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Evaluation of tech ventures’ evolving business models: rules for performance-related classification
(2022)
At the early stage of a successful tech venture's life cycle, it is assumed that the business model will evolve to higher quality over time. However, there are few empirical insights into business model evolution patterns for the performance-related classification of early-stage tech ventures. We created relevant variables evaluating the evolution of the venture-centric network and the technological proposition of both digital and non-digital ventures' business models using the text of submissions to the official business plan award in the German State of Baden-Württemberg between 2006 and 2012. Applying a principal component analysis/rough set theory mixed methodology, we explore performance-related business model classification rules in the heterogeneous sample of business plans. We find that ventures need to demonstrate real interactions with their customers' needs to survive. The distinguishing success rules are related to patent applications, risk capital, and scaling of the organisation. The rules help practitioners to classify business models in a way that allows them to prioritise action for performance.
Validity of the business model is a key indicator for buying into ventures in the early-stage. Business models of early-stage ventures decrease in validity when developing the business over the progressing stages of the business life-cycle. By doing so, the ventures are validating their business model when building transaction relationships to the surrounding value network. In prior research, we developed a research design based on existing business innovation proposals (onepager, pitch decks, business plans) that is assumed to evaluate the status of business model validation. The core hypothesis of the research design is that transaction relations represent a strong anchor between the business model and the business reality, thus providing information on the business model validity. In this research, we test this hypothesis by designing and analyzing a survey that was directed to founders taking part in a business plan competition. We compared the relationships described in the submitted business plans to the relations explicitely stated in the follow-up questionnaire. We identified that the described relations to customers, investors, and people (human resources) match the relationships expressed in questionnaires quite well. A significant disagreement, however, exists in the relationships to suppliers. We conclude that there is still a theoretical and empirical gap that leads to disagreement between business plans and reality in the group of suppliers.
New Technology-Based Firms (NTBFs) learn their business in the early-stages of their life-cycle. As a central element of the entrepreneurial learning process, the business model describes the value-creation functions that are conceptualized in different stages of the NTBF’s life-cycle. Transaction relations connect the model with the business reality and ideally mature in strength over time to a functioning value-network. This chapter describes the development of a research design that determines, extracts, and evaluates semantics constructs of this entrepreneurial learning out of a convenient sample and three cohorts of business plans submitted to a business plan award between 2008 and 2010. The analysis shows empirical evidence for the survival and growth of those NTBFs that exhibit a balanced status of entrepreneurial learning in the maturity of the value-network that can be characterized as early startup-stage. The empirical findings of the network theory based business plan analysis will allow for a better explanation of the performance in the entrepreneurial process that is discussed for NTBFs based on theory of organizational learning.
The business model canvas (BMC) and the lean start-up manifesto (LSM) have been changing both the entrepreneurial education and, on the practical side, the mindset in setting up innovative ventures since the burst of the dot-com bubble. However, few empirical insights on the business model implementation patterns that distinguish between digital and non-digital innovative ventures exist. Connecting practical management tools to network theory as well as to the theory of organizational learning, this paper investigates evolution patterns of digital and non-digital business models out of the deal flow of an innovation intermediary. For this purpose, a multi-dimensional quantitative content analysis research design is applied to 242 ventures' business plans. The measured strength of transaction relations to customers, suppliers, people, and financiers has been combined with performance indicators of the sampled ventures. The results indicate that in order to succeed, digital ventures iterate their business on the market early and search for investment afterwards. Contrariwise, non-digital ventures already need financial investments in the early stages to set up a product ready to be tested on the market. In both groups we found strong evidence that specific evolutionary patterns relate to higher rates of success.
