Last 7 days
![]() ; Fisch, Christian ![]() in International Review of Entrepreneurship (2021), 19(2), 151-168 The COVID-19 pandemic has immense impact on the conditions and behaviours of people and on those of small business owners in particular. Using two samples of some 3700 French business owners, collected ... [more ▼] The COVID-19 pandemic has immense impact on the conditions and behaviours of people and on those of small business owners in particular. Using two samples of some 3700 French business owners, collected before and during the pandemic, this study finds that on average, health perceptions in terms of physical and mental health differ: while perceptions of good mental health declined, those of good physical health improved. We also find that the size of business and the growth of turnover are mechanisms that contributed to the decline of the total health score. This novel finding implies that during the pandemic, business size and growth of turnover are seen as liabilities rather than assets by business owners. The results of our study have strong implications both for business owners as well as for policy makers. [less ▲] Detailed reference viewed: 32 (1 UL)![]() Fisch, Christian ![]() in Journal of Business Research (2021), 125(3), 564-576 Research on initial coin offerings (ICOs) is nascent and assesses ICOs from the perspectives of ventures and regulators. Little is known about the equally important group of investors who provide their ... [more ▼] Research on initial coin offerings (ICOs) is nascent and assesses ICOs from the perspectives of ventures and regulators. Little is known about the equally important group of investors who provide their capital to ventures in ICOs. Using a primary dataset of 517 ICO investors, we identify and categorize the motivations to invest in ICOs using factor analysis. We find that investors are driven by ideological, technological, and financial motives. Regarding the relative importance of the motives, we find that technological motives are the most important motives to ICO investors, followed by financial and ideological motives. To further profile investors, we conduct a regression analysis to distinguish investors across different motives. For example, we show significant differences across motives with regard to investors' risk perception, sources of information, and demand for strict regulation. The implications of this study for both theory and practice are considerable. [less ▲] Detailed reference viewed: 39 (1 UL)![]() Fisch, Christian ![]() in Journal of Business Venturing Insights (2021), 16 We examine the association between several behavioral and electrophysiological indices of impulsivity-related constructs and multiple entrepreneurial constructs. Specifically, we investigate if these ... [more ▼] We examine the association between several behavioral and electrophysiological indices of impulsivity-related constructs and multiple entrepreneurial constructs. Specifically, we investigate if these behavioral and electrophysiological measures are more useful as predictors of entrepreneurship than self-reported measures of impulsivity. Our findings are based on two datasets (n = 133 and n = 142) and indicate that behavioral and electrophysiological impulsivity measures are not robustly associated with entrepreneurship constructs, in contrast to selfreported measures of impulsivity. Though disappointing at first, our findings pave the way for future research on the relevance of behavioral and electrophysiological measures for entrepreneurship. [less ▲] Detailed reference viewed: 31 (1 UL)![]() ; ; Fisch, Christian ![]() in Entrepreneurship: Theory and Practice (2021), 45(6), 1522-1549 We investigate how individual factors moderate the impact of bankruptcy exemption levels—that is, the amount of wealth individuals can keep in case of bankruptcy—on entry into self-employment ... [more ▼] We investigate how individual factors moderate the impact of bankruptcy exemption levels—that is, the amount of wealth individuals can keep in case of bankruptcy—on entry into self-employment. Conceptually, we combine Prospect Theory’s axiom of diminishing sensitivity with insights from research on entrepreneurial failure. We hypothesize that individuals who face higher financial, social, or psychological costs because of bankruptcy will be less sensitive to higher exemption levels than will those who face lower costs across these dimensions. Our empirical results, which are based on a quasi-natural experiment in the United States, support our theoretical predictions. [less ▲] Detailed reference viewed: 39 (1 UL)![]() ; ; et al in International Journal of Innovation and Technology Management (2021), 18(2), 2002001 Detailed reference viewed: 34 (1 UL)![]() ; Fisch, Christian ![]() in Journal of Business Venturing Insights (2021), 15(6), 00213 Initial coin offerings (ICOs) represent an innovative and new funding mechanism for new technology ventures. In our comprehensive review of the industry’s evolution, we show that despite its short history ... [more ▼] Initial coin offerings (ICOs) represent an innovative and new funding mechanism for new technology ventures. In our comprehensive review of the industry’s evolution, we show that despite its short history, there have been dramatic changes and shifts in the number of ICOs, the amount of money raised, the geographic distribution of ICOs, and their regulation. This dynamism calls into question current research practices and findings. We propose that scholars sort out and differentiate supply of vs. demand for ICO funding, taking geography and regulation into account with a global perspective. [less ▲] Detailed reference viewed: 51 (3 