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The design of context‐aware mobile applications can be improved through a clear and in‐depth understanding of context and how it can be used to meet users' requirements. Using tourism as a case application, this paper aims to address the lack of understanding of context and tourists' goals.

This is achieved through a literature review of existing research and focus groups to gather information needs for tasks commonly executed by tourists.

This paper proposes the TILES (temporal, identity, location, environmental and social) model to define and classify five main contextual types, and properties associated with each type for tourism‐related applications. The TILES model (with 32 factors) derived from the analysis of the literature review is refined through inputs from two focus groups to incorporate an additional ten factors.

The TILES model can be generalised to support domains other than tourism, such as medical and edutainment.

The model will help to achieve a better understanding of context, users' information needs and their goals. In addition, this work extends findings in the field of context‐aware computing and information retrieval on mobile devices. Solution providers will also be able to adopt TILES as a framework for guiding the design of their context‐aware mobile applications.

Researchers recommend a reorganization of the medical profession into larger groups with a multispecialty mix. We analyze whether there is evidence for the superiority of these models and if this organizational transformation is underway.

We summarize the evidence on scale and scope economies in physician group practice, and then review the trends in physician group size and specialty mix to conduct survivorship tests of the most efficient models.

The distribution of physician groups exhibits two interesting tails. In the lower tail, a large percentage of physicians continue to practice in small, physician-owned practices. In the upper tail, there is a small but rapidly growing percentage of large groups that have been organized primarily by non-physician owners.

While our analysis includes no original data, it does collate all known surveys of physician practice characteristics and group practice formation to provide a consistent picture of physician organization.

Our review suggests that scale and scope economies in physician practice are limited. This may explain why most physicians have retained their small practices.

Larger, multispecialty groups have been primarily organized by non-physician owners in vertically integrated arrangements. There is little evidence supporting the efficiencies of such models and some concern they may pose anticompetitive threats.

This is the first comprehensive review of the scale and scope economies of physician practice in nearly two decades. The research results do not appear to have changed much; nor has much changed in physician practice organization.

Copula modeling enables the analysis of multivariate count data that has previously required imposition of potentially undesirable correlation restrictions or has limited attention to models with only a few outcomes. This article presents a method for analyzing correlated counts that is appealing because it retains well-known marginal distributions for each response while simultaneously allowing for flexible correlations among the outcomes. The proposed framework extends the applicability of the method to settings with high-dimensional outcomes and provides an efficient simulation method to generate the correlation matrix in a single step. Another open problem that is tackled is that of model comparison. In particular, the article presents techniques for estimating marginal likelihoods and Bayes factors in copula models. The methodology is implemented in a study of the joint behavior of four categories of US technology patents. The results reveal that patent counts exhibit high levels of correlation among categories and that joint modeling is crucial for eliciting the interactions among these variables.

Purpose – The chapter studies gender occupational segregation of rural-urban migrant workers in China based on 2006 survey data from five Chinese cities.

Methodology – The multinomial logit (MNL) model is used to analyze migrant workers' occupational attainment by gender. The Oaxaca–Blinder decomposition method is employed to analyze factors affecting gender occupational segregation, which can be classified into observed factors and unobserved factors, including gender discrimination.

Findings – The index of dissimilarity based on the data shows that gender occupational segregation for migrant workers exists. The result of Oaxaca–Blinder decomposition shows that the unobserved effects account for more than three-fourths of the total gender occupational segregation.

Research limitations – The “index problem” and the assumption of the same occupational preference between men and women of the Oaxaca–Blinder decomposition need to be addressed further.

Social implications – The existing gender equality policies and social protection confined to urban workers should be extended to migrant workers. Increasing training investment in migrant workers is also recommended.

This chapter focused on presenting the result of the Delphi study from the questionnaire distributed to the experts. The Delphi technique was used for modelling the construction supply chain management (CSCM) practice in the fourth industrial revolution (4IR) era. The technique was also used to predict the supply chain management's (SCM) possible trends in the construction industry. A total of 15 experts were selected for this study based on their working experience. The Delphi study also validated the gaps (organisational culture and 4IR component) identified from the existing CSCM model. The findings from the Delphi study revealed that organisational culture has a significant impact on the practice of CSCM in the 4IR era. Regarding adopting the 4IR component for the CSCM in Nigeria, the Delphi study revealed that smart management and virtualisation are the most adopted. Unfortunately, the cyber-physical system, the heartbeat of the 4IR, is yet to be fully implemented for CSCM practice in the Nigerian construction industry.

The purpose of this study is to identify the process of virtual influencer stickiness in the age of influencer marketing, which has received little attention in the literature. This is essential because the research creates a theoretical model of follower loyalty/stickiness to virtual influencer techniques from the standpoint of influencer marketing, which has a substantial effect on the evolution of the global marketing world.

In 2022, 302 people who currently follow an Instafamous virtual influencer took part in an Instagram self-administered online survey.

