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The purpose of this paper is twofold: first, to identify prominent patterns of media use across six media (e.g. television, social media, public libraries) and four gratification contexts (e.g. studying, leisure activities), and second, to investigate whether media use patterns vary with six individual characteristics by introducing the construct of information repertoire.

Data were collected through an online questionnaire completed by 811 adult internet users in the USA. Latent class analysis (LCA), including latent class regression, was performed to analyse the data.

The study found eight information repertoire profiles. The user characteristics associated with each profile, such as age, race and ethnicity, were identified. The profile with the most respondents was characterised by heavy use of TV and the internet for everyday leisure activities. Overall, the eight profiles do not show exclusive use of one or two media (such as a power-law pattern). However, the profiles do exhibit patterned behaviour, in which respondents use the same configuration of media in two or more gratification contexts. These findings suggest some level of gratification-based heuristic in media selection and use when respondents face contexts they deem to be similar.

In conceptual development, the study introduced the construct of information repertoire to capture media use profiles that account for multiple media use across multiple contexts. Methodologically, less-used LCA was applied, which allowed combining the 24 variables (6 media×4 gratification contexts) and the six demographic covariates in a single, unified analysis.

This study examines Pateman's “spillover thesis” that democratic participation in the workplace will “spill over” into political participation. It applies a latent class analysis (LCA) to identify patterns of political behavior and uses workplace participation and political efficacy as predicting variables of political behavior patterns.

This study analyzed the International Social Survey Programme (ISSP) in 2014 General Social Survey (GSS) data. This study applied a LCA to identify distinct patterns in people's political behaviors and did a multinomial regression analysis to predict the patterns with workplace participation and political efficacy.

The study found partial support for the spillover thesis. Among three distinct political behavior patterns, two active patterns were associated with political efficacy. However, the mediation from workplace participation to political participation through political efficacy was not supported. Respondents involved in workplace units that collectively make work-related decisions were more likely to be active in political behaviors, but only one set of political activities. Higher political efficacy was found to lead to more active overall political participation of both patterns.

Unlike the previous studies of democratic spillover, which treated political behaviors either as independent types of behaviors or as a summative index of such binary coded variables, this study addressed such shortcomings of the previous studies by providing a more complex picture of political behavior patterns and their relationship with workplace participation. Future research can build on this unique methodological endeavor to explore a holistic picture of how workplace practices can influence politics and democracy through individual workers.

This paper focuses on patterns of film consumption within cultural consumption more broadly to assess trends in consumerism such as eclectic consumption, individualised consumption and omnivorous/univorous consumption and whether economic background and status feature in shaping cultural consumption. We focus on film because it is widely consumed, online and offline, and has many genres that vary in terms of perceived artistic and entertainment value. In broad terms, film is differentiated between mainstream commercially driven film such as Hollywood blockbusters, middlebrow “feel good” movies and independent arthouse and foreign language film. Our empirical statistical analysis shows that film consumers watch a wide range of genres. However, films deemed to hold artistic value such as arthouse and foreign language feature as part of broad and wide-ranging pattern of consumption of film that attracts its own dedicated consumers. Though we found that social and economic factors remain predictors of cultural consumption the overall picture is more complex than a simple direct correspondence and perceptions of other cultural forms also play a role. Those likely to consume arthouse and foreign language film consume other film genres and other cultural forms genres and those who “prefer” arthouse and foreign language film have slightly more constrained socio-economic characteristics. Overall, we find that economic and cultural factors such income, education, and wider consumption of culture are significant in patterns of film consumption.

Cybercrime is the greatest threat facing law enforcement agencies in England and Wales. Although these crimes are transnational by nature, the burden of response has been placed on line officers. Not all officers, however, believe they are capable of responding to calls involving cybercrime. The current study, using latent class analysis (LCA) on a large sample of English and Welsh officers, finds two types of officers: those prepared (39 percent) and those unprepared (61 percent). Using logistic regression to predict who falls into either classification, the authors find that training and age are the best predictors of latent membership. Implications for policy and future research are discussed. The paper aims to discuss these issues.

In this study, the authors used LCA to determine the number and character of unobserved categories of officers in how they deal with cybercrime.

