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On many occasions, organizational science research has been referred to as fragmented and disjointed, resulting in a literature that is, in the opinion of many, difficult to navigate and comprehend. One potential explanation is that scholars have failed to comprehend that organizations are complex and intricate systems. In order to move us past this morass, we recommend that researchers extend beyond traditional rational, mechanistic, and variable-centered approaches to research and integrate a more advantageous pattern-oriented approach within their research program. Pattern-oriented methods approximate real-life phenomena by adopting a holistic, integrative approach to research wherein individual- and organizational-systems are viewed as non-decomposable organized wholes. We argue that the pattern-oriented approach has the potential to overcome a number of breakdowns faced by alternate approaches, while offering a novel and more representative lens from which to view organizational- and HRM-related issues. The proposed incorporation of the pattern-oriented approach is framed within a review and evaluation of current approaches to organizational research and is supplemented with a discussion of methodological and theoretical implications as well as potential applications of the pattern-oriented approach.

The authors seek (1) to identify the profiles of subjective financial well-being (SFWB) of bank customers before and during the coronavirus disease 2019 (COVID-19) pandemic, (2) to analyze the transition to profiles of lower SFWB during the pandemic and (3) to identify the factors driving such transitions.

The authors surveyed five countries during 2019 and 2020 to measure SFWB. The authors applied latent class analysis (LCA) to identify profiles of bank customers according to a mix of SFWB indicators in pre-pandemic times (Study 1). The authors validated the profiles during the pandemic and identified the SFWB dimensions that deteriorated during the crisis (Study 2). Finally, the authors applied latent transition analysis (LTA) to explore transitions to profiles of lower SFWB and identify the drivers.

The authors identified three profiles of customers in pre- and post-pandemic periods for four dimensions of SFWB: control over finances, capacity to absorb financial shocks, ability to track financial goals and financial freedom. Gender, age, trust in banks and bank-supporting policies were related to transitions across profiles of SFWB during the pandemic. These relationships are contingent upon contextual country-related variables.

Banks and policymakers should reduce customers' exposure to the pandemic's long-lasting adverse effects on SFWB and should identify and control the multiplier role that contextual variables play.

Extant literature has not fully identified the dimensions of SFWB that changed due to the COVID-19 pandemic. The authors narrow this gap by identifying three SFWB profiles of customers, analyzing the patterns of SFWB change and connecting these changes to individual, provider and contextual factors.

The purpose of the paper is to examine how psychological characteristics predict membership of and transitions between states of higher vs lower financial vulnerability – and vice versa – over time.

This research uses a dynamic latent class model (latent transition analysis) to explore the dynamics of consumers’ financial vulnerability over time using longitudinal data obtained by repeatedly administering a measure of financial vulnerability.

This research finds that consumers in a state of lower vulnerability are “fragile” in having a relatively high likelihood of moving to a state of higher vulnerability, whereas those in a state of higher vulnerability are “entrenched” in having a relatively low likelihood of moving to a state of lower vulnerability. This pattern of results is called the “financial vulnerability trap.” While financial self-efficacy explains state membership, the consideration of future consequences drives state transitions.

Future research could follow consumers over a longer period and consider the role of alternative psychological characteristics besides those examined.

This research provides practitioners with actionable insights regarding the drivers of changes in consumers’ financial vulnerability across time, showing the value of financial self-efficacy and the consideration of future consequences when developing strategies to prevent consumers from sliding from a state of lower to higher financial vulnerability over time.

There is scant research on financial vulnerability. Further, prior research has not examined whether and how consumers’ psychological characteristics help explain their membership of and transitions between states of different levels of financial vulnerability over time.

The idea that criminal behavior is a function of the offender's personality, also called the Homology hypothesis, has a long history in forensic psychology and criminology. This assumption, however, has been decried as lacking empirical support. In spite of much social concern relative to sexual offenses, there is virtually no research looking at the stability of offending pattern in sex offenders of adult women. This paper aims to fill some of the gaps.

Latent structure analyses were conducted on a secondary dataset including 145 serial rapists. A cross‐sectional, discrete time‐series design was used including a sequence of three offenses.

Moderate support was found for the three main assumptions underlying the Homology hypothesis. Offenses tended to share a relatively similar underlying structure, with the victimology and aggression components being more prominent than the sexual dimension. The three primary profiles identified, labeled “Passive”, “Stranger‐aggressive”, and “Antisocial”, were found to be about 50 percent stable across the sequence. Finally, the presence of significant dysfunction in the family of origin predicted membership in the “Antisocial” class, as well as increased the specificity and stability of this profile. The presence of early maladjustment was not related to any of the states.

Based on the results, it is proposed that future research incorporates contextual‐environmental elements in order to increase the validity of the findings.

This study represents a unique attempt at documenting patterns of stability and variations across incidents of rape, using an institutional sample. Furthermore, it illustrates the use and potential benefits of latent structure models in criminological research.

Behavioural change practice has focussed attention on understanding behaviour; failing to apply dynamic approaches that capture the underlying determinants of behavioural change. Following recommendations to direct analytical focus towards understanding both the causal factors of behaviour and behavioural change to enhance intervention practice, this paper aims to apply a hidden Markov model (HMM) approach to understand why people transition from one state to another (e.g. reporting changes from wasting food to not wasting food or vice versa).

