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The purpose of this paper is to examine the number and nature of latent classes of delinquency that exist among male juvenile offenders incarcerated in prisons in Pakistan.

The sample consisted of 415 young male offenders incarcerated in prisons in Khyber Pakhtunkhwa (KPK) Pakistan. Latent class analysis was employed to determine the number and nature of delinquency latent classes. Multinomial logistic regression was used to estimate the associations between latent classes and the three factors of criminal social identity (cognitive centrality, in-group affect, and in-group ties) whilst controlling for criminal friends, period of confinement, addiction, age, and location.

The best fitting latent class model was a three-class solution. The classes were labelled: “minor delinquents” (the baseline/normative class; Class 3), “major delinquents” (Class 1), and “moderate delinquents” (Class 2). Class membership was predicted by differing external variables. Specifically, Class 1 membership was related to having more criminal friends; while Class 2 membership was related to lower levels of in-group affect and higher levels of in-group ties.

Findings are discussed in relation to refining current taxonomic arguments regarding the structure of delinquency and implications for prevention of juvenile delinquent behaviour.

First, most previous studies have focused on school children, whereas, this paper focuses on incarcerated juvenile offenders. Second, this research includes delinquents from Pakistan, whereas, most previous research has examined delinquent behaviour in western cultures.

We discuss adoption as a diverse family structure in America. Adoption has existed in some form throughout the history with the portrayal varying by historical epoch. Adoption has been both disparaged and idealized to perpetuate the interest of elite players. This chapter discusses adoption in terms of the changing demographic which 21st century families face. In this manuscript, we first discuss the history of adoption in the United States including its impact as social control of premarital sex. Then the three players in the adoption triad are discussed and analyzed. Finally, we highlight how demographics of race, class, gender, and sexuality impact the adoption experience by 21st century families. Specifically, we explore the recent National Survey of Adoptive Parents from the United States Center for Disease Control and look at the modern adoption experience

Under investigation is Prosecco wine, a sparkling white wine from North‐East Italy. Information collection on consumer perceptions is particularly relevant when developing market strategies for wine, especially so when local production and certification of origin play an important role in the wine market of a given district, as in the case at hand. Investigating and characterizing the structure of preference heterogeneity become crucial steps in every successful marketing strategy. The purpose of this paper is to investigate the sources of systematic differences in consumer preferences.

The paper explores the effect of inclusion of answers to attitudinal questions in a latent class regression model of stated willingness to pay (WTP) for this specialty wine. These additional variables were included in the membership equations to investigate whether they could be of help in the identification of latent classes. The individual specific WTPs from the sampled respondents were then derived from the best fitting model and examined for consistency.

The use of answers to attitudinal question in the latent class regression model is found to improve model fit, thereby helping in the identification of latent classes. The best performing model obtained makes use of both attitudinal scores and socio‐economic covariates identifying five latent classes. A reasonable pattern of differences in WTP for Prosecco between CDO and TGI types were derived from this model.

The approach appears informative and promising: attitudes emerge as important ancillary indicators of taste differences for specialty wines. This might be of interest per se and of practical use in market segmentation. If future research shows that these variables can be of use in other contexts, it is quite possible that more attitudinal questions will be routinely incorporated in structural latent class hedonic models.

Outsourcing of accounting increasingly attracts research interest, but research concerning the impact of the benefits of outsourcing on firm capabilities and performance across firms remains limited. This paper aims to reveal the unobservable latent classes of firms that outsource their accounting functions by testing a research model concerning the topic.

The authors build on accounting outsourcing research and adapt a research model from the literature on business services outsourcing. The authors analyze the data from 261 small and medium-sized enterprises in Europe using finite mixture structural equation modeling (FMSEM) and additional methods.

