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Co-location tools of urban economic development, such as accelerators and incubators, can facilitate entrepreneurship. Of these tools, accelerators have proliferated in number and variety over the past couple of decades. However, growing evidence suggests that these programs are not equally effective, varying in form and function with disparate outcomes. Initial evidence indicates that the effectiveness of accelerators varies by entrepreneurial ecosystem features, such as density and university involvement. Current scholarship is limited, however, in that it doesn't provide an adequate explanation for why that is the case. This paper uses creative class theory to explain the distinct advantages of an accelerator powered by an urban, metropolitan research university. Among these advantages are the dense and diverse networks comprising urban research universities and the value each network participant contributes. In addition, we posit that amplifying these collective contributions is critical to startup success and the overall vitality of the entrepreneurial ecosystem within the region. We support our logic by profiling the best practices, design features, and lessons learned of an accelerator powered by a public, metropolitan research university serving as an anchor institution for the St. Louis region. [The citation of v34 n4 on the PDF is incorrect, this article appears in v34 n3.]

Self-administered questionnaires often use examples or lists of examples to aid respondent recall. We report on the results of a field experiment examining how such examples in survey questions affect the episodic recall of events. Building on part-set cuing theory, the authors propose that examples increase recall when they cue low-accessibility subcategories of events, but may decrease recall when they cue high-accessibility subcategories. Further, cuing with examples rather than subcategory names may in some situations clarify questions and reduce non-useable open-ended responses. Findings from a survey of 2137 adult Medicaid recipients are generally consistent with these predictions. [ABSTRACT FROM AUTHOR]

A framework that helps reveal the underlying values of decisions and allows to expressly think through the trade-offs between those values is presented. Decision mapping and extended decision mapping can be used in evaluating a decision that is formed around choice options, values/goals, outcomes and consequences. How values can be better integrated in decision making is explained.

A study examines whether means-end laddering research innovations used in decision-based voter segmentation processes can be effectively used for campaign message development. Results suggest that the innovations can be used effectively to develop campaign message.

Purpose – The purpose of this paper is to explore the relationship between consumers’ purchase motivations to show support for university programs and the influence of merchandise quality cues on their purchase decision, and examine how one's affiliation with a university (official or non-official) moderates this relationship. Design/methodology/approach – This research utilized a mail survey of university bookstore customers from the USA and Canada. The university, located in the USA, has an international reputation for its academic programs, its athletic teams, and its religious affiliation. Findings – Our findings demonstrate the significance of athletic programs over academic programs and religious values in motivating purchases of licensed university merchandise. Research limitations/implications – These findings have significant implications for several stakeholders in the business of retailing licensed merchandise. In particular, university licensors and their bookstore retailers may consider managing their inventory of licensed products to reflect the greater relative importance athletic teams have in the purchase decision process. Originality/value – This paper adds to our understanding of customer motivations to purchase university licensed merchandise, and the conditions when merchandise quality is a key decision driver. [ABSTRACT FROM AUTHOR]