UL)![]() ; Fisch, Christian ![]() in Industry and Innovation (2021), 28(6), 704-724 Building on organisational failure learning and upper echelons theory, we examine the link between top management team (TMT) prior experiences and invention failure learning among research organisations ... [more ▼] Building on organisational failure learning and upper echelons theory, we examine the link between top management team (TMT) prior experiences and invention failure learning among research organisations. Specifically, we develop theoretical arguments to suggest that TMT founding experience and exposure to US culture facilitate organisational learning from failure. We test our theoretical reasoning using a longitudinal data set comprising 550 organisation-year observations of the patenting activities conducted by 39 research institutes in Germany. In support of our theoretical arguments, we find that TMT founding experience and TMT exposure to US culture positively moderate the link between prior invention failure and subsequent invention performance. Pointing to TMT experiences as a crucial contingency for whether organisations learn from failure, the present study contributes to the literature on organisational failure learning and upper echelons. [less ▲] Detailed reference viewed: 30 (1 UL)![]() Fisch, Christian ![]() in Journal of Business Venturing (2021), 36(1), 106015 We assess whether and how entrepreneurs' digital identities change in response to entrepreneurial failure based on a sample of 760 entrepreneurs who experienced failure. We analyze a longitudinal dataset ... [more ▼] We assess whether and how entrepreneurs' digital identities change in response to entrepreneurial failure based on a sample of 760 entrepreneurs who experienced failure. We analyze a longitudinal dataset of Twitter messages before, during, and after a business failure with a language-based method of computerized text analysis. The results of our explorative research indicate that the financial, social, and psychological consequences of failure are reflected in entrepreneurs' Tweets and lead to changes in their digital identities. Among others, entrepreneurs' language decreases in emotional tone and indicates increased psychological distress. Simultaneously, we observe higher levels of self-assurance and reflection after failure. We conclude by outlining the potential of using Twitter-generated digital footprints in future entrepreneurship research. [less ▲] Detailed reference viewed: 38 (1 UL)![]() Mathivanan, Karthik ![]() ![]() in Procedia CIRP (2021) Laser welding of copper to aluminum is challenging due to the formation of complex intermetallic phases. More Al (~18.5 at. %) can be dissolved in Cu, in contrast to Cu (~2.5 at. %) in Al. Therefore ... [more ▼] Laser welding of copper to aluminum is challenging due to the formation of complex intermetallic phases. More Al (~18.5 at. %) can be dissolved in Cu, in contrast to Cu (~2.5 at. %) in Al. Therefore, welding from copper side, large melting of Al can be achieved. However optimum Cu and Al must be melted for a strong joint. Finding the right amount is difficult and time consuming by tradition analysis technique like inspection by weld cross-sections. Considering the speed of the welding process and complexity of analysis involving with metallography cross-sections, alternative rapid method to qualify the welds are necessary. The acoustic emission during laser welding can give proportional information of the Al, Cu melted. With such an approach the weld status can be obtained in real time. In this paper the acoustic welding signal using an airborne sensor in the audible range of 20 Hz to 20 kHz, is correlated to the weld strength and material mixing (Al, Cu melt). Finally, the weld status is predicted by an artificial neural network based on the acquired signal. [less ▲] Detailed reference viewed: 56 (3 UL)![]() ; ; Rupp, Andy ![]() in Advances in Cryptology - ASIACRYPT 2021 - 27th International Conference on the Theory and Application of Cryptology and Information Security Singapore, December 6-10, 2021, Proceedings, Part II (2021) Detailed reference viewed: 37 (11 UL)![]() Solchenbach, Karl ![]() in e-Perimetron (2021) The planimetric accuracy of old maps can be calculated using cartometric methods like Helmert transformations. As the choice of control points for these transformations is somewhat arbitrary, this may ... [more ▼] The planimetric accuracy of old maps can be calculated using cartometric methods like Helmert transformations. As the choice of control points for these transformations is somewhat arbitrary, this may cause stochastic variations in the results. This paper addresses these stochastic variations and proposes to apply Bayesian data analysis methods to quantify the uncertainty of the cartometric calculations. The paper shows that the Bayesian data analysis is consistent with the deterministic calculations, and it provides safe statistical bounds for the results. [less ▲] Detailed reference viewed: 34 (1 UL)![]() ; ; et al in IEEE Transactions on Robotics (2021), 37(6), 2226-2233 We present a distributed framework for predicting whether a planned reconfiguration step of a modular robot will mechanically overload the structure, causing it to break or lose stability under its own ... [more ▼] We present a distributed framework for predicting whether a planned reconfiguration step of a modular robot will mechanically overload the structure, causing it to break or lose stability under its own weight. The algorithm is executed by the modular robot itself and based on a distributed iterative solution of mechanical equilibrium equations derived from a simplified model of the