This article examines the road that network scholarship has followed in Public Administration. We look at the historical drivers of the use of networks in practice and scholarship in the field and discuss how that has shaped the current literature. The body of the article focuses on the current challenges that network scholars face in the discipline, specifically basic theoretical issues, knowledge about formal networks, knowledge about informal networks, and methodological issues. We close the article with a look to the future and some suggestions for the future of network scholarship in Public Administration.

This article addresses a gap in the extant literature on networks by assessing how interorganizational relationships evolve in a public sector network setting. The context for the research was a network of publicly funded health and human service agencies involved in service delivery to people with serious mental illness. Longitudinal data were collected from a single community. The analysis suggests that public and nonprofit sector relationships evolve differently than private sector partnerships, providing an alternative perspective to the prevailing view in organization theory. Policy makers have increasingly selected network forms of governance as a mechanism to provide health and human services to their constituents (Agranoff 1991; Bardach 1998; O'Toole 1997). Networks are thought to assist service providers in coordinating professional activities, resulting in enhanced services to clients. Although network forms of governance are a common mechanism used by state and local governments to accomplish coordination among their service providers, knowledge about the process of creating, maintaining, or growing linkages within a network is still just emerging. In particular, the question of how network relationships change over time remains largely unanswered. As policy makers continue to encourage the formation of service provision networks among private and nonprofit organizations, it is important to understand how networks work. The most extensive body of literature on interorganizational relationships and networks has been in organization theory. Unfortunately, the preponderance of this literature has focused on private sector settings. Although it is likely that some, and even many, findings in the private sector literature are transferable to the public sector, we do not

This article offers an overview of the conceptual, substantive, and practical issues surrounding “big data” to provide one perspective on how the field of public affairs can successfully cope with the big data revolution. Big data in public affairs refers to a combination of administrative data collected through traditional means and large‐scale data sets created by sensors, computer networks, or individuals as they use the Internet. In public affairs, new opportunities for real‐time insights into behavioral patterns are emerging but are bound by safeguards limiting government reach through the restriction of the collection and analysis of these data. To address both the opportunities and challenges of this emerging phenomenon, the authors first review the evolving canon of big data articles across related fields. Second, they derive a working definition of big data in public affairs. Third, they review the methodological and analytic challenges of using big data in public affairs scholarship and practice. The article concludes with implications for public affairs.

Researchers concerned with organizational change have consistently emphasized the role that the work environment plays in employee acceptance of change. Underexamined in the public management literature, however, is the role that employee values, particularly public service motivation (PSM), may play in employee acceptance of change. Some scholars have noted a positive correlation between employee PSM and organizational change efforts; this article extends this work by attempting to isolate the mechanisms that explain this relationship. Using data from a survey of employees in a city undergoing a reorganization and reduction in workforce, the authors find that only employees who scored high on a single dimension of PSM—self‐sacrifice—were more likely than others to support organizational change. Rather than support changes for their potential to improve public service, this finding suggests that employees with higher PSM may simply be less likely to resist changes that might disadvantage them personally.

As examples of a state of agents, this paper will present a comparative analysis of the evolution of two community mental health networks that both have similar contracts from the State of Arizona and operate under the same set of rules. One of these is governed by a for-profit firm that both produces services directly and buys them from a network of nonprofit agencies. The other is governed by a community based nonprofit that contracts with four separate nonprofit networks to offer services. These networks are analyzed, using social network analysis, at the beginning of the system and four years later. The mature network is compared to the new network. The for-profit governed system is compared to the nonprofit governed system. The paper discusses the evolution of structure over time and a limited comparison of the networks in terms of which produced higher quality outcomes.

Enthusiasm for using Twitter as a source of data in the social sciences extends to measuring the impact of research with Twitter data being a key component in the new altmetrics approach. In this paper, we examine tweets containing links to research articles in the field of dentistry to assess the extent to which tweeting about scientific papers signifies engagement with, attention to, or consumption of scientific literature. The main goal is to better comprehend the role Twitter plays in scholarly communication and the potential value of tweet counts as traces of broader engagement with scientific literature. In particular, the pattern of tweeting to the top ten most tweeted scientific dental articles and of tweeting by accounts is examined. The ideal that tweeting about scholarly articles represents curating and informing about state-of-the-art appears not to be realized in practice. We see much presumably human tweeting almost entirely mechanical and devoid of original thought, no evidence of conversation, tweets generated by monomania, duplicate tweeting from many accounts under centralized professional management and tweets generated by bots. Some accounts exemplify the ideal, but they represent less than 10% of tweets. Therefore, any conclusions drawn from twitter data is swamped by the mechanical nature of the bulk of tweeting behavior. In light of these results, we discuss the compatibility of Twitter with the research enterprise as well as some of the financial incentives behind these patterns.

This article examines the evolution of a community-based network of mostly nonprofit

States are key to implementing evidence-based practices, but state mental health authorities should note that each of the practices requires different skill sets and involves different stakeholders. Thus implementing many evidence-based practices at once may not yield economies of scale.