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The purpose of this study was to examine the relationship between place image and attitudes toward cities with the moderating effect of sporting event awareness. Exploratory research was conducted using a mall-intercept sampling technique with a sample of 299 local residents. PLS-SEM using SmartPLS 3.3.2 was performed to test the hypothesized relationships. The findings demonstrated a significant relationship between place image and resident attitudes. In addition, a reflective–formative construct of place image showed that municipal facilities, leisure, and public services were significant factors in influencing perceptions of place image. The moderating effect of awareness was not found to be significant. The results of this study recommend that city authorities and tourism managers recognize and address the various dimensions of place image to increase community support. This would benefit event managers through developing favorable attitudes of residents towards their cities, thus having a social impact on the host city's residents.

Consumer interest and attention are drawn to the brand through advertisements that feature the celebrity endorser, resulting in heightened brand awareness, increased sales, more favorable brand attachment, and increased consumer intention to purchase the endorsed brand. The effectiveness of a celebrity endorsement depends on the endorser’s inherent meaning, including the authentic lifestyle, personality, and social status that a particular celebrity brings to the brands they endorse. Authenticity provides a brand with a unique identity and a strong association for consumers. The purpose of this study is to examine the relationships between consumer perceptions of athlete authenticity, endorsed brand authenticity, brand attachment and purchase intention. Data were collected from Amazon’s Mechanical Turk and a total of 372 were deemed usable data. Structural equation modeling (SEM) was conducted to examine the hypotheses. This study reveals that consumers’ perceptions of the athlete endorser’s authenticity positively influenced their perceptions of brand authenticity, which then led to attachment to the brand and a favorable intention to purchase it. Athlete endorser authenticity, however, does not have an influence on brand attachment but rather first needs to be inserted into the brand authenticity. The current study expands on the knowledge of brand attachment literature to show that authentic brands elicit strong attachments in consumers.

Researchers have struggled to understand under what conditions the endorsement effect is maximized. The current study is the first attempt to apply the concept of ‘authenticity’ to the endorsement domain of sport. The purpose of this study is to apply a new concept -authenticity- to the evaluation of endorser effects and empirically investigate the three-way interaction effects of endorser-brand congruence, endorser authenticity, and self-brand connection on brand attitude in the sport domain. A total of 243 participants in the United States were recruited via online survey method. Current study reveals three key findings. First, the endorser-brand congruence effect on the attitude toward the brand is maximized when two variables (endorser authenticity and self-brand connection) interact with each other rather than when each predictor separately affects the brand attitude. Second, an athlete endorser’s authentic image can be transferred to attitude toward the brand when consumers have a self-brand connection. Third, the athlete endorser’s authentic image is not easily transferred to the brand attitude at the low level of self-brand connection.

Highway-rail grade crossings (HRGCs) are unique nodes in the transportation system that facilitate the movement of rail and highway traffic. Various mathematical models are available that provide safety assessments of HRGCs. A chief ingredient of these models is the annual average daily traffic (AADT). One of the main sources of data for such models is the Federal Railroad Administration (FRA)’s Grade Crossing Inventory. A substantial portion of the AADT data in the inventory is outdated. This paper investigates the effects of using out-of-date rather than up-to-date AADT values, using two safety assessment models to isolate the differences. Results show that the use of out-of-date AADT data generates biased rankings of HRGCs based on safety considerations. Since collection of AADT data is resource-intense, a methodology based on a geographic information system for estimating updated AADT is presented. This methodology utilizes limited traffic counts that are supplemented with additional publicly available data. An application using a geographically weighted Poisson regression model for 14 HRGCs gave results that closely matched AADT values based on 2018 field traffic counts at those HRGCs. This method provides an alternative to costly field-data-based updating of AADT in the relatively extensive Grade Crossing Inventory database. Limitations of the research and suggestions for future research complete this paper.