robot. The model treats intermodular connections as beams and assumes no-sliding contact between the modules and the ground. We also provide a procedure for simplified instability detection. The algorithm is verified in the Programmable Matter simulator VisibleSim, and in real-life experiments on the modular robotic system Blinky Blocks. © 2004-2012 IEEE. [less ▲] Detailed reference viewed: 52 (2 UL)![]() ; ; et al in The Proceedings of the Data Science and Advanced Analytics (DSAA 2021) IEEE conference (2021) The dark face of digital commerce generalization is the increase of fraud attempts. To prevent any type of attacks, state-of-the-art fraud detection systems are now embedding Machine Learning (ML) modules ... [more ▼] The dark face of digital commerce generalization is the increase of fraud attempts. To prevent any type of attacks, state-of-the-art fraud detection systems are now embedding Machine Learning (ML) modules. The conception of such modules is only communicated at the level of research and papers mostly focus on results for isolated benchmark datasets and metrics. But research is only a part of the journey, preceded by the right formulation of the business problem and collection of data, and followed by a practical integration. In this paper, we give a wider vision of the process, on a case study of transfer learning for fraud detection, from business to research, and back to business. [less ▲] Detailed reference viewed: 25 (1 UL)![]() Lebichot, Bertrand ![]() in nternational Journal of Data Science and Analytics (2021) very second, thousands of credit or debit card transactions are processed in financial institutions. This extensive amount of data and its sequential nature make the problem of fraud detection ... [more ▼] very second, thousands of credit or debit card transactions are processed in financial institutions. This extensive amount of data and its sequential nature make the problem of fraud detection particularly challenging. Most analytical strategies used in production are still based on batch learning, which is inadequate for two reasons: Models quickly become outdated and require sensitive data storage. The evolving nature of bank fraud enshrines the importance of having up-to-date models, and sensitive data retention makes companies vulnerable to infringements of the European General Data Protection Regulation. For these reasons, evaluating incremental learning strategies is recommended. This paper designs and evaluates incremental learning solutions for real-world fraud detection systems. The aim is to demonstrate the competitiveness of incremental learning over conventional batch approaches and, consequently, improve its accuracy employing ensemble learning, diversity and transfer learning. An experimental analysis is conducted on a full-scale case study including five months of e-commerce transactions and made available by our industry partner, Worldline. [less ▲] Detailed reference viewed: 62 (1 UL)![]() Toulouse, Constance ![]() in Physical Review Materials (2021), 5(2), 024404 Helium implantation in epitaxial thin films is a way to control the out-of-plane deformation independently from the in-plane strain controlled by epitaxy. In particular, implantation by means of a helium ... [more ▼] Helium implantation in epitaxial thin films is a way to control the out-of-plane deformation independently from the in-plane strain controlled by epitaxy. In particular, implantation by means of a helium microscope allows for local implantation and patterning down to the nanometer resolution, which is of interest for device applications. We present here a study of bismuth ferrite (BiFeO3) films where strain was patterned locally by helium implantation. Our combined Raman, x-ray diffraction, and transmission electron microscopy (TEM) study shows that the implantation causes an elongation of the BiFeO3 unit cell and ultimately a transition towards the so-called supertetragonal polymorph via states with mixed phases. In addition, TEM reveals the onset of amorphization at a threshold dose that does not seem to impede the overall increase in tetragonality. The phase transition from the R-like to T-like BiFeO3 appears as first-order in character, with regions of phase coexistence and abrupt changes in lattice parameters. [less ▲] Detailed reference viewed: 51 (6 UL)![]() Lebichot, Bertrand ![]() in IEEE Access (2021) Credit card fraud jeopardizes the trust of customers in e-commerce transactions. This led in recent years to major advances in the design of automatic Fraud Detection Systems (FDS) able to detect ... [more ▼] Credit card fraud jeopardizes the trust of customers in e-commerce transactions. This led in recent years to major advances in the design of automatic Fraud Detection Systems (FDS) able to detect fraudulent transactions with short reaction time and high precision. Nevertheless, the heterogeneous nature of the fraud behavior makes it difficult to tailor existing systems to different contexts (e.g. new payment systems, different countries and/or population segments). Given the high cost (research, prototype development, and implementation in production) of designing data-driven FDSs, it is crucial for transactional companies to define procedures able to adapt existing pipelines to new challenges. From an AI/machine learning perspective, this is known as the problem of transfer learning. This paper discusses the design and implementation of transfer learning approaches for e-commerce credit card fraud detection and their assessment in a real setting. The case study, based on a six-month dataset (more than 200 million e-commerce transactions) provided by the industrial partner, relates to the transfer