The business plan is one of the most frequently available artifacts to innovation intermediaries of technology-based ventures' presentations in their early stages [1]–[4]. Agreement on the evaluations of venturing projects based on the business plans highly depends on the individual perspective of the readers [5], [6]. One reason is that little empirical proof exists for descriptions in business plans that suggest survival of early-stage technology ventures [7]–[9]. We identified descriptions of transaction relations [10]–[13] as an anchor of the snapshot model business plan to business reality [13]. In the early-stage, surviving ventures are building transaction relations to human resources, financial resources, and suppliers on the input side, and customers on the output side of the business towards a stronger ego-centric value network [10]–[13]. We conceptualized a multidimensional measurement instrument that evaluates the maturity of this ego-centric value networks based on the transaction relations of different strength levels that are described in business plans of early-stage technology ventures [13]. In this paper, the research design and the instrument are purified to achieve high agreement in the evaluation of business plans [14]–[16]. As a result, we present an overall research design that can reach acceptable quality for quantitative research. The paper so contributes to the literature on business analysis in the early-stage of technology-based ventures and the research technique of content analysis.
Mutual Information Analysis for Generalized Spatial Modulation Systems With Multilevel Coding
(2022)
Generalized Spatial Modulation (GSM) enables a trade-off between very high spectral efficiencies and low hardware costs for massive MIMO systems. This is achieved by transmitting information via the selection of active antennas from a set of available antennas besides the transmission of conventional data symbols. GSM systems have been investigated concerning various aspects like suitable signal constellations, efficient detection algorithms, hardware implementations, spatial precoding, and error control coding. On the other hand, determining the capacity of GSM is challenging because no closed-form expressions have been found so far. This paper investigates the mutual information for different GSM variants. We consider a multilevel coding approach, where the antenna selection and IQ modulation are encoded independently. Combined with multistage decoding, such an approach enables low-complexity capacity-achieving coded modulation. The influence of the data symbols on the mutual information is illuminated. We analyze the portions of mutual information related to antenna selection and the IQ modulation processes which depend on the GSM variant and the signal constellation. Moreover, the potential of spatial modulation for massive MIMO systems with many transmit antennas is investigated. Especially in systems with many transmit antennas much information can be conveyed by antenna selection.
Entrepreneurial employees
(2019)
Volatile markets and accelerating innovation cycles progressively force established companies to adopt alternative innovation strategies such as entrepreneurship. Due to the key role entrepreneurial employees play for strengthening the company's abilities for innovation and change, various concepts have emerged like corporate entrepreneurship or intrapreneurship. While the extant literature has increasingly examined only specific issues of entrepreneurial employees, an overall view on it lacks investigation. Therefore, the purpose of this paper is to structurally present current research on entrepreneurial employees by conducting a broad systematic literature review. The resulting research streams contribute to a clearer justification for future research and are a first step towards a comprehensive research view related to intrapreneurship.
Research credits corporate entrepreneurship (CE) with enabling established companies to create new types of innovation. Scholars have focused on the organizational design of CE activities, proposing specific organizational units. These semi-autonomous units create a tense management situation between the core organization and its CE activities. Management and organization research considers control as a key managerial function for help. However, control has received limited research attention regarding CE units, leaving design issues for appropriate control of CE units unanswered. In this study, we link management control and CE to illustrate how control is understood in the context of CE. For this, we scanned the CE literature to identify underlying attributes and characteristics that allow specifying control for CE. We identified 11 attributes to describe control for CE activities in a first round and to derive future research paths.
Corporate Entrepreneurship (CE) has now evolved into an imperative innovation practice of established companies. Despite organizational design models for CE activities and companies' frequent initiation of new activities, effectively managing them remains a challenging endeavor which results in disappointment about the outcomes of CE and its early termination. We assume specific types of goals for CE as one element of this unresolved management issue. While both practice and literature address goals in different contexts, no uniform picture has emerged so far. Although goals are commonly used to categorize CE activities, they seldomly seem to be the core subject of investigation. Based on this preliminary analysis and consolidation, we put the goals of CE in focus. In a systematic literature review, we reveal aspects of goals to unmask the different types of goals and their underlying dimensions and characteristics. Our review contributes to a better understanding of goals by (1) organizing relevant literature on goals of CE in a specific classification process, (2) describing dimensions and attributes for a systematic classification of CE goals; and (3) providing a framework showing differences of goals for the CE context. We conclude with a discussion and hints for future research paths.
