The impact of organizational culture and reshaping capabilities on change implementation success: The mediating role of readiness for change

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.

The role of uncertainty in the relationship between fairness evaluations and willingness to pay

Participants in contingent valuation studies may be uncertain about a number of aspects of the policy and survey context. The uncertainty management model of fairness judgments states that individuals will evaluate a policy in terms of its fairness when they do not know whether they can trust the relevant managing authority or experience uncertainty due to insufficient knowledge of the general issues surrounding the environmental policy. Similarly, some researchers have suggested that, not knowing how to answer WTP questions, participants convey their general attitudes toward the public good rather than report well-defined economic preferences. These contentions were investigated in a sample of 840 residents in four urban catchments across Australia who were interviewed about their WTP for stormwater pollution abatement. Four sources of uncertainty were measured: amount of prior issue-related thought, trustworthiness of the water authority, insufficient scenario information, and WTP response uncertainty. A logistic regression model was estimated in each subsample to test the main effects of the uncertainty sources on WTP as well as their interaction with fairness and proenvironmental attitudes. Results indicated support for the uncertainty management model in only one of the four samples. Similarly, proenvironmental attitudes interacted rarely with uncertainty to a significant level, and in ways that were more complex than hypothesised. It was concluded that uncertain individuals were generally not more likely than other participants to draw on either fairness evaluations or proenvironmental attitudes when making decisions about paying for stormwater pollution abatement.

Special issue: Selected papers from the sixth IFIP 2.6 working conference on visual database systems: Guest editors' introduction

While multimedia data, image data in particular, is an integral part of most websites and web documents, our quest for information so far is still restricted to text based search. To explore the World Wide Web more effectively, especially its rich repository of truly multimedia information, we are facing a number of challenging problems. Firstly, we face the ambiguous and highly subjective nature of defining image semantics and similarity. Secondly, multimedia data could come from highly diversified sources, as a result of automatic image capturing and generation processes. Finally, multimedia information exists in decentralised sources over the Web, making it difficult to use conventional content-based image retrieval (CBIR) techniques for effective and efficient search. In this special issue, we present a collection of five papers on visual and multimedia information management and retrieval topics, addressing some aspects of these challenges. These papers have been selected from the conference proceedings (Kluwer Academic Publishers, ISBN: 1-4020- 7060-8) of the Sixth IFIP 2.6 Working Conference on Visual Database Systems (VDB6), held in Brisbane, Australia, on 29–31 May 2002.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.