Entrepreneurial orientation and the threat of imitation: the influence of upstream and downstream capabilities

This paper uncovers the complexity between Entrepreneurial Orientation (EO) and performance. The paper explores the effect of the threat of imitation, which is a key external factor to explain competitive dynamics, and hence highlights effectiveness of EO. Also the paper accounts for the role of upstream (technical) and downstream (marketing) capabilities as they influence effectiveness of EO. Our results show that, under threat of imitation, downstream marketing capabilities facilitate taping into opportunities derived from EO, which positively affects performance. Conversely, available upstream technical capabilities do not aim at EO when imitation threats exist in the environment. Of importance is that we question the complexity between EO and performance can be better understood using a configurational approach

Knowledge source preferences as determinants of strategic entrepreneurial orientation

In the knowledge intensive context, firms’ capacity to integrate external and internal sources of knowledge becomes an important competitive advantage and may distinguish entrepreneurial from conservative firms. This paper explores the proposition that differences in strategic entrepreneurial orientation (EO) across firms may be significantly determined by differences in firms’ preferences regarding knowledge sources. Our research is based on 208 firms operating in knowledge intensive industries in six Central and East European countries (CEEC). We identified three types of firms in terms of patterns of sources of knowledge: external R&D knowledge based firms, in-house knowledge based firms and value chain dependent firms. By using different proxies or different dimensions of EO, we have found that the EO is strongest in firms based on external knowledge. Firms with inhouse based knowledge have an intermediate strength of the EO, and firms dependent on value chains are the least entrepreneurially oriented. We have also found moderate support for grouping different proxies of EO into three dimensions identified in literature – innovativeness, pro-activeness and risk-taking. Value chain firms are not pro-active, have the lowest innovativeness, and are the most risk averse. External knowledge based firms are the most active in all three dimensions of EO, while inhouse knowledge based firms are in an intermediate position. Our results point to strong systemic features of entrepreneurial activities; i.e., EO is inherently different in different sub-populations of firms depending on their patterns of sources of knowledge. It seems that these patterns operate as a moderating factor between performance and the EO, which explains mixed results from the literature

Comments on EO 13126

EO_13126_Comments_FINAL_DOL_2011_0006.pdf: 226 downloads, before Oct. 1, 2020

Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

A latent class analysis of parental bipolar disorder: examining associations with offspring psychopathology

Bipolar disorder (BD) is highly heterogeneous, and course variations are associated with patient outcomes. This diagnostic complexity challenges identification of patients in greatest need of intervention. Additionally, course variations have implications for offspring risk. First, latent class analysis (LCA) categorized parents with BD based on salient illness characteristics: BD type, onset age, polarity of index episode, pole of majority of episodes, rapid cycling, psychosis, anxiety comorbidity, and substance dependence. Fit indices favored three parental classes with some substantively meaningful patterns. Two classes, labeled “Earlier-Onset Bipolar-I” (EO-I) and “Earlier-Onset Bipolar-II” (EO-II), comprised parents who had a mean onset age in mid-adolescence, with EO-I primarily BD-I parents and EO-II entirely BD-II parents. The third class, labeled “Later-Onset BD” (LO) had an average onset age in adulthood. Classes also varied on probability of anxiety comorbidity, substance dependence, psychosis, rapid cycling, and pole of majority of episodes. Second, we examined rates of disorders in offspring (ages 4–33, Mage=13.46) based on parental latent class membership. Differences emerged for offspring anxiety disorders only such that offspring of EO-I and EO-II parents had higher rates, compared to offspring of LO parents, particularly for daughters. Findings may enhance understanding of BD and its nosologyThis study was funded by two Brain & Behavior Research Foundation (formerly NARSAD) Independent Investigator Awards (PI: Nierenberg), a Brain & Behavior Research Foundation Young Investigator Award (PI: Henin) generously supported in part by the SHINE Initiative, and an MGH Claflin Award (PI: Henin). We thank David A. Langer, Ph.D., Thomas M. Olino, Ph.D., and Meredith Lotz Wallace, Ph.D. for their consultation. (Brain & Behavior Research Foundation; Brain & Behavior Research Foundation Young Investigator Award; SHINE Initiative; MGH Claflin Award)Accepted manuscrip

Ultra-High Electro-Optic Activity Demonstrated in a Silicon-Organic Hybrid (SOH) Modulator

Efficient electro-optic (EO) modulators crucially rely on advanced materials that exhibit strong electro-optic activity and that can be integrated into high-speed and efficient phase shifter structures. In this paper, we demonstrate ultra-high in-device EO figures of merit of up to n3r33 = 2300 pm/V achieved in a silicon-organic hybrid (SOH) Mach-Zehnder Modulator (MZM) using the EO chromophore JRD1. This is the highest material-related in-device EO figure of merit hitherto achieved in a high-speed modulator at any operating wavelength. The {\pi}-voltage of the 1.5 mm-long device amounts to 210 mV, leading to a voltage-length product of U{\pi}L = 320 V{\mu}m - the lowest value reported for MZM that are based on low-loss dielectric waveguides. The viability of the devices is demonstrated by generating high-quality on-off-keying (OOK) signals at 40 Gbit/s with Q factors in excess of 8 at a drive voltage as low as 140 mVpp. We expect that efficient high-speed EO modulators will not only have major impact in the field of optical communications, but will also open new avenues towards ultra-fast photonic-electronic signal processing.Comment: 9 pages, 4 figure