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The livestock sector is growing steadily and is responsible for around 18% of global greenhouse‐gas‐emissions, which is more than the global transport sec-tor (Steinfeld et al. 2006). This paper examines the potential of social marketing to reduce meat consumption. The aim is to understand consumers’ motivation in diet choices and to learn what opportunities social marketing can provide to counteract negative environmental and health trends. The authors believe that research to answer this question should start in metropolitan areas, be-cause measures should be especially effective there. Based on the Theory of Planned Behaviour (TPB, Ajzen 1991) and the Technology‐Acceptance‐Model by Huijts et al. (2012), an online‐study with participants from the metropolitan region (n = 708) was conducted in which central socio‐psychological constructs for a meat consumption reduction were examined. It was shown that attitude, personal norm and habit have a critical influence on the intention to reduce meat consumption. A segmentation of consumers based on these factors led to three consumer clusters: vegetarians/flexitarians, potential flexitarians and convinced meat eaters. Potential flexitarians are an especially relevant target group for the development of social‐marketing‐measures to reduce meat consumption. In co‐creation‐workshops with potential flexitarians from the metropolitan region, barriers and benefits of reducing meat consumption were identified. The factors of environmental protection, animal welfare and desire for variety turn out to be the most relevant motivational factors. Based on these factors, consumers proposed a variety of social marketing measures, such as applications and labels to inform about the environmental impact of meat products.
The energy sector in Germany, as in many other countries, is undergoing a major transformation. To achieve the climate targets, numerous measures to implement smart energy and resource efficiency are necessary. Therefore, energy companies are experiencing increasing pressure from politics and society to transform their business areas in a sustainable manner and implement smart and sustainable business models. Consequently, numerous resources are expected to flow into the development and implementation of new business models. But often these efforts remain unsuccessful in practice. There is a large amount of literature on barriers and drivers of smart and sustainable business models in the energy sector. But what are the factors that companies struggle with most when developing and implementing new business models in practice? To answer this question, the results of a systematic literature review were evaluated by conducting semi-structured interviews with experts of the German energy sector. Six categories of transformation barriers were identified: Organizational, Financial, Legal, Partner-Network, Societal and Technological barriers. To overcome these barriers, recommendations for action and key success factors are outlined by the experts interviewed. The interview study validates key barriers and drivers in terms of their significance in practice in the German energy sector and makes recommendations to advance the smart and sustainable transformation of the energy sector.
This is a report from a one-day fourth international workshop on "Information Systems in Distributed Environments" (ISDE), which was organized in conjunction with the OnTheMove Federated Conferences & Workshops (OTM 2014) October 29-30, 2014, Amantea, Calabria, Italy. The main focus of this event was to provide a venue for the discussion of challenges related to the development, operation, and maintenance of distributed information systems, and their creation in the context of global development projects. Further dissemination of research results will lead to an improvement of distributed information system development and deployment across the globe.
The implementation of a web based portal QA solution will lead to a high acceptance of the staff as the usage of commonly known standard software (e.g. web browser) allows intuitive handling. In the daily use a significant simplification of the workflow and Performance enhancement can be achieved by easy access to the check documents. As the data is now saved in a database it can easily be processed and long-term trends can be displayed. Therefore possible errors can be detected much easier and earlier. By the usage of time stamps and user authentication procedures and user responsibilities are comprehensibly documented. As the software is browser based, integration into an existing software Environment is not critical. As only technical QA data is processed, no further data security measures are necessary. A certification as a medical product is not required.
The business landscape is changing radically because of software. Companies in all industry sectors are continously finding new flexibilities in this programmable world. They are able to deliver new functionalities even after the product is already in the customer's hands. But success is far from guaranteed if they cannot validate their assumptions about what their customers actually need. A competitor with better knowledge of customer needs can disrupt the market in an instant.
This book introduces continuous experimentation, an approach to continuously and systematically test assumptions about the company's product or service strategy and verify customers' needs through experiments. By observing how customers actually use the product or early versions of it, companies can make better development decisions and avoid potentially expensive and wasteful activities. The book explains the cycle of continuous experimentation, demonstrates its use through industry cases, provides advice on how to conduct experiments with recipes, tools, and models, and lists some common pitfalls to avoid. Use it to get started with continuous experimentation and make better product and service development decisions that are in-line with your customers' needs.
Digital twins deployed in production are important in practice and interesting for research. Currently, mostly structured data coming from e.g., sensors and timestamps of related stations, are integrated into Digital Twins. However, semi- and unstructured data are also important to display the current status of a digital twin (e.g., of a machinery or produced good). Process Mining and Text Mining in combination can be used to support the use of log file data to understand the current state of the process as well as highlight issues. Therefore, issue related reactions can be taken more quickly, targeted and cost oriented. Applying a design science research approach; here a prototype as an artefact based on derived requirements is developed. This prototype helps to understand and to clarify the possibilities of Process Mining and Text Mining based on log data for production related Digital Twins. Contributions for practice and research are described. Furthermore, limitations of the research and future opportunities are pointed out.
Digitalization and enterprise architecture management: a perspective on benefits and challenges
(2023)
Many companies digitally transform their business models, processes, and services. They have also been using Enterprise Architecture Management approaches for a long time to synchronize corporate strategy and information technology. Such digitalization projects bring different challenges for Enterprise Architecture Management. Without understanding and addressing them, Enterprise Architecture Management projects will fail or not deliver the expected value. Since existing research has not yet addressed these challenges, they were investigated based on a qualitative expert study with leading industry experts from Europe. Furthermore, potential benefits of digitalization projects for Enterprise Architecture Management were researched. Our results provide a theoretical framework consisting of five identified challenges, triggers and a number of benefits. Furthermore, we discuss in what ways digitalization and EAM is a promising topic for future research.
Data analysis is becoming increasingly important to pursue organizational goals, especially in the context of Industry 4.0, where a wide variety of data is available. Here numerous challenges arise, especially when using unstructured data. However, this subject has not been focused by research so far. This research paper addresses this gap, which is interesting for science and practice as well. In a study three major challenges of using unstructured data has been identified: analytical know-how, data issues, variety. Additionally, measures how to improve the analysis of unstructured data in the industry 4.0 context are described. Therefore, the paper provides empirical insights about challenges and potential measures when analyzing unstructured data. The findings are presented in a framework, too. Hence, next steps of the research project and future research points become apparent.
Revenue management information systems are very important in the hospitality sector. Revenue decisions can be better prepared based on different information from different information systems and decision strategies. There is a lack of research about the usage of such systems in small and medium-sized hotels and architectural configurations. Our paper empirically shows the current development of revenue information systems. Furthermore, we define future developments and requirements to improve such systems and the architectural base.
New business concepts such as Enterprise 2.0 foster the use of social software in enterprises. Especially social production significantly increases the amount of data in the context of business processes. Unfortunately, these data are still an unearthed treasure in many enterprises. Due to advances in data processing such as Big Data, the exploitation of context data becomes feasible. To provide a foundation for the methodical exploitation of context data, this paper introduces a classification, based on two classes, intrinsic and extrinsic data.