The nature and prevalence of inter-organizational project ventures : evidence from a large scale field study in the Netherlands 2006-2009

There has recently been noted a rapid increase in research attention to projects that involve outside partners. Our knowledge of such inter-organizational projects, however, is limited. This paper reports large scale data from a repeated trend survey amongst 2000 SMEs in 2006 and 2009 that focused on inter-organizational project ventures. Our major findings indicate that the overall prevalence of inter-organizational project ventures remained significant and stable over time, even despite the economic crisis. Moreover, we find that these ventures predominantly solve repetitive rather than unique tasks and are embedded in prior relations between the partnering organizations. These findings provide empirical support for the recent claims that project management should pay more attention to inter-organizational forms of project organization, and suggest that the archetypical view of projects as being unique in every respect should be reconsidered. Both have important implications for project management, especially in the area of project-based learning.

Alternative modes of entrepreneurial opportunity exploitation : the case on inter-organizational project

While entrepreneurship research has taken firm formation to be the predominant mode of opportunity exploitation, entrepreneurship can take place through many other types of organizational arrangements. In the present article, we consider one such alternative arrangement, namely the formation of inter-organizational projects (IOPs). We propose a multi-level contingency model that suggests that uncertainty both at the level of the firm and at the level of the environment makes the exploitation of opportunities through IOPs more likely. The model is tested by telephone survey data collected amongst a panel of 1725 SMEs and longitudinal industry data. Our findings provide strong support for the industry-level part of the model, but interestingly, only partial support for the firm level part of the model. This indicates that the effects of uncertainty need to be dissected into different levels of analysis to understand the conditions under which alternative modes of opportunity exploitation can be a prominent entrepreneurial alternative to new firm formation.

Collaborative enterprise governance : sustainable management of inter-firm R&D relationships in the German car industry

This research reports on the appropriate governance, i.e. design and management, of inter-firm R&D relationships in order to achieve sustainable competitive success for the whole partnership as well as its individual members. An exploratory study in the German automotive industry using inductive Grounded Theory was conducted. This involved data collection via 28 semi-structured interviews with 16 companies in order to form a set of 35 tentative propositions that have been validated via a questionnaire survey receiving 110 responses from 52 companies. The research has resulted in the consolidation of the validated propositions into a novel concept termed Collaborative Enterprise Governance. The core of the concept is a competence based contingency framework that helps decision makers in selecting the most appropriate governance strategy (i.e. sourcing strategy) for an inter-firm R&D relationship between a buyer and its supplier. Thereby, the concept does not draw on whole company-to-company connectivity. It rather conceptualises an inter-firm relationship to be composed of autonomous cross-functional units of the individual partner companies that contribute value to a particular joint R&D project via the possession of task specific competencies. The novel concept and its elements have been evaluated in a focus group with industrial experts of the German automotive industry and revealed positive effects on the sustainable competitive success of the whole partnership and the individual partner companies. However, it also showed that current practice does not apply the right mechanisms for its implementation and hence guidelines for practitioners and decision makers involved in inter-firm R&D collaboration in the automotive industry are offered on how to facilitate the implementation and usage of the Collaborative Enterprise Governance philosophy.

The critical competences needed for innovative organizational inter-firm and intra-firm integration

In today's highly challenging business environment, an innovative and systemic approach is imperative to survival and growth. Organisational integration and technological integration, are often seen as a catalyst of change that could lead to significant improvements in organisations. The levels of improvement in inter and intra firm integration should arise from a detailed understanding and development of competences within and between organisations. Preliminary findings suggest that lack of trust across organisational cultures within the firms has a negative influence on the development of the capabilities to integrate and align technological innovations and hinders implementation and the effectiveness of the operations. Additionally, poor communication and conflict effects customer satisfaction. Firms need to transfer the competences that support cooperative integration, developed through interaction with supply chain partners, to their relationship arrangements with other supply chain partners, as these are key to ensuring low operational costs.

An Econometric Analysis of Inter-Firm Labour Mobility

This paper utilizes the Survey of Work History (1981) data to examine the importance of non-random sampling in the context of a model of interfirm labour mobility. The paper adopts Heckman's two-step procedure in order to estimate a three-equation model incorporating an individual's mobility status as endogenously determined. The main conclusion is that in estimating wage equations it is important to consider the role of job mobility and to correct for the effects of sample-selection bias. The results generally accord with those reported by Osberg et al. (1986) in the only previous Canadian study of job mobility in a sample-selection context.

A Model for Creating Strategic Alliances. A Study of Inter-firm Cooperation in the North European ICT Sector

In this study, it is argued that the view on alliance creation presented in the current academic literature is limited, and that using a learning approach helps to explain the dynamic nature of alliance creation. The cases in this study suggest that a wealth of inefficiency elements can be found in alliance creation. These elements can further be divided into categories, which help explain the dynamics of alliance creation. The categories –combined with two models brought forward by the study– suggest that inefficiency can be avoided through learning during the creation process. Some elements are especially central to this argumentation. First, the elements related to the clarity and acceptance of the strategy of the company, the potential lack of an alliance strategy and the elements related to changes in the strategic context. Second, the elements related to the length of the alliance creation processes and the problems a long process entails. It is further suggested that the different inefficiency elements may create a situation, where the alliance creation process is –sequentially and successfully– followed to the end, but where the different inefficiencies create a situation where the results are not aligned with the strategic intent. The proposed solution is to monitor and assess the risk for inefficiency elements during the alliance creation process. The learning, which occurs during the alliance creation process as a result of the monitoring, can then lead to realignments in the process. This study proposes a model to mitigate the risk related to the inefficiencies. The model emphasizes creating an understanding of the other alliance partner’s business, creating a shared vision, using pilot cooperation and building trust within the process. An analytical approach to assessing the benefits of trust is also central in this view. The alliance creation approach suggested by this study, which emphasizes trust and pilot cooperation, is further critically reviewed against contracting as a way to create alliances.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

An assessment of upper ocean salinity content from the ocean reanalyses inter-comparison project (ORA-IP)

Many institutions worldwide have developed ocean reanalyses systems (ORAs) utilizing a variety of ocean models and assimilation techniques. However, the quality of salinity reanalyses arising from the various ORAs has not yet been comprehensively assessed. In this study, we assess the upper ocean salinity content (depth-averaged over 0–700 m) from 14 ORAs and 3 objective ocean analysis systems (OOAs) as part of the Ocean Reanalyses Intercomparison Project. Our results show that the best agreement between estimates of salinity from different ORAs is obtained in the tropical Pacific, likely due to relatively abundant atmospheric and oceanic observations in this region. The largest disagreement in salinity reanalyses is in the Southern Ocean along the Antarctic circumpolar current as a consequence of the sparseness of both atmospheric and oceanic observations in this region. The West Pacific warm pool is the largest region where the signal to noise ratio of reanalysed salinity anomalies is >1. Therefore, the current salinity reanalyses in the tropical Pacific Ocean may be more reliable than those in the Southern Ocean and regions along the western boundary currents. Moreover, we found that the assimilation of salinity in ocean regions with relatively strong ocean fronts is still a common problem as seen in most ORAs. The impact of the Argo data on the salinity reanalyses is visible, especially within the upper 500m, where the interannual variability is large. The increasing trend in global-averaged salinity anomalies can only be found within the top 0–300m layer, but with quite large diversity among different ORAs. Beneath the 300m depth, the global-averaged salinity anomalies from most ORAs switch their trends from a slightly growing trend before 2002 to a decreasing trend after 2002. The rapid switch in the trend is most likely an artefact of the dramatic change in the observing system due to the implementation of Argo.