Guiding through the Fog
(2021)
Corporate Entrepreneurship (CE) programs are formalized efforts to realize entrepreneurial activities in established companies. Despite the growing and evolving landscape of CE programs, effectively managing them remains a challenging endeavor which results in disappointing outcomes and oftentimes leads to the early termination of such programs. We unmask the differences in goal setting of CE programs and highlight that setting appropriate goals is imperative for their desired outcomes. In practice, companies seem to struggle with the goal setting, and scholars have not yet fully solved the puzzle of goals setting in the context of CE programs either. Therefore, we set out to explore the current state of goal setting in the context of CE programs building upon 61 semi-structured interviews with CE program executives from cross-industry companies with different sizes. Our study contributes to a better understanding of goal setting in the context of CE programs by (1) characterizing the goal setting of CE programs based on goal attributes and goal types and (2) identifying differences among the goal setting of CE programs. We provide implications to practice for a more effective management of CE programs and conclude with a discussion for future research on the impact of the different goal settings.
We present an analysis of how to determine security requirements for software that controls routing decisions in the distribution of discrete physical goods. Requirements are derived from stakeholder interests and threat scenarios. Three deployment scenarios are discussed: cloud and hybrid deployment as well as on-premise installation for legacy sites.
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open problem. Existing methods separate inpainting of global structure and the transfer of details, which leads to blurry results and loss of global coherence in the detail transfer step. Based on advances in texture synthesis using CNNs we propose patch-based image inpainting by a single network topology that is able to optimize for global as well as detail texture statistics. Our method is capable of filling large inpainting regions, oftentimes exceeding quality of comparable methods for images of high-resolution (2048x2048px). For reference patch look-up we propose to use the same summary statistics that are used in the inpainting process.
In this paper we present a method using deep learning to compute parametrizations for B-spline curve approximation. Existing methods consider the computation of parametric values and a knot vector as separate problems. We propose to train interdependent deep neural networks to predict parametric values and knots. We show that it is possible to include B-spline curve approximation directly into the neural network architecture. The resulting parametrizations yield tight approximations and are able to outperform state-of-the-art methods.
Knot placement for curve approximation is a well known and yet open problem in geometric modeling. Selecting knot values that yield good approximations is a challenging task, based largely on heuristics and user experience. More advanced approaches range from parametric averaging to genetic algorithms.
In this paper, we propose to use Support Vector Machines (SVMs) to determine suitable knot vectors for B-spline curve approximation. The SVMs are trained to identify locations in a sequential point cloud where knot placement will improve the approximation error. After the training phase, the SVM can assign, to each point set location, a so-called score. This score is based on geometric and differential geometric features of points. It measures the quality of each location to be used as knots in the subsequent approximation. From these scores, the final knot vector can be constructed exploring the topography of the score-vector without the need for iteration or optimization in the approximation process. Knot vectors computed with our approach outperform state of the art methods and yield tighter approximations.
Deep 3D
(2017)
Vortrag
In the reverse engineering process one has to classify parts of point clouds with the correct type of geometric primitive. Features based on different geometric properties like point relations, normals, and curvature information can be used, to train classifiers like Support Vector Machines (SVM). These geometric features are estimated in the local neighborhood of a point of the point cloud. The multitude of different features makes an in-depth comparison necessary. In this work we evaluate 23 features for the classification of geometric primitives in point clouds. Their performance is evaluated on SVMs when used to classify geometric primitives in simulated and real laser scanned point clouds. We also introduce a normalization of point cloud density to improve classification generalization.
