A firm’s organizational innovation and organizational learning abilities

Many recent studies are dedicated to the problem of innovation as a mean of improving a firm’s overall performance. Various kinds of innovation in a firm usually are closely interrelated with each other. While the majority of studies focus on technological - product and process - innovation, the investigation of non-technological - marketing and organizational - innovation (ORI), has increasingly attracted the interest of researchers during the last decade. Organizational culture and organizational learning are important drivers of such innovation. For instance, a collaborative culture, trust and open-mindedness encourage new initiatives and ideas, while learning helps not just to improve skillsets and abilities of individual employees, but can also greatly contribute to strategic knowledge management and building a resilient, innovative organization. This study examines the relationship between a firm’s organizational learning ability and its organizational innovation performance. The authors consider such factors as Learning Intention – seeing learning as a key investment and organizational commitment to it, and Openness - open-mindedness and organizational culture open to new ideas and worldviews. This study contributes to the theory of ORI by finding the answer to the question what impact these factors could have on ORI development in a firm. The findings are based on a quantitative analysis of more than 150 small and medium-sized enterprises surveyed in Russia and Latvia. The survey questions measuring ORI performance were developed in line with the widely used definition introduced in the OECD - Eurostat Oslo Manual. The scales for organizational learning were adopted from the previous studies elaborated this area of a firm activity. The survey compared a firm’s innovation performance to that of its closest competitors. This research demonstrates that some of the elements of organizational learning positively influence ORI activity. The results also suggest that Latvian companies differ from Russian ones in terms of their organizational learning intention

EC-Earth3-AerChem : a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6

This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average 0.09 Wm(-2) with a standard deviation due to interannual variability of 0.25 Wm(-2), showing no significant drift. The global surface air temperature in the simulation is on average 14.08 degrees C with an interannual standard deviation of 0.17 degrees C, exhibiting a small drift of 0.015 +/- 0.005 degrees C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9 degrees C, and its transient climate response is estimated at 2.1 degrees C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995-2014 has an average bias of -0.86 +/- 0.05 degrees C with a standard deviation across ensemble members of 0.35 degrees C in the North-ern Hemisphere and 1.29 +/- 0.02 degrees C with a corresponding standard deviation of 0.05 degrees C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091-2100) of 4.9 degrees C above the preindustrial mean. A 0.5 degrees C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5 degrees C.Peer reviewe

EC-Earth3-AerChem: a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6

This paper documents the global climate model EC-Earth3-AerChem, one of the members of the EC-Earth3 family of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). EC-Earth3-AerChem has interactive aerosols and atmospheric chemistry and contributes to the Aerosols and Chemistry Model Intercomparison Project (AerChemMIP). In this paper, we give an overview of the model, describe in detail how it differs from the other EC-Earth3 configurations, and outline the new features compared with the previously documented version of the model (EC-Earth 2.4). We explain how the model was tuned and spun up under preindustrial conditions and characterize the model's general performance on the basis of a selection of coupled simulations conducted for CMIP6. The net energy imbalance at the top of the atmosphere in the preindustrial control simulation is on average −0.09 W m−2 with a standard deviation due to interannual variability of 0.25 W m−2, showing no significant drift. The global surface air temperature in the simulation is on average 14.08 ∘C with an interannual standard deviation of 0.17 ∘C, exhibiting a small drift of 0.015 ± 0.005 ∘C per century. The model's effective equilibrium climate sensitivity is estimated at 3.9 ∘C, and its transient climate response is estimated at 2.1 ∘C. The CMIP6 historical simulation displays spurious interdecadal variability in Northern Hemisphere temperatures, resulting in a large spread across ensemble members and a tendency to underestimate observed annual surface temperature anomalies from the early 20th century onwards. The observed warming of the Southern Hemisphere is well reproduced by the model. Compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis version 5 (ERA5), the surface air temperature climatology for 1995–2014 has an average bias of −0.86 ± 0.05 ∘C with a standard deviation across ensemble members of 0.35 ∘C in the Northern Hemisphere and 1.29 ± 0.02 ∘C with a corresponding standard deviation of 0.05 ∘C in the Southern Hemisphere. The Southern Hemisphere warm bias is largely caused by errors in shortwave cloud radiative effects over the Southern Ocean, a deficiency of many climate models. Changes in the emissions of near-term climate forcers (NTCFs) have significant effects on the global climate from the second half of the 20th century onwards. For the SSP3-7.0 Shared Socioeconomic Pathway, the model gives a global warming at the end of the 21st century (2091–2100) of 4.9 ∘C above the preindustrial mean. A 0.5 ∘C stronger warming is obtained for the AerChemMIP scenario with reduced emissions of NTCFs. With concurrent reductions of future methane concentrations, the warming is projected to be reduced by 0.5 ∘C

Laadullinen tapaustutkimus opetusresurssien nopean ja voimakkaan vähenemisen vaikutuksista korkeakouluopetukseen

Tässä tapaustutkimuksessa perehdytään opetusresurssien nopean ja voimakkaan vähenemisen vaikutuksiin korkeakouluopetuksen laatuun. Yliopistojen ja ammattikorkeakoulujen rahoitusta vähennettiin merkittävästi vuosina 2015-2016, jolloin tämän tutkimuksen haastatteluaineisto on kerätty. Tämä tutkimus on toteutettu laadullisena haastattelututkimuksena ja tulokset on analysoitu Gioian menetelmällä. Menetelmän valinnalla on tarkoitus tavoitella laadullisesta aineistosta tehtyjen päätelmien parempaa jäljitettävyyttä. Haastateltavia oli 15, joista 5 työskenteli Saimaan ammattikorkeakoulussa ja 10 Lappeenrannan teknillisessä yliopistossa. Tutkimustulosten perusteella resurssien väheneminen näkyy ensisijaisesti opetustarjonnan suppenemisena. Opetuksen digitalisaatiolle asetetaan odotuksia niin organisaation kuin opettajienkin keskuudessa, mutta toistaiseksi haastatellut suosivat perinteisiä opetusmenetelmiä. Resurssien riittävyydestä ollaan huolissaan, mutta toisaalta opettajakunnan odotukset laadun paranemisen suhteen vaikuttavat olevan vahvoja. Tämän ristiriidan seurauksena on mahdollista, että osa resurssien vähenemisen seurauksista näkyy viiveellä opetushenkilökunnan jaksamisongelmina