The LCA indicated there are two distinct categories of police in the English and Welsh constabulary: those prepared (39 percent) and those unprepared (61 percent). Training and age were the two key determinants of this classification.

LCA is an exploratory analysis technique that requires additional validation to confirm the findings of any one study.

The salience of training in helping officers feel prepared to deal with cybercrime cases as well as victims was demonstrated. A full 60 percent of the officers in this study fell in the “unprepared” category, which continues to highlight the limitations of local police to handle cybercrime cases; nevertheless, almost 40 percent of officer could be considered ready when responding to cybercrimes.

As the harm cybercrime brings to our financial and social well-being, law enforcement agencies will be required to improve their response capabilities. Most current cybercrime responses address technical issues related to online fraud and abuse, but officers often perceive the problem as outside their legal and geographic jurisdiction. Knowing how officers perceive cybercrime as well as their own capabilities will allow us to begin changing enforcement policies, training capacity and individual response efficacy.

This study involved a sample of English and Welsh constables and sergeants to classify their cybercrime readiness. The analysis and particular data are unique to the study of cybercrime.

The purpose of this study is to identify latent classes of work values that influence the career choices of Korean workers through a person-centred approach. Because work values may be diverse in individuals, investigating the various combinations of those values will help understand individual's decisions to take, maintain and leave a job.

The authors used a total of 15,103 datasets collected at the national level in South Korea. Data were analyzed by using latent class analysis (LCA); a three-step approach was employed to address classification.

As the results of this study, Class 3, “seeking balanced work values rather than income,” presented the highest level of job satisfaction, whereas Class 1, “seeking job security and income,” exhibited the lowest.

Employing an assessment tool to identify the distinct combinations of work values that individuals possess and then providing them with appropriate training and development programs and customized Human Resource (HR) policies aligned with the classes will be essential tasks for HRD (Human Resource Development)/HRM (Human Resource Management) practitioners.

The effects of the COVID-19 pandemic on cities have transformed the lives of urban societies across the globe. One of such effects has been the redefinition of access and urban mobility patterns, exposing divides and inequalities along the lines of class, gender and social positions. In Latin America, long-term lockdowns and widespread containment-oriented restrictions have deepened already acute conditions of poverty and deprivation. Low-income and socially vulnerable households and individuals in countries such as Colombia find themselves unable, or in a disadvantaged position, to work from home, access goods and services securely and avoid transport modes that increase exposure to contagion. This chapter examines inequalities in urban mobility and access to essential opportunities in urban settings in Colombia, through data collected from 3,900 respondents to a web survey organised during the national lockdown in the country in April 2020. The chapter presents a Latent Class Analysis model exploring how intersecting differences in class, gender, ethnicity, age and other relevant socioeconomic characteristics, influence the degree of adaptability and capacity to adapt to the challenging conditions posed by COVID-19 for physical travel and carrying out everyday activities. Building on three distinct classes of mobility and access-related conditions, the chapter reflects on structural inequalities associated with Colombian cities’ urban form, functional and productive structures and its wide social gaps. The chapter builds on empirical findings to reflect on urban policy and discuss avenues for addressing social and spatial inequalities worsened by the pandemic.

Unsafe behavior is a major cause of safety accidents, while in most management measures for unsafe behavior, the construction workers are generally managed as a whole. Therefore, this study aims to propose group management of construction workers' unsafe behavior considering individual characteristics.

A cognitive process model with ten cognitive factors was constructed based on cognitive safety theory. The questionnaire was developed and validated based on the cognitive model, and the results showed that the questionnaire had good reliability and validity, and the cognitive model fitted well. Latent class analysis was used to classify the unsafe behaviors of construction workers.

Four categories of cognitive excellent type, cognitive failure type, no fear type and knowingly offending type were obtained. Workers of cognitive excellent type have good cognitive ability and a small tendency for unsafe behaviors. Workers of cognitive failure type have poor cognitive ability and the potential for cognitive failure in all four cognitive links. Workers of no fear type have weak cognitive ability, and cognitive failure may occur in discovering information and choosing coping links. Workers of knowingly offending type have certain cognitive abilities, but cognitive failure may occur in choosing coping link.

