The concept of absorptive capacity has already been considerably studied from a theoretical perspective, but few, if any, attempts at operationalizing the concept have been studied in ways that would allow its full assessment. The more specific focus provided by the four dimensions identified in some recent literature -acquisition, assimilation, transformation and exploitation -opens up some promising avenues for operationalizing the concept. This exploratory research studies and describes case studies of ten innovative companies using a cross-sectional research design. In the first part of the article, we re-examine the concept of absorptive capacity in terms of dynamic capabilities and provide a review of the relevant literature. The second part describes the work accomplished to operationalize the concept of dynamic capability and analyses the possible relationship between the business strategies adopted by the companies studied and their particular strategic capacity.

This questionnaire study of both partners from 162 romantic and marital relationships sought to examine perceived partner maintenance strategies as correlates of participant satisfaction for relationships at varying dialectical moments of the autonomy-connection, predictability-novelty and openness-closedness contradictions. The perceived partner maintenance strategies of contact, romance and avoidance varied in efficacy depending on the particular dialectical conditions of the relationship, especially among male participants.

Abstract-In this paper, the problem of joint Carrier Frequency Offset (CFO) and channel estimation for OFDM systems over the fast time-varying frequency-selective channel is explored within the framework of the expectation-maximization (EM) algorithm and parametric channel model. Assuming that the path delays are known, a novel iterative pilot-aided algorithm for joint estimation of the multi-path Rayleigh channel Complex Gains (CG) and the Carrier Frequency Offset (CFO) is introduced. Each CG time-variation, within one OFDM symbol, is approximated by a Basis Expansion Model (BEM) representation. An auto-regressive (AR) model is built to statistically characterize the variations of the BEM coefficients across the OFDM blocks.In addition to the algorithm, the derivation of the Hybrid Cramér-Rao Bound (HCRB) for CFO and CGs estimation in our context of very high mobility is provided. We show that the proposed EM has a lower computational complexity than the optimum maximum a posteriori estimator and yet incurs only an insignificant loss in performance.

International audienceThis article argues that entrepreneurial learning is genuinely connected to entrepreneurial networking activities, within a co-evolving dynamics. We take a longitudinal network approach to study the combined development of network dynamics and learning in a French formal entrepreneurial network over a period of four years (2005-2009). Our aim is to extend our knowledge of entrepreneurial learning emphasised both as a process and an outcome of social interaction, by focussing on the interplay between network evolution and the changing learning needs of participants over time. Building on a situated social perspective of entrepreneurial learning, we demonstrate that network learning processes and outcomes are contingent on the progressive network transformation from a social network to a community of practice

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1 In this paper, a novel pilot-aided algorithm is developed for MIMO-OFDM systems operating in fast timevarying environment. The algorithm has been designed to work both with parametric L-path channel model (with known path delays) and equivalent discrete-time channel model to jointly estimate the multi-path Rayleigh channel complex amplitudes (CA) and Carrier Frequency Offset (CFO). Each CA timevariation within one OFDM symbol is approximated by a Basis Expansion Model (BEM) representation. An Auto-Regressive (AR) model is built for the parameters to be estimated. The algorithm performs estimation using Extended Kalman Filtering. The channel matrix is thus easily computed and the data symbol is estimated without Inter-sub-Carrier-Interference (ICI) when the channel matrix is QR-decomposed. It is shown that our algorithm is far more robust to high speed than the conventional algorithm, and the performance approaches that of the ideal case for which the channel response and CFO are known. . His main research interests are in mobile communications and carrier and symbol synchronization.Laurent Ros received the degree in electrical engineering from the "Ecole Supérieure d'Electricité" (Supélec), Paris, France, in 1992 and the Ph.D. degree in signal processing and communications from Grenoble Institute of Technology (Grenoble-INP), Grenoble, France, in 2001. From 1993to 1995 he was with France-Telecom R&D center, Lannion, France, where he worked in the area of very low frequency transmissions for submarine applications, in collaboration with Direction of Naval Construction, Toulon, France. From 1995 to 1999, he was a Research and Development team manager at Sodielec, Millau, France, where he worked in the design of digital modems and audio codecs for telecommunication applications. Since 1999, he has joined the Gipsalaboratory/DIS (ex "Laboratory of Image and Signal") and Grenoble-INP where he is currently an Associate Professor. His general research interests include statistical signal processing, synchronization and channel estimation problems for wireless communications.

This paper deals with channel estimation for Orthogonal Frequency Division Multiplexing (OFDM) systems over time-varying fading channels. In conventional methods, the leastsquares (LS) estimate is obtained over the pilot subcarriers, and next interpolated over the entire frequency grid. Those methods only exploit the frequency-domain correlation of the channel. In this paper, we propose to exploit both the time-domain correlation and the specific features of the wireless radio channel. Assuming the availability of delay related information, we propose to track the variation of the paths complex amplitudes by means of online recursive algorithms. We developed two simple sub-optimal algorithms based on second-order loops which exhibit a reduced complexity compared to that of the widely popular Kalman algorithm. The error signal is based on the LS estimate of the path complex gains for the first loop, and on the steepest-descent method of the same LS cost function for the second loop. For each algorithm, we give derivations to correctly tune the loop coefficients. Simulation results over slow Rayleigh fading channel with Jakes' spectrum show that our algorithms outperform the conventional methods. Moreover, the Mean Square Error (MSE) of the first algorithm is closer to the Bayesian Cramer Rao Bound than that of a Kalman filter based on a first-order AutoRegressive approximation of the channel.