Creating cages that enclose a 3D-model of some sort is part of many preprocessing pipelines in computational geometry. Creating a cage of preferably lower resolution than the original model is of special interest when performing an operation on the original model might be to costly. The desired operation can be applied to the cage first and then transferred to the enclosed model. With this paper the authors present a short survey of recent and well known methods for cage computation.
The authors would like to give the reader an insight in common methods and their differences.
Cities around the world are facing an increasing number of global and local challenges, such as climate change and scarcity of raw materials. At the same time trends like digitalization, globalization and networking gain in importance. For this reason, cities have started imple-menting smart solutions within the urban structure in order to evolve towards a Smart City. In Botswana, the Maun Science Park is intended to provide a best practice approach for a Bot-swanan Smart City. Since Smart City concepts have to be specifically tailored to local condi-tions, the first main goal of this thesis is to develop a synthesis concept for the Maun Science Park. A key problem in cities is the utilization of space, which is further intensified by increasing urbanization and population growth. Therefore, the second main goal is to develop approaches of (digitally) re-programmable space to use available areas intelligently and optimized.
Within the thesis, human-centered design has been applied as structure-giving methodology. By clarifying relevant Smart City contents, considering reference examples as well as identify-ing local challenges and requirements, an appropriate concept has been developed with hu-man-focus. Furthermore, the methodologies of literature research and expert interviews have been used as input in the individual human-centered design phases. In combination with an innovation funnel, the methodology human-centered design forms the structure of the thesis.
In total, ten main solution areas and 37 sub-segments have been identified for the synthesis concept of Maun Science Park. Additionally, a concept for Smart Buildings has been devel-oped as a part of the synthesis concept and as an essential infrastructure component of the Maun Science Park (three main segments, 16 sub-segments). Based on expert input, a priori-tization has been determined by evaluating the impact and economic affordability of the indi-vidual sub-areas. Moreover, individual key areas have been highlighted by identifying direct interactions between sub-segments and on the basis of expert input – these are particularly related to the segments Smart Data and Smart People. Besides the synthesis concept, ap-proaches of (digitally) re-programmable space have been created. Thereby, ten approaches refer to the conversion, reuse or expansion abilities of space within daily, weekly or life cycle. In addition, the conventional (digitally) re-programmable space idea has been extended by two new considerations – “multi-purpose use of built-up space” and “concept programming in the planning phase”. Finally, within an overall consideration – synthesis concept combined with approaches of (digitally) re-programmable space – the added value of the developed contents has been outlined, positive and negative aspects have been identified within a SWOT analysis and the business model of the Maun Science Park approach has been verified in a Business Model Canvas.
Through explicit elaboration, classification and prioritization of solution areas, the developed concept can serve as a basis for further project steps. Based on the defined requirements of the sub-segments, solutions can be developed with regard to the entire Smart City context.
Due to the rising need for palliative care in Russia, it is crucial to provide timely and high-quality solutions for patients, relatives, and caregivers. A methodology for remote monitoring of patients in need of palliative care and the requirements will be developed for a hardware-software complex for remote monitoring of patients' health at home.
Urban car-free mobility
(2021)
Across the globe, urban areas experience the phenomena of rising road-congestion, air pollution and car accidents. These are just a few popular quantified effects that arise due to rapid, uncoordinated urbanization on a car-centric city layout. There is an urgent need to consider new concepts of urban mobility development to combat these negative effects. Car-free mobility is one notion adopted in diverse formats by numerous cities to create a more inclusive, just, healthy and sustainable urban life. The focus of this thesis is to ex- amine whether a car-free mobility concept is applicable to the Maun Science Park, Bot- swana. Therefore, the idea of car-free mobility, its positive aspects as well as its con- straints, are described first. This illustrates the complexity of urban transport planning as it is intertwined with urban land-use, political vision and people’s perceptions and behav- iors. Secondly, examples and strategies on how to change existing structures are pre- sented. Following this, the smart developments in the field of sustainable urban mobility are considered to provide an insight into their assets and drawbacks. Then the local mo- bility conditions are examined before the car-free concept is exemplarily applied to the Maun Science Park via scenario construction. These scenarios give a first vision of how a car-free concept can be applied to the MSP and additionally provide a starting point for future strategic planning as well as inspiration for other cities to follow along.
