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Studies of the social construction of markets have not determined which social environments, which we refer to as proximate social space, are most likely to trigger social construction processes. We find that U.S. nonprofit fiscal sponsors respond to greater potential for category emergence when proximate social space is defined by geography but not by market segment. Further, in addition to responding to potential claimants based on geographic peers, organizations also respond to actual claimants based on peers in the market segment. The pattern suggests that geographic social proximity triggers initial label claiming, which in turn triggers responses from market segment peers.

There can be no question that the aggregate economic performance of the United States over the 1990s was outstanding. Except for a brief recession in 1990–1991, the United States experienced steady growth, rising productivity, low and falling unemployment, and little inflation. Following sharp run-ups at the start of the decade, there were also declines in other social and economic indicators such as poverty, welfare caseloads, crime, and teenage birth rates. These trends suggest there were widespread increases in economic prosperity. In fact, however, we do not know exactly how the benefits of this performance were distributed.

We study trends in occupational and geographic mobility of single and married men and women in the United States over the last 40 years. We find that while occupational mobility has increased for almost all subgroups of males, most of the increase was accounted for by a sharp increase in the mobility of singles. Similarly, the rates of geographic mobility were virtually identical for single and married workers in the early 1970s, but diverged since then – the increase in the geographic mobility of single men was more pronounced than the increase for married men. We discuss several theories of worker mobility in light of these trends and suggest that the increased labor force attachment of women might have played a prominent role in driving these changes.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

Choosing where to expand is an important firm strategy. We review and structure research in international location choices. First, we categorize research based on the motive for expansion, distinguishing market-seeking and resource-seeking explanations. Within these two categories we assess the progression of the literature toward an increased acknowledgment of strategic interaction among firms. We also evaluate work that begins to account for different modes of expansion. This emerging research explores the role of geography in acquisitions and begins to incorporate firms' often complex geographic configurations. Building on these developments, we highlight the following areas for future research: examining further the role of location in acquisitions, exploring the role of geography in postexpansion restructuring, and investigating the interaction of vertical and horizontal spillovers to entrants.

This chapter investigates the geographical variations and approaches that shape the implementation of smart city projects on a global scale. Recognizing the significant influence of contextual factors on smart city initiatives, this chapter aims to comprehend the dynamics that drive the objectives and approaches of smart city projects across different countries. This chapter provides an overview of the strategic and geographical factors that impact smart city implementation, considering organizational drivers and practices, such as the Hofstede model in context. It explores the role of citizen-based, technology-based, and decision-making-based development in smart city implementation. Moreover, this chapter examines the strategic, cultural, socioeconomic, and geographical differences that influence smart city projects worldwide. It analyzes the geographical influence and internal drivers of smart city projects, focusing on Europe, North America, Latin America, and East and South Asia. This analysis offers insights into diverse approaches to smart city development, encompassing top-down and bottom-up approaches. By examining various perspectives and experiences from smart city initiatives worldwide, this chapter sheds light on the challenges and opportunities associated with implementing smart city strategies in different contexts.

We study research designs where a binary treatment changes discontinuously at the border between administrative units such as states, counties, or municipalities, creating a treated and a control area. This type of geographically discontinuous treatment assignment can be analyzed in a standard regression discontinuity (RD) framework if the exact geographic location of each unit in the dataset is known. Such data, however, is often unavailable due to privacy considerations or measurement limitations. In the absence of geo-referenced individual-level data, two scenarios can arise depending on what kind of geographic information is available. If researchers have information about each observation’s location within aggregate but small geographic units, a modified RD framework can be applied, where the running variable is treated as discrete instead of continuous. If researchers lack this type of information and instead only have access to the location of units within coarse aggregate geographic units that are too large to be considered in an RD framework, the available coarse geographic information can be used to create a band or buffer around the border, only including in the analysis observations that fall within this band. We characterize each scenario, and also discuss several methodological challenges that are common to all research designs based on geographically discontinuous treatment assignments. We illustrate these issues with an original geographic application that studies the effect of introducing copayments for the use of the Children’s Health Insurance Program in the United States, focusing on the border between Illinois and Wisconsin.

There were 374 mass shootings in the United States between 2013 and 2014 and they were not random occurrences. We expanded the FBI’s definition of mass shootings (four or more injured or killed, not including the shooter), and collected data on every mass shooting that occurred in the United States to observe geographical patterns. Social Disorganization theories state that violence will occur in areas with high levels of poverty, large population density, and little economic opportunity. These theories work well with strain theory, which suggests that blocked goals, the introduction of a negative stimulus, or the removal of a positive stimulus leads to negative emotions, and these emotions can lead to crime in order to resolve the strain felt. From under this framework, we discover with point pattern analysis that there are patterns in the location of mass shootings crime scenes. They are not random. These crimes were far more likely to occur in the South, the Upper Midwest, and in Southern California, while they were considerably less likely to occur in the Pacific Northwest, Upper Midwest, or the Northeast. The lack of random spatial pattern indicates that the structural factors that contribute to mass shootings are more prevalent in certain areas of the United States than in others.