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Social media applications are slowly diffusing across all levels of government. The organizational dynamics underlying adoption and use decisions follow a process similar to that for previous waves of new information and communication technologies. The authors suggest that the organizational diffusion of these types of new information and communication technologies, initially aimed at individual use and available through markets, including social media applications, follows a three‐stage process. First, agencies experiment informally with social media outside of accepted technology use policies. Next, order evolves from the first chaotic stage as government organizations recognize the need to draft norms and regulations. Finally, organizational institutions evolve that clearly outline appropriate behavior, types of interactions, and new modes of communication that subsequently are formalized in social media strategies and policies. For each of the stages, the authors provide examples and a set of propositions to guide future research.

AbstractThe partial takedown phenomenon associated with bank loan commitments is examined in a dynamic context in which banks adjust commitment prices to client takedown behavior. The optimal takedown is an increasing function of client riskiness and a decreasing function of the time the client plans to remain with its present bank and the cost of switching to a new bank. Since the bank's learning is cumulative, the longer a client remains with its bank the smaller is the commitment price adjustment resulting from an aberrant takedown. The enhanced commitment price certainty, obtained with longevity of the client relationship, helps to explain client reluctance to switch banks. Since the optimal takedown is an increasing function of client riskiness under adaptive pricing, such pricing may serve the added purpose of providing information on client risk.

Tests of a neuropsychological model for spatial orientation in the absence of vision were developed and administered to 31 children who are congenitally blind. The results supported the model and indicated that some congenitally blind subjects had focal brain damage, sufficient to impair their capacity to be accurately oriented in physical space.

Policy researchers have become increasingly familiar with a number of improved techniques for analyzing data obtained from interrupted time‐series designs for evaluating public programs and policies. In this paper we contribute to this trend by presenting two groups of data analysis techniques which are not currently widely used by policy researchers, but are likely to be valuable adjuncts to traditional regression techniques for analyzing data obtained from interrupted time‐series designs. First, aids for model specification are presented that enable the analyst to define an appropriate linear trend model—often one which will reduce the degree of multicollinearity and, therefore, produce more precise estimates of the impacts of a public program or policy. Next we consider approaches for point estimation and joint (simultaneous) interval estimation of a policy intervention's total effect at various points in time.