Creative industry and cultural tourism destination Lake Constance - a media discourse analysis
(2020)
The following media discourse analysis examines the news media coverage of four regional online newspapers, about the topics “creative industries” and “cultural tourism” at Lake Constance region in the period from 2006 until 2016. The results show that, besides event-relater reporting, there is currently no vibrant media discourse on the topics “creative industries” and “cultural tourism”. Even though the image of the Lake Constance region is heavily influenced by tourism, “cultural tourism” also plays a secondary role when it comes to regional news reporting. Moreover, discourses do not overlap and thus no synergies within the local media discourse are formed. This result is relevant for the regional tourism development, because the cooperation between “creative industries” and “cultural tourism” creates opportunities such as the expansion of the tourism offer and an extension of the tourist season. To activate unused opportunities at the different destinations of the region, a supra-regional visibility of the sector “creative industries” should be developed and the cooperation of the sector with local stakeholders of cultural tourism should be promoted.
Cultural Mapping 4.0
(2021)
Cultural mapping aims to capture and visualize tangible and intangible cultural assets. This extend abstract proposes the consequent extension of analogue forms of cultural mapping using digital technologies, and its contribution is two-fold. First, the necessary theoretical basis is provided by a literature review of the still-young field of cultural mapping and the complementary disciplines of participatory mapping and digital story-mapping. Second, we propose a digitally enhanced Cultural Mapping 4.0 vision based on a case study from an ongoing research project in the Lake Constance region. Digital participatory mapping approaches are applied to capture data, and to validate and disseminate the results, story-mapping - a spatial form of digital storytelling - is used.
The Lake Constance region is due to its scenic attractiveness one of the most visited destinations in German-speaking countries. Scenic attractiveness as well as so-called landscape stereotypes also play a decisive role in tourism marketing. Tour operators reproduce supra-individual landscape concepts and establish mental geographies that ultimately influence the choice of destinations. A growing trend in tourism is the emergence of creative narratives in tourism marketing and tourism offers induced by creative companies. By means of a discourse-analytical investigation, whose theoretical and conceptual frame of reference is the hegemony and discourse theory of Laclau and Mouffe (1985), recurring landscape stereotypes are identified in tourist promotional material for the destination Bodensee. Based on these results as well as expert interviews with regional tourism stakeholders, a discussion of the creative economic potential for regional tourism marketing will take place. The investigation shows that these potentials are currently not being exhausted. At the same time, creative tourism can help a rural region, such as Lake Constance, to position itself as an alternative to city tourism, while at the same time addressing the lucrative target group 60plus.
To learn from the past, we analyse 1,088 "computer as a target" judgements for evidential reasoning by extracting four case elements: decision, intent, fact, and evidence. Analysing the decision element is essential for studying the scale of sentence severity for cross-jurisdictional comparisons. Examining the intent element can facilitate future risk assessment. Analysing the fact element can enhance an organization's capability of analysing criminal activities for future offender profiling. Examining the evidence used against a defendant from previous judgements can facilitate the preparation of evidence for upcoming legal disclosure. Follow the concepts of argumentation diagrams, we develop an automatic judgement summarizing system to enhance the accessibility of judgements and avoid repeating past mistakes. Inspired by the feasibility of extracting legal knowledge for argument construction and employing grounds of inadmissibility for probability assessment, we conduct evidential reasoning of kernel traces for forensic readiness. We integrate the narrative methods from attack graphs/languages for preventing confirmation bias, the argumentative methods from argumentation diagrams for constructing legal arguments, and the probabilistic methods from Bayesian networks for comparing hypotheses.