Traffic crash hot spot analyses allow identification of roadway segments that may be of safety concern. Understanding geographic patterns of existing motor vehicle crashes is one of the primary steps for geostatistical-based hot spot analysis. Much of the current literature, however, has not paid particular attention to differentiating among cluster types based on crash severity levels. This study aims at building a framework for identifying significant spatial clustering patterns characterized by crash severity and analyzing identified clusters quantitatively. A case study using an integrated method of network-based local spatial autocorrelation and the Kernel density estimation method revealed a strong spatial relationship between crash severity clusters and geographic regions. In addition, the total aggregated distance and the density of identified clusters obtained from density estimation allowed a quantitative analysis for each cluster. The contribution of this research is incorporating crash severity into hot spot analysis thereby allowing more informed decision making with respect to highway safety.

Brand extension is one of the most effective marketing strategies for companies to expand their business spectrum. At the same time, failed brand extensions lead to negative consequences for the companies, such as decreasing brand loyalty. In this sense, it is necessary to examine how sport consumers evaluate brand extensions and the impact of brand extension evaluation on the brand loyalty. The purpose of this study is to investigate the structural relationships between two antecedents (i.e., the perceived quality of the parent brand; and the perceived fit between the parent brand and its extension brand) and brand extension evaluation. Data were collected from 254 sport consumers living in South Korea. Structural equation modeling suggests that a perceived fit between the parent brand and its extension brand plays a pivotal role in the evaluation of brand extension that leads to increasing brand loyalty. Although the perceived quality of the parent brand has not had a significant influence on brand extension evaluation, it positively affects brand loyalty. The current study provides sport marketers and brand managers with important information to maximize the successful rate of brand extensions that ultimately lead to enhancement of the parent brand loyalty.

Existing literature on fan associations tends to neglect consumer segmentation such as BIRFing and CORSing. Thus, empirical research on fan associations (or dissociations) among sport fans who exhibit more deviant team identification tendency, such as BIRFers or CORSers, will contribute to the body of knowledge. Via a purposive sampling, the current study sought to predict rather unusual fan tendencies (BIRFers’ intention to resist team switch; CORSers’ intention to switch teams). The overall results depicted how BIRFers and CORSers cognitively associate with professional sports teams. Briefly, seven fan association types (e.g., Brand Mark) significantly predicted BIRFers’ resistance with team switching while two fan association types (e.g., Rivalry) significantly predicted CORSers’ intention to team switch.

The purpose of this research is to evaluate the quality of Differential Police Response strategy. Although it has been approximately three years since these new police response systems were introduced, there is no research to evaluate them empirically. Using two types of statistical quality control techniques, Xbar-R control charts for variables data and P charts for attributes data, this study analyzes approximately 3,000 calls reported throughout the year 2012 to the 112 Integrated Dispatch Center in Ik-san police station. The Xbar-R control charts revealed that the police did not consistently respond to an emergency call for service (i.e., code one case) within 3 minutes. The P control chart also identified that there was a significant variation in the portion/number of defective calls where police failed to respond to non-emergency calls for service within 5 minutes. The results from this study suggest the police may need to review the target response time for code 1 and code 2 respectively.

The objectives of this research were to test and validate the feasibility of assessing humped highway–rail crossings for safe passage of vehicles with low ground clearance using lidar data. Collected using an airborne platform, lidar data provide georeferenced spatial information about the shape and surface characteristics of Earth. The suitability of humped highway–rail crossings for use by vehicles with low ground clearance and a long wheelbase is a concern because of the possibility of vehicles getting lodged on rail tracks. While such vehicles usually travel on designated routes, emergencies or highway closures may result in these vehicles traveling on undesignated highways with humped grade crossings. Lidar data and line-of-sight analysis in a geographic information system (GIS) were used to identify potentially problematic grade crossings for certain types of low-ground-clearance vehicles with a long wheelbase. Results of the GIS analysis were validated in the field at actual grade crossings with survey equipment. The main conclusion was that lidar data could be successfully used for identification of highway–rail crossing vehicle hang-up issues.