Search results

Most college athletics department have not sold corporate naming rights to their athletics facilities. Popp et al. (2016) suggests two primary reasons: (1) difficulty in determining proper valuation and (2) fear of stakeholder backlash. The purpose of the current study is to address both concerns by utilizing a hedonic pricing model predicting collegiate naming rights values and utilizing fixed-effects models to determine if consumer behavior (event attendance and donations) is impacted by a corporate name change.

Data from 110 naming rights agreements among NCAA Division I programs were examined, alongside market-related variables, institution-related variables and venue-related variables. Utilizing hierarchical model building to reduce independent variables and OLS regression modeling, significant relationships with annual value of naming rights agreements were uncovered. Fixed effects models were utilized to determine if naming rights impacted attendance and donations.

A final model explained more than 53% of the variance in average annual value of naming rights agreements, with three significant factors: (1) attendance, (2) all-time winning percentage and (3) venue construction cost. Fixed-effects models revealed no significant differences in attendance or donations after a naming rights deal was signed.

Corporate naming rights agreements for college athletics facilities are a recent phenomenon. While a similar study examining drivers of collegiate sport naming rights was previously conducted, the current study revealed a shifting marketplace. In addition, no prior study has examined the impact of a corporate naming rights agreement on future attendance and donations.

The effects of big data in this present age are highly significant, and big data have become more applicable to society. Big data technology has been adopted by many, and its applications are utilized at national, organizational, and industry levels. This transformation of industries due to big data is changing working practice in academia, business, the humanitarian sector, and government, as they offer insights and positive effects across all sectors, making legal, economic, political, social, and ethical impacts in our world and producing innovation, efficiency, better decision-making, and a greater return on investments. This paper reviews the social implications, risks, challenges, and present and future opportunities of big data.

Community-police relations have gained increasing public attention during the past decade. The purpose of the present study was to better understand the relationship between perceived community support and police officer burnout and engagement.

Data were gathered via online survey from 117 officers from a city police department in the Southeastern United States.

Community support was negatively correlated with burnout and positively correlated with engagement. Moreover, multiple regression analyses showed that community support explained significant incremental variance in most dimensions of burnout and engagement, above and beyond demographic factors and community stressors. Qualitative results showed that police officers had mixed perceptions of how they were viewed by the general public, with more negative than positive responses. However, officers felt more positively perceived in their own communities, but concerns were raised that national events affected the perceptions of officers even in positive relationships with their communities. Finally, officers felt that public perceptions impacted their job satisfaction, job performance and personal lives.

The results have practical implications for how to encourage positive interactions between officers and their community, with recommendations for both law enforcement leaders and civilians.

This study is one of the few that highlights the officers' perspective on how public perceptions affect their work. This is important in understanding how to maximize quality community interactions while minimizing conditions that would increase burnout.

The literature on foreignness has, to date, stressed the liability of foreignness (LOF) and the advantage of foreignness (AOF). Drawing on industrial organisation theory, institutional theory, the resource-based view of the firm and the literature on networking, the authors’ research develops an integrated framework to explore the impact of foreignness on internationalisation depth from the perspective of the duality of foreignness (LOF versus AOF) within multiple dimensions. These dimensions are isomorphism, home country of origin, institutional distance and dual embeddedness of multinational enterprises (MNEs).

In this study, the authors empirically test hypotheses arising from this new theoretical framework by examining the characteristics of a sample of 324 Chinese MNEs (CMNEs) that were operating in 63 countries from 1999 to 2018. Employing regression analysis on a panel of 9,410 observations, the results show that foreignness does exhibit multilevel complexity and duality.

The authors’ empirical results show that isomorphism pressures, country of origin and institutional distance have a negative effect on internationalisation depth (as an outcome of LOF) but that dual embeddedness, on the part of MNEs, exerts a positive impact on internationalisation depth (as an outcome of AOF). The implications for research on multilevel complexity and the duality of foreignness are discussed, and managerial implications are outlined.

The implications of the authors’ findings for MNEs should not be generalised to developed countries without examining the characteristics of both China as an emerging country and its MNEs. The second limit is regarding ownership; this framework has limitations due to choosing China and its OFDIs for testing internationalisation depth. Finally, for subsequent research, examining the dynamics of foreignness completes the nature of multicomplexity, defined by external and internal factors of foreignness changing over time and space.

CMNE managers are advised to actively scrutinise their behaviours in the local country to overcome the differences in routines, values and practices inherent in local institutions (Chen et al., 2019). The results imply that CMNEs should be careful not to overuse their home country image when penetrating a new market. Thus, a strategy to reduce a home government's hegemonic or otherwise negative image may be wise when operating abroad. Finally, the authors’ model suggests that CMNEs equipped with great RCN CIPs for identifying, scanning and interpreting local institutions can enhance internationalisation depth.

The authors’ research contributes to research on foreignness by emphasising foreignness as a construct of multilevel complexity. The authors argue that foreignness arises due to varying factors at the host, home, host-home levels and at the level of the organisational entity. The authors’ definition of foreignness and empirical results supports the notion that isomorphism pressures (host country-level factors), country-of-origin of home country (home country-level factors) and institutional distance (host-home country-level factors) are inextricably negatively linked with internationalisation depth (as effects of LOF). By contrast, the dual embeddedness of MNEs (the factor of organisational level) represents a positive relationship with internationalisation depth (as effects of AOF).