Conducting surveillance impact assessment is the first step to solve the "Who monitors the monitor?" problem. Since the surveillance impacts on different dimensions of privacy and society are always changing, measuring compliance and impact through metrics can ensure the negative consequences are minimized to acceptable levels. To develop metrics systematically for surveillance impact assessment, we follow the top-down process of the Goal/Question/Metric paradigm: 1) establish goals through the social impact model, 2) generate questions through the dimensions of surveillance activities, and 3) develop metrics through the scales of measure. With respect to the three factors of impact magnitude: the strength of sources, the immediacy of sources, and the number of sources, we generate questions concerning surveillance activities: by whom, for whom, why, when, where, of what, and how, and develop metrics with the scales of measure: the nominal scale, the ordinal scale, the interval scale, and the ratio scale. In addition to compliance assessment and impact assessment, the developed metrics have the potential to address the power imbalance problem through sousveillance, which employs surveillance to control and redirect the impact exposures.
The intentions of the so-called "More Electrical Aircraft" (MEA) are higher efficiency and lower weight. A main topic here is the application of electrical instead of hydraulical, pneumatical and mechanical systems. The necessary power electronic devices have intermediate DC-links, which are typically supplied by a three-phase system with active B6 and passive B12 rectifiers. A possible alternative is the B6 diode bridge in combination with an active power filter (APF). Due to the parallel arrangement, the APF offers a higher power density and is able to compensate for harmonics from several devices. The use of the diode bridge rectifier alone is not permitted due to the highly distorted phase current. The following investigations are dealing with the development of an active power filter for a three-phase supply with variable frequency from 360 to 800 Hz. All relevant components such as inductors, EMC-filters, power modules and DC-link capacitor are designed. A particular focus is put on the customized power module with SiC-MOSFETs and SiC-diodes, which is characterized electrically and thermally. The maximum supply frequency slope has a value of 50 Hz/ms, which requires a high dynamic and robustness on the control algorithm. Furthermore, the content of 5th and 7th harmonics must be reduced to less than 2 %, which demands a high accuracy. To cope with both requirements, a two-stage filter algorithm is developed and implemented in two independent signal processors. Simulations and laboratory experiments confirm the performance and robustness of the control algorithm. This work comprehensively presents the design of aerospace rectifiers. The results were published in conferences and patents.
It is widely recognized that sustainability is a new challenge for many manufacturing companies. In this paper, we tackle this issue by presenting an approach that deals with material and substance compliance within Product Lifecycle Management in a complex value chain. Our analysis explains why, how and when sustainable manufacturing arises, and it identifies, quantifies and evaluates the environmental impact of a new product. We propose (I) a Life Cycle Assessment tool (LCA) and (II) a model to validate this approach and evaluate the risk of noncompliance in supply chain. Our LCA approach provides comprehensive information on environmental impacts of a product.
Product and materials cycles are parallel and intersecting, making it challenging to integrate Material Selection Process across Product Lifecycle Management, Integration of LCA with PLM. We provide only a foundation. Further research in systems engineering is necessary. LCA is sensitive to data quality. Outsourcing production and having problems in supplier cooperation can result in material mismatch (such as property, composition mismatching) in the production process due to that may cause misleading of LCA results.
This paper also describes research challenges using riskbased due diligence.
In the last decade, both sustainability and business models for sustainability have increased in importance. Sustainability issues have become the focus of discussion. These issues are interlinked and often negatively impact each other. They are complex and include socio-ecological dilemmas, exist in almost every aspect of our society (economic, environmental, social), and are hard to formulate. They may have multiple, incompatible solutions, competing objectives, and open timeframes. Previous research has not developed satisfactory ways to comprehend and solve problems of this nature. Life Cycle Assessment (LCA) the widely used method to assess sustainable development has reached its limitation to achieve sustainable social goals. System Dynamics (SD) is a valuable methodology that enhances understanding of the structure and internal dynamic behaviours of large, complex, and dynamic systems, leading to improved decision-making. It offers a philosophy and set of tools for modelling, analysing, and simulating dynamic systems. This research applied system dynamics methods in conjunction with simulation software to assess the potential impact of a solution on environmental, social, and economic aspects of a complex system, aims to gain insights into the system's behaviour and identify the potential consequences of interventions or policy changes across multiple dimensions. This paper responds to the urgent need for a new business model by presenting a concept for an adapted dynamic business modelling for sustainability (aDBMfS) using system dynamics. Case studies in the smartphone industry are applied.
