The Impact of Organizational Culture and Reshaping Capabilities on Change Implementation Success: The Mediating Role of Readiness for Change

abstract    It was hypothesized that employees' perceptions of an organizational culture strong in human relations values and open systems values would be associated with heightened levels of readiness for change which, in turn, would be predictive of change implementation success. Similarly, it was predicted that reshaping capabilities would lead to change implementation success, via its effects on employees' perceptions of readiness for change. Using a temporal research design, these propositions were tested for 67 employees working in a state government department who were about to undergo the implementation of a new end-user computing system in their workplace. Change implementation success was operationalized as user satisfaction and system usage. There was evidence to suggest that employees who perceived strong human relations values in their division at Time 1 reported higher levels of readiness for change at pre-implementation which, in turn, predicted system usage at Time 2. In addition, readiness for change mediated the relationship between reshaping capabilities and system usage. Analyses also revealed that pre-implementation levels of readiness for change exerted a positive main effect on employees' satisfaction with the system's accuracy, user friendliness, and formatting functions at post-implementation. These findings are discussed in terms of their theoretical contribution to the readiness for change literature, and in relation to the practical importance of developing positive change attitudes among employees if change initiatives are to be successful.     

Evolutionary and socio-cultural influences on feelings and attitudes towards nature: a cross-cultural study

Mounting environmental issues have prompted reconsideration of the human–nature relationship. Accordingly, attitudes to nature, as an important dimension of human–nature interactions, have become a research focus. How feelings and attitudes towards nature are influenced by evolutionary and social-cultural constructions, and whether there is variation between different cultural groups, demands more attention. Using a survey of visitors to two very different National Parks, the New Forest National Park, England and Jiuzhaigou Scenic Area, China, this paper shows that of nationality and living environment, differences between the two nationalities were significant in respect of both attitudes and feelings. Specifically, it demonstrates that the biophilia thesis, which purports that people have an innate and a genetically inherited need for affiliation with nature, is influenced by their socio-cultural environment, in particular their national culture, but also by their current living place. The study contributes to our understanding of sustainable tourism in natural areas.     

LACK OF RIGOUR IN DEFENDING FAIRTRADE: A REJOINDER TO ALISTAIR SMITH

Smith (2010 ) does not deny that he made errors in economic theory, logic and fact, and that he had misused evidence. He says that I misrepresented a large body of theory, that I distorted what he said in four places and that I was wrong in one sentence. These statements are false.     

ON THE ROBUSTNESS OF RANGE‐BASED VOLATILITY ESTIMATORS

We empirically examine Parkinson's range‐based volatility estimate in the federal funds market, which is unique because institutional regulations create a predictable pattern in interday volatility. We find that range‐based volatility estimates and standard deviations produce the expected volatility pattern. We also find that at trading pressure points where microstructure noise should be greatest, range‐based estimates are less than the standard deviations. Thus, we support the argument that range‐based volatility estimates remove the upward bias created by microstructure noise. We find that the Parkinson method is the most efficient range‐based volatility measure among a set of alternates in this market.     

Bivariate income distributions for assessing inequality and poverty under dependent samples

As indicators of social welfare, the incidence of inequality and poverty is of ongoing concern to policy makers and researchers alike. Of particular interest are the changes in inequality and poverty over time, which are typically assessed through the estimation of income distributions. From this, income inequality and poverty measures, along with their differences and standard errors, can be derived and compared. With panel data becoming more frequently used to make such comparisons, traditional methods which treat income distributions from different years independently and estimate them on a univariate basis, fail to capture the dependence inherent in a sample taken from a panel study. Consequently, parameter estimates are likely to be less efficient, and the standard errors for between-year differences in various inequality and poverty measures will be incorrect. This paper addresses the issue of sample dependence by suggesting a number of bivariate distributions, with Singh–Maddala or Dagum marginals, for a partially dependent sample of household income for two years. Specifically, the distributions considered are the bivariate Singh–Maddala distribution, proposed by Takahasi (1965), and bivariate distributions belonging to the copula class of multivariate distributions, which are an increasingly popular approach to modelling joint distributions. Each bivariate income distribution is estimated via full information maximum likelihood using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey for 2001 and 2005. Parameter estimates for each bivariate income distribution are used to obtain values for mean income and modal income, the Gini inequality coefficient and the headcount ratio poverty measure, along with their differences, enabling the assessment of changes in such measures over time. In addition, the standard errors of each summary measure and their differences, which are of particular interest in this analysis, are calculated using the delta method.     

The Developmental Impact of Asian Drivers on Kenya with Emphasis on Textiles and Clothing Manufacturing

(1251) Paul Kamau with Dorothy McCormick and Nicolas Pinaud Kenya has enjoyed a relatively diversified economy (at least by SSA standards), with light manufacturing industries in particular playing a significant growing role. The rise of Asian competition (locally, regionally and on third‐country markets), partly due to the erosion of trade preferences for clothing and footwear, has raised fresh policy challenges. The specific relevance of the clothing industry in the analysis of China’s and India’s impact on Africa is manifold: this is a low‐skilled labour‐intensive industry, and hence an avenue for African economies’ diversification; the competition from Asian producers vis‐à‐vis the SSA clothing industry is felt at the local, regional and global level (on third‐country markets): it is therefore direct and indirect; also, the Asian Drivers’ impact on African clothing industries has both a trade and investment dimension while being competitive and complementary.