19,241 research outputs found

    Investigating the impact of networking capability on firm innovation performance:using the resource-action-performance framework

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    The author's final peer reviewed version can be found by following the URI link. The Publisher's final version can be found by following the DOI link.Purpose The experience of successful firms has proven that one of the most important ways to promote co-learning and create successful networked innovations is the proper application of inter-organizational knowledge mechanisms. This study aims to use a resource-action-performance framework to open the black box on the relationship between networking capability and innovation performance. The research population embraces companies in the Iranian automotive industry. Design/methodology/approach Due to the latent nature of the variables studied, the required data are collected through a web-based cross-sectional survey. First, the content validity of the measurement tool is evaluated by experts. Then, a pre-test is conducted to assess the reliability of the measurement tool. All data are gathered by the Iranian Vehicle Manufacturers Association (IVMA) and Iranian Auto Parts Manufacturers Association (IAPMA) samples. The power analysis method and G*Power software are used to determine the sample size. Moreover, SmartPLS 3 and IBM SPSS 25 software are used for data analysis of the conceptual model and relating hypotheses. Findings The results of this study indicated that the relationships between networking capability, inter-organizational knowledge mechanisms and inter-organizational learning result in a self-reinforcing loop, with a marked impact on firm innovation performance. Originality/value Since there is little understanding of the interdependencies of networking capability, inter-organizational knowledge mechanisms, co-learning and their effect on firm innovation performance, most previous research studies have focused on only one or two of the above-mentioned variables. Thus, their cumulative effect has not examined yet. Looking at inter-organizational relationships from a network perspective and knowledge-based view (KBV), and to consider the simultaneous effect of knowledge mechanisms and learning as intermediary actions alongside, to consider the performance effect of the capability-building process, are the main advantages of this research

    Iran

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    Iran lies between Iraq and, further north, Turkey to the west and Afghanistan and Pakistan to the east. Armenia, Azerbaijan, Turkmenistan, and the Caspian Sea border Iran to the north, and thee Persian Gulf to the south. Iran covers 636,293 square miles. In the early decades of the twentieth century, many people lived by herding animals. Some of the Kurds and the Shahsevan in the northwest, Qashqai, Bakhtiary, Lurs, and Kamseh in the southwest, Baluch in the southeast, and Turkmen in the northeast lived in nomadic camps, traveling with their animals in search of water and pastures. Beginning in the 1920s, the two Pahlavi shahs, Reza Shah and his son, Mohammad Reza Shah, worked to pacify tribespeople and bring them under the control of the central government. Now, nomads have largely been settled and live in villages or migrate to urban areas

    A new approach in petrophysical rock typing

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    Petrophysical rock typing in reservoir characterization is an important input for successful drilling, production, injection, reservoir studies and simulation. In this study petrophysical rock typing is divided into two major categories: 1) a petrophysical static rock type (PSRT): a collection of rocks having the same primary drainage capillary pressure curves or unique water saturation for a given height above the free water level, 2) a petrophysical dynamic rock type (PDRT): a set of rocks with a similar fluid flow behavior. It was shown that static and dynamic rock types do not necessarily overlap or share petrophysical properties, regardless of wettability. In addition, a new index is developed to define PDRTs via the Kozeny-Carman equation and Darcy's law. We also proposed a different index for delineation of PSRTs by combining the Young–Laplace capillary pressure expression and the Kozeny-Carman equation. These new indices were compared with the existing theoretical and empirical indices. Results showed that our indices are representatives of previously developed models which were also tested with mercury injection capillary pressure, water-oil primary drainage capillary pressure, and water-oil relative permeability data on core plugs from a highly heterogeneous carbonate reservoir in an Iranian oil field. This study enabled us to modify the conventional J-function to enhance its capability of normalizing capillary pr essure data universally
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