The findings show that both expertise and trustworthiness have a positive and significant influence on parasocial interaction, which in turn has a significant influence on virtual engagement and stickiness.

This research will specifically assist international readers in understanding how to harness and increase the efficiency and efficacy of interactive marketing strategies and methods to engage and retain followers of Instafamous virtual influencer. Moreover, the findings will be beneficial to opinion leaders, brand managers, company investors, entrepreneurs and service designers.

1. The study pioneers a holistic virtual follower stickiness mechanism that comprises the role of source credibility, parasocial interaction, informational influence and virtual follower’s engagement and their interrelationship to each other.

2. This study is based on parasocial interaction theory and source credibility theory to understand the relationship between virtual followers and influencers stickiness process at social media platforms.

3. In addition, the study examined the subsequent effects of sources of credibility components on parasocial interaction; as well as, on virtual follower engagement and stickiness.

4. This study also categorized and examined the moderating effects exerted by the genres of informative influence of virtual influencer.

The study pioneers a holistic virtual follower stickiness mechanism that comprises the role of source credibility, parasocial interaction, informational influence and virtual follower’s engagement and their interrelationship to each other.

This study is based on parasocial interaction theory and source credibility theory to understand the relationship between virtual followers and influencers stickiness process at social media platforms.

In addition, the study examined the subsequent effects of sources of credibility components on parasocial interaction; as well as, on virtual follower engagement and stickiness.

This study also categorized and examined the moderating effects exerted by the genres of informative influence of virtual influencer.

A major stumbling block in multivariate discrete data analysis is the problem of evaluating the outcome probabilities that enter the likelihood function. Calculation of these probabilities involves high-dimensional integration, making simulation methods indispensable in both Bayesian and frequentist estimation and model choice. We review several existing probability estimators and then show that a broader perspective on the simulation problem can be afforded by interpreting the outcome probabilities through Bayes’ theorem, leading to the recognition that estimation can alternatively be handled by methods for marginal likelihood computation based on the output of Markov chain Monte Carlo (MCMC) algorithms. These techniques offer stand-alone approaches to simulated likelihood estimation but can also be integrated with traditional estimators. Building on both branches in the literature, we develop new methods for estimating response probabilities and propose an adaptive sampler for producing high-quality draws from multivariate truncated normal distributions. A simulation study illustrates the practical benefits and costs associated with each approach. The methods are employed to estimate the likelihood function of a correlated random effects panel data model of women's labor force participation.

This study aims to explore the meanings of solo travel for Asian women, focussing on how Asian women construct and negotiate their identities in the heteronormalised, gendered and Western-centric tourism space.

In-depth interviews were conducted with 35 Asian solo female travellers from ten Asian countries/societies and analysed using constructivist grounded theory. The interpretation was guided by a critical stance and intersectionality lens.

The findings show that solo travel provides a means for self-discovery but the path was different for Asian women, for whom the self is constructed by challenging the social expectations of Asian women. Western-centric discourse was identified in the participants’ interactions with other (Western) travellers and tourism service providers, as well as in the ways these Asian women perceive themselves in relation to Western travellers. In addition to gendered constraints and risks, the findings also reveal the positive meaning of being Asian women in the gendered tourism space.

By labelling Asian women, the study risks adopting an essentialised view and overlooking the differences within the group. However, this strategic essentialism is necessary to draw attention to the inequalities that persist in contemporary tourism spaces and practices.

This study investigated Asian solo female travellers, an emerging but under-researched segment. It provides a critical examination of the intersectional effect of gender and race on identity construction for Asian solo female travellers. This study shows the need for a more inclusive tourism space.

Few studies assess how child abuse and neglect (CAN) affects adolescents’ mental health. Further, the majority of studies conducted to date discount the individual CAN items and report overall prevalence rates for different types of abuse and neglect. The purpose of this study was to examine the levels of and gender differences in CAN subtypes, lifetime prevalence of individual CAN items and the contribution of different CAN subtypes for explaining depression, anxiety and irritability.

The sample included Jamaican (n = 7,182, 60.8% female) and Ugandan (n = 11,518, 52.4% female) youths. The authors used a population-based cross-sectional study design. Youths completed an anonymous survey in school settings.

The authors found gender differences in the levels of CAN subtypes. Maltreatment behaviors of lesser severity were more commonly endorsed by the youths than those of greater severity. Neglect and emotional abuse were the strongest correlates of depression (e.g. neglect: ß = 0.23, among Jamaican youths; emotional abuse outside-the-home: ß = 0.23, among Ugandan girls), anxiety (e.g. neglect: ß = 0.17, among Ugandan girls; emotional abuse outside-the-home: ß = 0.27, among Ugandan girls) and irritability (e.g. emotional abuse in-the-home: ß = 0.17, among Jamaican boys; emotional abuse outside-the-home: ß = 0.17, among Ugandan girls) in most samples.

These findings will inform policymakers and professionals working with youths in Jamaica and Uganda, providing comprehensive contemporary insights beyond existing research in these regions.