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To examine objective measures of economic job quality for a broad sample of workers in the US spectator sports industry and compare job quality in spectator sports to other industries.

Logistic and linear regressions are performed on American Community Survey (ACS) data collected from 2015 to 2019. Earnings and employer provision of health insurance are the outcomes.

Earnings and employer-provided health insurance are lower in the spectator sports industry than in other industries after controlling for relevant factors. Differences are partly explained by the occupational composition of the industry and the higher incidence of part-time work. Many but not all occupational groups have lower earnings and less employer-provided health insurance in sports.

ACS data only reports one job, so the results likely underestimate the prevalence of part-time work in the US spectator sports industry. The study finds support for a micro-class occupational composition effect and a pulsating organization effect. Some support is also found for a sports industry compensating wage differential, but the effect is not industry wide, counter to some depictions.

This is the first study to examine objective, economic measures of job quality across all occupational sub-groups in the sports industry. This is the first study to propose theoretical explanations for poor economic job quality in sport.

Despite increasingly persuasive women-focused marketing of gambling products, there has only been limited investigation around women sports betting. Men remain the focus of much of the conversation about sports betting as they have generally been found to be the most active sports bettors and the most at risk of experiencing harms associated with their behaviour. This chapter aims to fill this gap by exploring the characteristics of young women sports bettors in the United Kingdom and the relationship between sports betting and the experience of gambling harms. To do this, we created two models of analysis. Our analysis is based on data from the first wave (2019) of the Emerging Adults Gambling Survey (EAGS) dataset (n = 3,549). The EAGS is a non-probability longitudinal survey that includes individuals between the ages of 16 and 24 who were residents in Britain at the time of data collection. Firstly, we examined the associations between women sports bettors and several factors identified as important predictors of sports betting. Secondly, we sought to understand the relationship between women's sports betting and the harms associated with this activity. From these models, we found that women's sports betting was most reliably predicted according to fandom and peer influence. We also found that women sports bettors were more at risk of experiencing harms associated with difficulties with family and friends than women gamblers using other products.

This study investigated the relationship between last-mile distribution or delivery (LMD) and commodity access through the mediating role of commodity availability and commodity security and the moderating effect of supply chain integration (SCI).

The study adopted the survey research design and employed the questionnaire instrument in collecting primary data from respondents in Eastern Regional Health Institutions in Ghana. The total number of valid responses received was 204. The partial least squares structural equation modeling (PLS-SEM) approach was adopted to analyze the relationship between the study variables.

The findings showed that there is a positive and significant relationship between LMD and commodity availability as well as LMD and commodity security. Moreover, while the relationship between commodity availability and commodity access is positive and significant, that between commodity security and commodity access is positive but insignificant. Furthermore, there is a positive and statistically significant relationship between LMD and commodity access. The study discovered that the interaction between LMD and commodity access is insignificant and negatively affected by SCI.

To the best of the authors' knowledge, no previous studies have empirically verified the effect of LMD on commodity access in the presence of mediating factors such as commodity availability and commodity security and SCI as the moderating factors.

This study aims to examine the performance implications of an information governance (IG) framework for managing, controlling access to and securing information, focusing on (1) the performance benefits of an organization's IG orientation and (2) how the configuration of IG orientation and supply chain (SC) strategy type relate to performance outcomes.

This study leverages multiple secondary sources for US hospitals, serving as the context for the study. It also employs cluster analysis to develop an SC strategy taxonomy, namely sophisticated and delivery-focused SC strategies. The proposed research model is tested using a robust regression to mitigate the influence of outliers and produce more accurate estimates.

IG orientation is positively associated with financial performance and patient experience, and IG-oriented hospitals with a sophisticated SC strategy realize more financial benefits and achieve better patient care experiences compared to other configurations. Regardless of SC strategy type, IG-oriented hospitals offer better care experiences than non-IG-oriented hospitals.

This paper offers empirical evidence that a hospital's IG orientation and SC strategy jointly affect financial outcomes and patient experience. For hospitals, an organization-wide framework for governing information streamlines both intra- and inter-organizational information flows and improves care delivery throughout a patient's care experience.

This is one of a few studies that empirically examine the performance implications of governance of information in the domain of supply chain management (SCM). This study also develops an SC strategy taxonomy for the healthcare context and offers a springboard for research in service SC strategy.

The study aims to design a holistic multi-stage hierarchical model that leverages the firm's knowledge-enabled distinctive core competencies (DCCs) and builds enduring and profitable customer relationships to achieve sustainable competitive advantage (SCA) in dynamic and challenging environments. It developed a knowledge-enabled customer-centric competitiveness strategy (KCCS) model that integrates four pillars: business process reengineering (BPR), knowledge management (KM), customer relationship management (CRM) and competitiveness strategy. It also proposed a BPR model to enable cross-functional cooperation and coordination for firms dealing with customers, provided a blueprint for KCCS's successful implementation and compared the KCCS model with other customer-centric (CC) approaches.

This study adopted an exploratory research design based on a literature review of relevant studies. It has systematically analyzed 130 articles and books from Scopus, the Web of Science, Google Scholar and other renowned databases from 1982 to 2022. The analysis involved identifying and selecting relevant literature and conducting thematic research to develop a theoretical KCCS model that integrates BPR, KM, CRM, competitiveness strategy and the firm's SCA into a KCCS model.

This study developed an integrative KCCS theoretical model rooted in the extant literature in BPR, KM, CRM, competitiveness strategy, DCCs, SCA and other fields. The study proposed a BPR model as a significant component of KCCS that enables cross-functional cooperation and coordination, which are often troublesome for firms in their dealings with customers. The study also provided a blueprint for successfully implementing the KCCS model and compared the KCCS model with other CC approaches.

This study filled many research gaps in the literature in which knowledge-enabled CC frameworks are widely scattered. It offered a conceptual multi-stage hierarchical KCCS model that combines interrelated elements of BPR, KM, CRM, and competitiveness strategy. It proposed a BPR model as a significant component of the KCCS that enables cross-functional cooperation and coordination, which frequently form barriers when dealing with customers. It also provided a blueprint for successfully implementing the KCCS and compared it with other CC approaches.

Big data marketing analytics (BDMA) has been discovered to be a key contributing factor to developing necessary marketing capabilities. This research aims to investigate the impact of the technology and information quality of BDMA on the critical marketing capabilities by differentiating between firms with low and high perceived market performance.

The responses were collected from marketing professionals familiar with BDMA in North America (N = 236). The analysis was done with partial least squares-structural equation modelling (PLS-SEM).

The results indicated positive and significant relationships between the information and technology quality as exogenous constructs and the endogenous constructs of the marketing capabilities of marketing planning, implementation and customer relationship management (CRM) with mainly moderate effect sizes. Differences in the path coefficients in the structural model were detected between firms with low and high perceived market performance.

This research indicates the critical role of technology and information quality in developing marketing capabilities. The study discovered heterogeneity in the sample population when using the low and high perceived market performance as the source of potential heterogeneity, the presence of which would likely cause a threat to the validity of the results in case heterogeneity is not considered. Thus, this research builds on previous research by considering this issue.