Despite the importance of Social Life Cycle Sustainability Assessment (S-LCSA), little research has addressed its integration into Product Lifecycle Management (PLM) systems. This paper presents a structured review of relevant research and practice. Also, to address practical aspects in more detail, it focuses on challenges and potential for adoption of such an integrated system at an electronics company.
We began by reviewing literature on implementations of Social-LCSA and identifying research needs. Then we investigated the status of Social-LCSA within the electronics industry, both by reviewing literature and interviewing decision makers, to identify challenges and the potential for adopting S-LCSA at an electronics company. We found low maturity of Social-LCSA, particularly difficulty in quantifying social sustainability. Adoption of Social-LCSA was less common among electronics industry suppliers, especially mining & smelting plants. Our results could provide a basis for conducting case studies that could further clarify issues involved in integrations of Social-LCSA into PLM systems.
It is widely recognized that sustainability is a new challenge for many manufacturing companies. In this paper, we tackle this issue by presenting an approach that deals with material and substance compliance within Product Lifecycle Management in a complex value chain. Our analysis explains why, how and when sustainable manufacturing arises, and it identifies, quantifies and evaluates the environmental impact of a new product. We propose (I) a Life Cycle Assessment tool (LCA) and (II) a model to validate this approach and evaluate the risk of non-compliance in supply chain. Our LCA approach provides comprehensive information on environmental impacts of a product.
Product and materials cycles are parallel and intersecting, making it challenging to integrate Material Selection Process across Product Lifecycle Management, Integration of LCA with PLM. We provide only a foundation. Further research in systems engineering is necessary. LCA is sensitive to data quality. Outsourcing production and having problems in supplier cooperation can result in material mismatch (such as property, composition mismatching) in the production process due to that may cause misleading of LCA results. This paper also describes research challenges using risk-based due diligence.
In the last decade, both sustainability (Green &
Blue Economies) and business models for sustainability
(BMfS) have increased in importance. Social life cycle
sustainability assessment has not fully achieved goal,
mainly because sustainability‐oriented business is very
complex and dynamic. System Dynamics (SD) is a powerful
methodology and computer simulation modeling technique
for framing, understanding and discussing complex issues
and problems. This paper responds to the urgent need for
a new business model by presenting a concept for dynamic
business modeling for sustainability using system dynamics.
The paper illustrates the key operating principles through
an application from the smartphone industry with help
from STELLA® software for simulation. Simulations
suggest that dynamic business modeling for sustainability
may contribute to sustainable business model research and
practice by introducing a systemic design tool that frames
environmental, social, and economic drivers of value
generation into a dynamic business model causal feedback
structure, therefore overcoming shortcomings of current
business models when applied to complex systems.
We present an alternative approach to grid management in low voltage grids by the use of artificial intelligence. The developed decision support system is based on an artificial neural network (ANN). Due to the fast reaction time of our system, real time grid management will be possible. Remote controllable switches and tap changers in transformer stations are used to actively manage the grid infrastructure. The algorithm can support the distribution system operators to keep the grid in a safe state at any time. Its functionality is demonstrated by a case study using a virtual test grid. The ANN achieves a prediction rate of around 90% for the different grid management strategies. By considering the four most likely solutions proposed by the ANN, the prediction rate increases to 98.8%, with a 0.1 second increase in the running time of the model.
