Resource Curse or Destructive Creation: A Tale of Crony Capitalism in Transition

This paper explores the “resource curse” problem as a counter-example of creative performance and innovation by examining reliance on capital and physical resources, showing the gap between expectations and ex-post actual performance became clearer under conditions of economic turmoil. The analysis employs logistic regressions with dichotomous response and predictor variables, showing significant results.Several findings that have use for economic and business practice follow. First, in a transition period, a typical characteristic of successful firms was their reliance on either capital resources or physical asset endowments, whereas the innovation factor was not significant.Second, poor-performing enterprises exhibited evidence of over reliance on both capital and physical assets. Third, firms that relied on both types of resources tended to downplay creative performance. Fourth, reliance on capital/physical resources and adoption of “creative discipline/innovations” tend to be mutually exclusive. In fact, some evidence suggests that firms face more acute problem caused by the law of diminishing returns in troubled times. The Vietnamese corporate sector’s addiction to resources may contribute to economic deterioration, through a downward spiral of lower efficiency leading to consumption of more resources. The “innovation factor” has not been tapped as a source of economic growth. The absence of innovations and creativity has made the notion of “resource curse” become identical to “destructive creation” implemented by ex-ante resource-rich firms, and worsened the problem of resource misallocation in transition turmoil.

Assessing segmentation processes by click detection: online measure of statistical learning, or simple interference?

Statistical learning can be used to extract the words from continuous speech. Gómez, Bion, and Mehler (Language and Cognitive Processes, 26, 212–223, 2011) proposed an online measure of statistical learning: They superimposed auditory clicks on a continuous artificial speech stream made up of a random succession of trisyllabic nonwords. Participants were instructed to detect these clicks, which could be located either within or between words. The results showed that, over the length of exposure, reaction times (RTs) increased more for within-word than for between-word clicks. This result has been accounted for by means of statistical learning of the between-word boundaries. However, even though statistical learning occurs without an intention to learn, it nevertheless requires attentional resources. Therefore, this process could be affected by a concurrent task such as click detection. In the present study, we evaluated the extent to which the click detection task indeed reflects successful statistical learning. Our results suggest that the emergence of RT differences between within- and between-word click detection is neither systematic nor related to the successful segmentation of the artificial language. Therefore, instead of being an online measure of learning, the click detection task seems to interfere with the extraction of statistical regularities.