Overcoming liability of newness of international new ventures : the role of flexibility

Riding on the trend of globalization, a large number of new ventures have emerged deploying resources in multiple country markets so as to arrive at a competitive advantage. Studies that focus on such international new ventures grew to become a distinct research area: international Entrepreneurship that attracts much research attention but leaves a core issue namely liability of newness unaddressed. About 50 years ago, Stinchcombe (1965) coined this term to explain that most new ventures fail because their founders cannot switch their roles quickly enough to adapt to the changing environment. Although previous empirical studies have examined the entrepreneurial firms from the knowledge based view and organizational learning theory and tried to account for the varied ability of these entrepreneurial firms in switching roles in accordance of circumstances, little or no extant studies employs a Resource-based View (RBV) approach. This study will focus on INVs from emerging economics, trying to examine how INVs overcome liability of newness through “flexibility” to gain good performance during their internationalization. Based on the RBV of the firm, this study will address flexibility in form of a flexible configuration of firm resources consisting of cognitive, structural, and strategic flexibility as the predictors, arguing that these flexibilities would help INVs cope with liability of newness by fostering various dynamic capabilities that have been found to improve INVs’ performance. In addition, this study will focus on those INV firms located in industrial clusters, and examine how an INV\u27s network ties within an industrial cluster moderate the relationships among flexibility and the involved dynamic capabilities. This study collected a sample of 192 Chinese international new ventures, and structural equation modeling was used to test the full model. The findings demonstrate that: (1) all the three dimension of flexibilities have positive impact on international performance; (2) exploratory learning capability and adaptive capability mediate flexibility-international performance relationship while information acquisition capability does not; and (3) an INV’s network ties positively moderates both cognitive flexibility-information acquisition capability relationship and information acquisition capability-exploratory learning capability relationship while negatively moderates information acquisition capability-adaptive capability relationship. On the basis of current findings, implications and future research directions are drawn

Transcriptional Regulation Of The Urea Cycle Enzyme Genes In The Liver Of Rana Catesbeiana Tadpoles During Spontaneous And Thyroid Hormone-induced Metamorphosis

The ornithine urea cycle enzymes, carbamyl phosphate synthetase (CPS-1), ornithine transcarbamylase (OTC) and arginase, are liver-specific proteins. Their expression is coordinately activated during the metamorphosis of the Rana catesbeiana tadpole by thyroid hormone (TH), and their presence is critical for the shift of this amphibian from an aquatic, ammonotelic larva into a terrestrial, ureotelic adult. My studies were focused on analyzing the transcriptional regulation of the genes encoding these urea cycle enzymes and determining whether these genes were upregulated directly or indirectly by TH. With this thought in mind, I isolated and characterized the sequences in the promoter regions of the CPS-1 and OTC genes and found that they lacked thyroid hormone response elements (TREs). This observation implies that TH is not directly regulating the expression of these genes. However, the presence of C/EBP (CAATT/enhancer binding protein) binding elements in the promoter regions of both of these genes prompted the thought that this transcription factor may be TH-inducible and play a role in the TH-indured expression of the CPS-1 and OTC genes. Thus, I isolated and characterized cDNAs encoding two different C/EBP-like proteins. One of them, RcC/EBP-1, encodes a Rana homologue of the mammalian C/EBP{dollar}\alpha{dollar}, and protein synthesized from it was found to bind specifically to the mammalian C/EBP-like sequences present in the Rana CPS-1 and OTC genes. Although no TREs are evident in the promoter region of this RcC/EBP-1 gene, Southern hybridizations suggest that more than one copy of this gene is present in the Rana genome and Northern hybridizations indicate that at least one of them is upregulated by TH. The TH-induced upregulation of an RcC/EBP-1 mRNA is concurrent with the upregulation of mRNAs encoding a thyroid hormone direct-response gene, TR{dollar}\beta{dollar}, and precedes, by at least 12 hours, the upregulation of mRNAs encoding CPS-1, OTC and arginase. These results imply that the TH-induced expression of urea cycle enzyme genes involves a cascade of molecular events in which a member of the RcC/EBP-1 family plays a role in orchestrating the expression of these genes in the liver of this tadpole during both spontaneous and TH-induced metamorphosis

Multifractal scaling analyses of urban street network structure: the cases of twelve megacities in China

Traffic networks have been proved to be fractal systems. However, previous studies mainly focused on monofractal networks, while complex systems are of multifractal structure. This paper is devoted to exploring the general regularities of multifractal scaling processes in the street network of 12 Chinese cities. The city clustering algorithm is employed to identify urban boundaries for defining comparable study areas; box-counting method and the direct determination method are utilized to extract spatial data; the least squares calculation is employed to estimate the global and local multifractal parameters. The results showed multifractal structure of urban street networks. The global multifractal dimension spectrums are inverse S-shaped curves, while the local singularity spectrums are asymmetric unimodal curves. If the moment order q approaches negative infinity, the generalized correlation dimension will seriously exceed the embedding space dimension 2, and the local fractal dimension curve displays an abnormal decrease for most cities. The scaling relation of local fractal dimension gradually breaks if the q value is too high, but the different levels of the network always keep the scaling reflecting singularity exponent. The main conclusions are as follows. First, urban street networks follow multifractal scaling law, and scaling precedes local fractal structure. Second, the patterns of traffic networks take on characteristics of spatial concentration, but they also show the implied trend of spatial deconcentration. Third, the development space of central area and network intensive areas is limited, while the fringe zone and network sparse areas show the phenomenon of disordered evolution. This work may be revealing for understanding and further research on complex spatial networks by using multifractal theory.Comment: 32 pages, 9 figures, 5 table