To master complexity, we can organize it or discard it. The Art of Insight in Science and Engineering first teaches the tools for organizing complexity, then distinguishes the two paths for discarding complexity: with and without loss of information. Questions and problems throughout the text help readers master and apply these groups of tools. Armed with this three-part toolchest, and without complicated mathematics, readers can estimate the flight range of birds and planes and the strength of chemical bonds, understand the physics of pianos and xylophones, and explain why skies are blue and sunsets are red.
Digitization and sustainability are the two big topics of our current time. As the usage of digital products like IoT devices continues to grow, it affects the energy consumption caused by the Internet. At the same time, more and more companies feel the need to become carbon neutral and sustainable. Determining the environmental impact of an IoT device is challenging, as the production of the hardware components should be considered and the electricity consumption of the Internet since this is the primary communication medium of an IoT device. Estimating the electricity consumption of the Internet itself is a complex task. We performed a life cycle assessment (LCA) to determine the environmental impact of an intelligent smoke detector sold in Germany, taking its whole life-cycle from cradle-to-grave into account. We applied the impact assessment method ReCiPe 2016 Midpoint and compared its results with ILCD 2011 Midpoint+ to check the robustness of our results. The LCA results showed that electricity consumption during the use phase is the main contributor to environmental impacts. The mining of coal causes this contribution, which is a part of the German electricity mix. Consequently, the smoke detector mainly contributes to the impact categories of freshwater and marine ecotoxicity, but only marginally to global warming.
Purpose
The goal of this research survey was to propose an entrepreneurship education model for students in higher education institutions.
Methodology
A questionnaire was distributed to 246 randomly sampled students at the Universitas Negeri Jakarta. The data was analyzed through Structural Equation Modeling to study the variables of entrepreneurship education for higher education students and examine whether it can be predicted by the university leadership as a facilitator of entrepreneurial culture, university departments as promoters of entrepreneurial skills, and university research as an incubator of local business
development.
Findings
The results show that university leadership as a facilitator of entrepreneurial culture is supported by the university leadership’s fostering a culture of entrepreneurial thinking. It was also evident that the university placed sufficient emphasis on entrepreneurial education, and it successfully motivated lecturers to embrace entrepreneurship education, and students to embrace entrepreneurship education. The results also indicated that university departments acted as promoters of entrepreneurial skills and stimulated students to attain sufficient entrepreneurial skills during their university education. Lastly, the university research also proved as an incubator of local business development and was found influenced by the university conducting research projects with local
private sector businesses and supporting graduates planning to launch start-ups.
Implications to Research and Practice
The survey results will provide valuable policy insights to improve entrepreneurship education. The university faculty and students would have opportunities to gain practical experience in local private sector businesses. The model of entrepreneurship education proposed herein can be applied for higher education students.
In order to elaborate inflation and deflation tendencies due to the COVID-19 pandemic and how they are tried to be actively influenced, this paper compares news regarding the measurements of central banks in Europe, USA and Japan. Factors affecting inflation are defined in conjunction with the typical measurements of central banks and conclusions are drawn in respect to differences of the most recent correcting behavior. The paper is concluded by discussing how price levels might develop during and after the crisis.
CSR Pyramid
(2023)
Carroll, A.B.
(2023)
Bribery
(2023)
This article describes a research project that aims at investigating individual entrepreneurial founders concerning their shift tendencies of decision-making logics - especially during the respective phases of the venture creating process. Prior studies found that team founders show a hybrid perspective on strategic decision-making. They not only combine causation (planning-based) and effectuation (flexible) logics but also show logic shifts and also re-shifts over time. Due to the fact, that founders' social identity shapes early structuring processes, this article describes the necessity of elimination of in-group influences of multi-founding ventures and focus on individuals in order to make specific assessments on logic shifts and re-shifts. Based on an extensive literature review, a pre-selection-test and a qualitative case study design from the empirical body of the paper. Insofar, this study applies a qualitative design of a process research approach to investigate shifts of decision-making logics of individual founders in new venture creation over time.