognitive fit theory

Asset Identification in Information Security Risk Assessment: A Business Practice Approach

2016 | Communications of the Association for Information Systems | Citations: 1

Authors: Shedden, Piya; Ahmad, Atif; Smith, Wally; Tscherning, Heidi; Scheepers, Rens

Abstract: Organizations apply information security risk assessment (ISRA) methodologies to ... Expand

Abstract: Organizations apply information security risk assessment (ISRA) methodologies to systematically and comprehensively identify information assets and related security risks. We review the ISRA literature and identify three key deficiencies in current methodologies that stem from their traditional accountancy-based perspective and a limited view of organizational “assets”. In response, we propose a novel rich description method (RDM) that adopts a less formal and more holistic view of information and knowledge assets that exist in modern work environments. We report on an in-depth case study to explore the potential for improved asset identification enabled by the RDM compared to traditional ISRAs. The comparison shows how the RDM addresses the three key deficiencies of current ISRAs by providing: 1) a finer level of granularity for identifying assets, 2) a broader coverage of assets that reflects the informal aspects of business practices, and 3) the identification of critical knowledge assets. Collapse

Topics: business process management data security organizational memory accounting information security risk

Methods: case study business process model and notation modeling language qualitative interview personal interview

Analysis of Federated Enterprise Architecture Models.

2015 | European Conference On Information Systems | Citations: 0

Authors: Antunes, Goncalo; Barateiro, Jose; Caetano, Artur; Borbinha, José Luis

Abstract: Enterprise architecture models support decision-making as they help organizatio ... Expand

Abstract: Enterprise architecture models support decision-making as they help organizations to understand, communicate and analyse how business processes are performed, the goals they achieve, the information they use, as well as the applications that realize the business, and the supporting technological infrastructure. The integrated analysis of these models is not straightforward because it cross-cuts different domains that are described using heterogeneous concepts. This paper explores the application of ontologies to analyse enterprise architecture models. Ontologies represent knowledge that can be analysed using computational inference. The contributions of this paper are (1) the specification of multiple enterprise architecture models as ontological schemas, (2) the integration of ontological schemas, and (3) the analysis of the integrated models. The solution artefact consists of a federated model specified as a set of ontological schemas described in OWL-DL that integrates multiple enterprise models and assists their analysis using computational inference. The paper demonstrates the application of the federated model to the ArchiMate language as a means to assess the compliance of business requirements in a civil engineering scenario.This section reviews the main concepts and definitions related to enterprise architecture model analysis (section 2.1) and ontologies (section 2.2). Collapse

Topics: enterprise architecture knowledge representation user requirement extensible markup language business process management

Methods: ontological modelling design science metamodel upper ontology