13th Corporate Environmental Management Information Systems (CEMIS) Days (BUIS-Tage 2023) - Session I
- 12.10.23
- 10:00 - 12:00
- Chair : Volker Wohlgemuth
Developing a Digitization Dashboard for Industry-Level Analysis of the ICT Sector
- Timothy Musharu
- Carl von Ossietzky Universität Oldenburg
- Sylvenstein
- 10:00
The digital revolution in the Information and Communications Technology (ICT) sector necessitates advanced analytical tools to understand industry dynamics and support strategic decision-making. This article presents the development of a digitization Dashboard for industry-level analysis of the ICT sector. The study aims to fill the research gap in comprehensive industry-level analytical instruments and provide valuable insights for managers, policymakers, and industry stakeholders. The research questions focus on identifying technological advancements, understanding interconnections between technologies, and predicting industry growth.
A comprehensive literature review was conducted, covering various sectors related to ICT, digitization trends, and industry-level analysis. The review highlighted the need for a specialized Dashboard to integrate and visualize data across diverse technological domains within the ICT sector.
The methodology employed a hybrid approach using Design Science Research, combining quantitative data analysis with qualitative data for software development. Industry data, including patent analysis and technological trends, were collected, and processed during the analysis phase. Prototypes of the Dashboard were developed based on requirements from literature and industry standards in the design and development phase. The Dashboard underwent iterative improvements based on user feedback and usability testing.
The evaluation of the digitization Dashboard assessed its functionality, usability, and effectiveness in providing industry-level insights. The results demonstrate that the Dashboard offers valuable visual representations, trend analysis, and forecasting capabilities, empowering stakeholders to make informed decisions.
Limitations of the study include the reliance on qualitative data analysis, limiting the inclusion of quantitative insights, and the need for further validation of the Dashboard’s impact in real-world scenarios and diverse groups of users.
Future research should explore the integration of more machine learning techniques on patent data sources and user-centric evaluations to enhance the comprehensiveness and applicability of the digitization Dashboard. Continuous updates and expansions of the Dashboard functionalities are needed to accommodate emerging technological trends and evolving industry dynamics.
Design of a recommender system to improve the environmental impact of companies based on their material and energy balances
- Hatem Fayed
- Hochschule für Technik und Wirtschaft Berlin
- Sylvenstein
- 10:30
As worldwide agreements aiming to reduce the carbon footprint keep coming into effect, many companies aim to become more efficient in their production process. However, it is costly to hire environmental experts to help with the efficiency and carbon reduction process. This research aims to analyze the possibility of creating a Recommender System (RS) which suggests Carbon Reduction Measures (CRM) to the users based on their Life Cycle Assessment (LCA) reports. Based on the literature review into the latest RS techniques and the available databases, a study was conducted into creating a RS prototype. Analysis of the results demonstrates, that with the currently available databases, it is not possible to create an effective RS. The results indicate that in order to be able to create a functional and useful RS more detailed data needs to be extractable from the LCA tool. Further research is needed into the exports from other Environmental Management Information Systems (EMIS) and the identification of other factors that could strengthen the effectiveness of the RS.
Assessment Power of ChatGPT in the Context of Environmental Compliance Management – Experiments with a Real-World Regulation Cadastre
- Heiko Thimm
- Pforzheim University
- Sylvenstein
- 11:00
In multiple research disciplines use cases built on Large Language Models in particular ChatGPT are at the centre of today’s discussions. For example, in various ongoing projects of the LegalTech area ChatGPT is evaluated in terms of its potential to replace routine work of lawyers. In a recently started project we are investigating the use of ChatGPT for a specific corporate compliance management task. In particular, based on a real-world test data set ChatGPT is prompted to assess the relevance of environmental regulations. The ChatGPT output is compared to the respective judgements of the human experts in order to obtain a first indication of the assessment power of ChatGPT in the compliance management domain. This research in progress article gives an overview of the evaluation approach and presents first results of a set of 142 test cases covering regulations from four different areas of environmental legislation.
Design of IT structures in vaguely defined application environments - Experiences from actor interaction in the blue bioeconomy
- Christian Lohaus
- Technische Hochschule Lübeck
- Sylvenstein
- 11:30
This contribution focuses at appropriate IT structures for innovative market segments which form an application environment that is only fundamentally defined in digitization efforts. The core feature are vague application profiles for IT structures to be set up, which players in such market segments can use internally, but especially in environmental and social interaction. For the example of the emerging blue bioeconomy, experiences in setting up a cross-location, distributed IT structure are presented, which is geared towards advising and supporting actors in the blue bioeconomy by a diverse team of experts. Key findings lie in (i) the need to integrate different dimensions of vagueness in the treatment of increasingly defined information in a three-layer model of the IT structure, (ii) the development of the IT structure in an open process that takes into account the dynamics of the market sector, and (iii) the constant training of the members of the expert team on content, routines and limitations of the IT structure in consulting of actors.