The authors reveal three latent classes with different research models. Thriving outsourcers (N = 103) have a positive attitude toward accounting outsourcing and associate competitive capabilities with mediating the relationship from outsourcing benefits to firm performance. Annoyed outsourcers (N = 143) are dissatisfied with their accounting service provider and only associate outsourcing benefits with competitive capabilities. Convenient outsourcers (N = 15) feel comfortable with their current accounting service provider and associate outsourcing benefits with neither capabilities nor with firm performance.

The study initiates the discussion about the unobservable heterogeneity among accounting outsourcers. The study introduces the use of the FMSEM method in accounting outsourcing research.

The study offers novel insights concerning accounting outsourcers and proposes original explanations for their outsourcing decisions that would help both the outsourcers and accounting service providers.

The study might be the first to categorize accounting outsourcers using FMSEM.

Discusses and empirically tests special cases of multiple‐chain mixed Markov latent class models with business data. The switches between negative and positive changes in earnings‐per‐share of firms are captured by alternative Markov models. The estimated response probabilities and state transition probabilities show interesting changes in the transformation patterns of the firms over time. Shows that Markov models can be valuable tools in predicting switches in profitability of firms.

This article addresses simultaneously two important features in random utility maximisation (RUM) choice modelling: choice set generation and unobserved taste heterogeneity. It is proposed to develop and to compare definitions and properties of econometric specifications that are based on mixed logit (MXL) and latent class logit (LCL) RUM models in the additional presence of prior compensatory screening decision rules. The latter allow for continuous latent bounds that determine choice alternatives to be or not to be considered for decision making. It is also proposed to evaluate and to test each against the other ones in an application to home-to-work mode choice in the Paris region of France using 2002 data.

The purpose of this paper is to investigate the effectiveness of a job resources-based intervention aimed at proactively increasing work engagement and team innovativeness during organizational restructuring using a person-centered approach.

The intervention was conducted in two organizations: two departments served as participants (n=82) and two as controls (n=52). The aim was to first identify sub-groups of employees with different developmental patterns of work engagement, and then to determine whether these sub-groups benefited differently from the intervention with respect to team innovativeness and work engagement.

Latent profile analysis identified three different patterns of work engagement among the participants: high and stable (n=64), moderate and decreasing (n=13), and low and decreasing (n=5). The χ²-test yielded no significant difference between participants and controls (n=52) with respect to team innovativeness over time. However, t-tests showed that team innovativeness increased in the high work engagement class and somewhat decreased in the moderate and low work engagement classes.

During organizational changes, those initially work-engaged seem to be able to proactively build their team innovativeness via a job resources-based intervention and remain engaged; whereas those initially not work-engaged may not, and their work engagement may even decrease.

This study reveals that an initial level of work engagement is a prerequisite why some employees profit more from a job resources-based intervention than others and provides tailored knowledge on the effectiveness of the intervention.

The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.

Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.

Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.

The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.

This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.

This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.

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.

While it is incontestable that eating in restaurants leads to a higher energy intake than eating at home, this paper explores the even more environmentally relevant connection between meat intake and the location of eating.

Based on secondary data from the US National Health and Nutrition Examination Survey (NHANES), the authors apply a latent class model (LCM), combining latent profile analysis (LPA) and regression analysis. Different (latent) consumer classes are modeled based (1) on share of meat consumption and (2) share of eating out by means of LPA, while class-specific socio-demographic characteristics are estimated by means of ordered logistic regression.

Results of the LPA reveal four (latent) consumer classes with regard to the share of meat consumption and the share of eating out. One class consists mostly of male meat lovers with a high share of eating out, which, however, only represents 7% of the sample. A much larger class represents an affluent social group that consumes the majority of food outside of the home but does not consume significantly more meat than the large group of moderates who mostly eat at home. The fourth class mostly consists of children with a very low intake of meat.

By applying a LCM, the authors shed some light on the relation between meat consumption and eating out. The authors demonstrated that commonly assumed relations, such as men eating more meat than women, do not necessarily apply. Similar findings apply to factors potentially influencing meat consumption, such as education, marital status and income.