This study formulates targeted management measures according to the potential characteristics of these four types and provides scientific theoretical support for the personalized management of unsafe behavior.

While school leadership literature has searched for practices with the largest effect on outcomes, we know little about how these behaviors vary by context. Further, recent shifts to include teachers in leadership have prompted a need for purposeful distinction between teacher and principal perceptions and roles. Person-centered statistics offer a means to study differences in how teachers and principals perceive leadership by context, how these perceptions interact, and the extent to which this interaction influences teacher decisions, such as whether or not to remain at their current school. The paper aims to discuss these issues.

This study applies a two-level latent class analysis (LCA) with a cross-level interaction to the 1999-2000 Schools and Staffing Survey (SASS), n=35,560 teachers across n=7,310 US public schools. SASS includes a comprehensive set of leadership measures, not found in other surveys, collected when US schools restructured to include teachers in leadership. Multilevel LCA helps to identify different types of teachers and principals in leadership, the distribution of teacher types across principal types and to test the extent that these types predict teacher retention decisions.

Teacher and principal types were best defined by the survey items that addressed their own role not the role of the other. The highest and lowest responding teacher types were evenly distributed across principal types. Teacher types who reported the lowest principal-directed leadership were more likely to leave their school regardless of principal type.

This study provides evidence for how leadership differs across perceptions and context and, in turn, influences teacher retention.

Using technology to meet national security expectations and requirements is not new. Nations attempt to strike a balance between security and the (expressed or otherwise) privacy needs of citizens. Attacks (physical or cyber) on citizens shift the equilibrium point towards security. In contrast, civil liberties organisations act to preserve or increase privacy. The purpose of this paper is to explore Australian attitudes towards privacy and surveillance during the COVID-19 pandemic. In addition, this paper aims to discover what (if any) factors contribute to societal acceptance of privacy encroachment implicated by surveillance programs.

Data collection occurred during 2021 using a cross-sectional survey comprising a variety of self-assessment questions. In addition, anchoring vignettes were introduced as a means of contextualising complex concepts, i.e. privacy and security. Finally, latent class analysis (LCA) was used to identify homogenous patterns within the data, referred to as “classes” for the analysis of trust.

First, the survey revealed that citizens appear to be unconcerned about surveillance in public and private spaces (although this may be a temporary effect resulting from the pandemic). The potential for identification, however, does raise concerns. Second, LCA surfaced a specific group that were more likely to trust entities and showed less concern about surveillance in society. Finally, even this latter group displayed a “trust deficit” in specific organisations (private businesses and social media firms).

The tension between security and privacy remains, even in a post-pandemic world; therefore, the authors consider that the results, whilst interesting, are preliminary. Notwithstanding this, the findings provide insight into Australian attitudes towards privacy and surveillance and, consequently, provide input into public policy.

This is the most recent survey of the Australian public concerning this issue. The analysis of the effect of the pandemic on attitudes provides further value.

Based on farm diversification's conventional and unconventional nature, the study intends to discriminate different profiles of farm diversification businesses. Furthermore, this study analyses the links between farm diversification efforts, (open) innovation networks as well as the environmental performance (EP) and financial performance (FP) of farms.

A questionnaire was administered through personal interviews with 160 fresh fruit farmers in an inland Portuguese region. Linear regression, latent class analysis (LCA) and multinomial logistic regression were used.

There are significant differences between the levels of diversification, performance and participation in (open) innovation networks of the three classes of farmers discriminated. Different types of diversification efforts and (open) innovation networks influence EP and FP, while FP and R&D projects are associated with the likelihood of being part of a farm diversification class. Moreover, this study shows that innovation networks, promoted by specialized agricultural advisors and R&D projects, are important forms of open innovation in the agricultural sector.

The study contributes to understanding the agricultural sector's diversification efforts and (open) innovation networks and their association with EP and FP. The conventional or unconventional nature of farm diversification was self-reported.

European and local institutions are advised to develop more R&D programs directed to farmers, including environmental and financial issues, besides comprising agricultural and non-agricultural diversification.

This study provides new insights to understand the association between diversification efforts, (open) innovation networks and agricultural businesses' performance.