Spatial Signal Analysis based on Wave-Spectral Fractal Scaling: A Case of Urban Street Networks

For a long time, many methods are developed to make temporal signal analyses based on time series. However, for geographical systems, spatial signal analyses are as important as temporal signal analyses. Nonstationary spatial and temporal processes are associated with nonlinearity, and cannot be effectively analyzed by conventional analytical approaches. Fractal theory provides a powerful tool for exploring complexity and is helpful for spatio-temporal signal analysis. This paper is devoted to researching spatial signals of geographical systems by means of wave-spectrum scaling. The traffic networks of 10 Chinese cities are taken as cases for positive studies. Fast Fourier transform and least squares regression analysis are employed to calculate spectral exponents. The results show that the wave-spectral density distribution of all these urban traffic networks follows scaling law, and the spectral scaling exponents can be converted to fractal dimension values. Using the fractal parameters, we can make spatial analyses for the geographical signals. The analytical process can be generalized to temporal signal analyses. The wave-spectrum scaling methods can be applied to both self-similar fractal signals and self-affine fractal signals in the geographical world.Comment: 22 pages, 7 figures, 4 table

An activity-based spatial-temporal community electricity vulnerability assessment framework

The power system is among the most important critical infrastructures in urban cities and is getting increasingly essential in supporting people s daily activities. However, it is also susceptible to most natural disasters such as tsunamis, floods, or earthquakes. Electricity vulnerability, therefore, forms a crucial basis for community resilience. This paper aims to present an assessment framework of spatial-temporal electricity vulnerability to support the building of community resilience against power outages. The framework includes vulnerability indexes in terms of occupant demographics, occupant activity patterns, and urban building characteristics. To integrate factors in these aspects, we also proposed a process as activity simulation-mapping-evaluation-visualization to apply the framework and visualize results. This framework can help planners make an effective first-time response by identifying the most vulnerable areas when a massive power outage happens during natural disasters. It can also be integrated into community resilience analysis models and potentially contributes to effective disaster risk managementComment: to be published in Proceedings of the 5th International Conference on Building Energy and Environmen

Community Time-Activity Trajectory Modelling based on Markov Chain Simulation and Dirichlet Regression

Accurate modeling of human time-activity trajectory is essential to support community resilience and emergency response strategies such as daily energy planning and urban seismic vulnerability assessment. However, existing modeling of time-activity trajectory is only driven by socio-demographic information with identical activity trajectories shared among the same group of people and neglects the influence of the environment. To further improve human time-activity trajectory modeling, this paper constructs community time-activity trajectory and analyzes how social-demographic and built environment influence people s activity trajectory based on Markov Chains and Dirichlet Regression. We use the New York area as a case study and gather data from American Time Use Survey, Policy Map, and the New York City Energy & Water Performance Map to evaluate the proposed method. To validate the regression model, Box s M Test and T-test are performed with 80% data training the model and the left 20% as the test sample. The modeling results align well with the actual human behavior trajectories, demonstrating the effectiveness of the proposed method. It also shows that both social-demographic and built environment factors will significantly impact a community's time-activity trajectory. Specifically, 1) Diversity and median age both have a significant influence on the proportion of time people assign to education activity. 2) Transportation condition affects people s activity trajectory in the way that longer commute time decreases the proportion of biological activity (eg. sleeping and eating) and increases people s working time. 3) Residential density affects almost all activities with a significant p-value for all biological needs, household management, working, education, and personal preference.Comment: to be published in Computers, Environment and Urban Syste

Defining Urban Boundaries by Characteristic Scales

Defining an objective boundary for a city is a difficult problem, which remains to be solved by an effective method. Recent years, new methods for identifying urban boundary have been developed by means of spatial search techniques (e.g. CCA). However, the new algorithms are involved with another problem, that is, how to determine the characteristic radius of spatial search. This paper proposes new approaches to looking for the most advisable spatial searching radius for determining urban boundary. We found that the relationships between the spatial searching radius and the corresponding number of clusters take on an exponential function. In the exponential model, the scale parameter just represents the characteristic length that we can use to define the most objective urban boundary objectively. Two sets of China's cities are employed to test this method, and the results lend support to the judgment that the characteristic parameter can well serve for the spatial searching radius. The research may be revealing for making urban spatial analysis in methodology and implementing identification of urban boundaries in practice.Comment: 26 pages, 5 figures, 7 table