of detection models developed for a European country to another country. In particular, we present and discuss 15 transfer learning techniques (ranging from naive baselines to state-of-the-art and new approaches), making a critical and quantitative comparison in terms of precision for different transfer scenarios. Our contributions are twofold: (i) we show that the accuracy of many transfer methods is strongly dependent on the number of labeled samples in the target domain and (ii) we propose an ensemble solution to this problem based on self-supervised and semi-supervised domain adaptation classifiers. The thorough experimental assessment shows that this solution is both highly accurate and hardly sensitive to the number of labeled samples. [less ▲] Detailed reference viewed: 34 (2 UL)![]() Hertweck, Florian ![]() in FACES Journal d'architecture (2021), 79 Detailed reference viewed: 40 (1 UL)![]() Trinh, van Chien ![]() ![]() in IEEE Transactions on Wireless Communications (2021) Massive multiple-input multiple-output (MIMO) is a key technology for improving the spectral and energy efficiency in 5G-and-beyond wireless networks. For a tractable analysis, most of the previous works ... [more ▼] Massive multiple-input multiple-output (MIMO) is a key technology for improving the spectral and energy efficiency in 5G-and-beyond wireless networks. For a tractable analysis, most of the previous works on Massive MIMO have been focused on the system performance with complex Gaussian channel impulse responses under rich-scattering environments. In contrast, this paper investigates the uplink ergodic spectral efficiency (SE) of each user under the double scattering channel model. We derive a closed-form expression of the uplink ergodic SE by exploiting the maximum ratio (MR) combining technique based on imperfect channel state information. We further study the asymptotic SE behaviors as a function of the number of antennas at each base station (BS) and the number of scatterers available at each radio channel. We then formulate and solve a total energy optimization problem for the uplink data transmission that aims at simultaneously satisfying the required SEs from all the users with limited data power resource. Notably, our proposed algorithms can cope with the congestion issue appearing when at least one user is served by lower SE than requested. Numerical results illustrate the effectiveness of the closed-form ergodic SE over Monte-Carlo simulations. Besides, the system can still provide the required SEs to many users even under congestion. [less ▲] Detailed reference viewed: 126 (4 UL)![]() ; ; et al in Journal of clinical medicine (2021), 10(10), Asymptomatic individuals, called "silent spreaders" spread SARS-CoV-2 efficiently and have complicated control of the ongoing COVID-19 pandemic. As seen in previous influenza pandemics, socioeconomic and ... [more ▼] Asymptomatic individuals, called "silent spreaders" spread SARS-CoV-2 efficiently and have complicated control of the ongoing COVID-19 pandemic. As seen in previous influenza pandemics, socioeconomic and life-trajectory factors are important in disease progression and outcome. The demographics of the asymptomatic SARS-CoV-2 carriers are unknown. We used the CON-VINCE cohort of healthy, asymptomatic, and oligosymptomatic individuals that is statistically representative of the overall population of Luxembourg for age, gender, and residency to characterise this population. Gender (male), not smoking, and exposure to early-life or adult traumatic experiences increased the risk of IgA seropositivity, and the risk associated with early-life exposure was a dose-dependent metric, while some other known comorbidities of active COVID-19 do not impact it. As prior exposure to adversity is associated with negative psychobiological reactions to external stressors, we recorded psychological wellbeing during the study period. Exposure to traumatic events or concurrent autoimmune or rheumatic disease were associated with a worse evolution of anxiety and depressive symptoms throughout the lockdown period. The unique demographic profile of the "silent spreaders" highlights the role that the early-life period plays in determining our lifelong health trajectory and provides evidence that the developmental origins of health and disease is applicable to infectious diseases. [less ▲] Detailed reference viewed: 46 (6 UL)![]() ; ; et al in IEEE Consumer Electronics Magazine (2021) Securing edge computing has drawn much attention due to the vital role of edge computing in Fifth Generation (5G) wireless networks. Artificial Intelligence (AI) has been adopted to protect networks ... [more ▼] Securing edge computing has drawn much attention due to the vital role of edge computing in Fifth Generation (5G) wireless networks. Artificial Intelligence (AI) has been adopted to protect networks against attackers targeting the connected edge devices or the wireless channel. However, the proposed detection mechanisms could generate a high false detection rate, especially against unknown attacks defined as zero-day threats. Thereby, we propose and conceive a new hybrid learning security framework that combines the expertise of security experts and the strength of machine learning to protect the edge computing network from known and unknown attacks, while minimizing the false detection rate. Moreover, to further decrease the number of false detections, a cyber security mechanism based on a Stackelberg game is used by the hybrid learning security engine (activated at each edge server) to assess the detection decisions provided by the neighboring security engines. [less ▲] Detailed reference viewed: 50 (2 UL) |
||