Data were drawn from a 2017 food waste programme that aimed to reduce waste of fruit and vegetables by increasing self-efficacy through a two-week pilot, featuring recipes and in-store cooking demonstrations. A repeated measure longitudinal research design was used. In total, 314 households completed a phone survey prior to the two-week pilot and 244 completed the survey in the weeks following the intervention (77% retention in the evaluation study).

Two behavioural states were identified, namely, fruit and vegetable (FV) wasters and non-FV wasters. Age was identified as a causal factor for FV food wasting prior to the campaign (45-54 years were most likely to waste FV). Following the intervention, a total of 43.8% transitioned away from FV wasters to non-wasters, and attitudes and self-efficacy were indicated as potential causal factors of this change in FV waste behaviour.

Through this application, it is demonstrated how HMM can identify behavioural states, rates of behaviour change and importantly how HMM can identify both causal determinants of behaviour and behavioural change. Implications, limitations and future research directions are outlined.

The methodological discourse of mixed-methods research offers general procedures to combine quantitative and qualitative methods for investigating complex fields of research such as higher education. However, integrating different methods still poses considerable challenges. To move beyond general recommendations for mixed-methods research, this chapter proposes to discuss methodological issues with respect to a particular research domain. Taking current studies on the transition to higher education as an example, the authors first provide an overview of the potentials and limitations of quantitative and qualitative methods in the research domain. Second, they show the need for a conceptual framework grounded in the theory of the research object to guide the integration of different methods and findings. Finally, an example study that investigates transition with regard to the interplay of the individual student and the institutional context serves to illustrate the guiding role of theory. The framework integrates different theoretical perspectives on transition, informs the selection of the research methods, and defines the nexus of the two strands that constitute the mixed-methods design. As the interplay of individual and context is of concern for teaching and learning in general, the example presented may be fruitful for the wider field of higher education research.

The purpose of this study is to identify latent profiles based on 3 dimensions of organizational commitment (OC) using 14 Korean samples.

This study used unpublished raw data. Allen and Meyer’s (1996) measurement was used to maintain consistency and facilitate comparison across samples. To determine the number of latent profiles that exist in Korea based on employees’ level of OC, a latent profile analysis (LPA) was performed.

The findings showed that there are two or three profiles (i.e. fully committed, weakly committed and/or moderately committed) across various types of organizations in Korea. These findings are similar to those based on LPA conducted in the West. The number of profiles is more limited in Korean samples than it is in Western samples. Like Western studies, this Korean-focused study identified fully committed, weakly committed and moderately committed profiles, but it did not show any other types of profiles found in the Western sample.

Based on these results, this study suggests academic and practical implications for researchers and practitioners.

Based on the job demands and resources (JD-R) model and conservation of resources (COR) theory, this paper aims to develop and test a model that examines the moderating role of daily remote work hours and the mediating role of work–family conflict on the effects of excessive workload and time pressure on life satisfaction due to mandatory remote work arrangements.

Hierarchical regression analysis was used to analyze data from 400 professionals working in the IT sector in Turkey. Scales developed by previous researchers were used to measure excessive workload, time pressure, work–family conflict and life satisfaction. While these four variables were measured with 19 statements, daily remote work hours were determined with a single question. The collected data were validated using confirmatory factor analysis, and the hypotheses were tested using structural equation modeling. Furthermore, the reliability and validity of the data were confirmed. Finally, PROCESS was applied to examine moderated mediation.

According to the analysis results obtained from the above sample data, daily remote work hours moderate the mediating role of work–family conflict in the relationships between (1) excessive workload and life satisfaction and (2) time pressure and life satisfaction. In other words, the findings show that job-related demands arising from workload, time pressure and remote work hours prevent employees from meeting their family obligations, thereby increasing work–family conflict and ultimately affecting life satisfaction.

The study can help employers, managers, human resource professionals, policymakers and researchers increase employees' life satisfaction due to the changes in job demands experienced by employees in companies that have transitioned to remote work practices. It can provide new approaches for dealing with dissatisfaction arising from work-related conflicts in Turkey's changing environment. The results can greatly facilitate the Turkish companies' efforts to create more innovative work arrangements and make an outstanding contribution to improving employee performance in Turkey's transition to remote work practices by focusing on reducing workload, time pressure and long working hours and creating employee-centered remote work models.

As per World Health Organization, the world will face frequent pandemic in the coming years, and thus organizations should be aware of remote work practices that will become widespread. This study provides a new perspective on the impact of employees' changing job demands on work–family conflict and life satisfaction during organizations' transition to new work arrangements in the face of the social crisis created by the COVID-19 pandemic. The study also contributes to closing the research gap between job demands, work–family conflict and life satisfaction.

Learning management systems (LMS) provide detailed information about the processes through event-logs. Process and related data-mining approaches can reveal valuable information from these files to help teachers and executives to monitor and manage their online learning processes. In this regard, the purpose of this paper is to present an overview of the current direction of the literature on educational data mining, and an application framework to analyze the educational data provided by the Moodle LMS.

The paper presents a framework to provide a decision support through the approaches existing in process and data-mining fields for analyzing the event-log data gathered from LMS platforms. In this framework, latent class analysis (LCA) and sequential pattern mining approaches were used to understand the general patterns; heuristic and fuzzy approaches were performed for process mining to obtain the workflows and statistics; finally, social-network analysis was conducted to discover the collaborations.

The analyses conducted in the study give clues for the process performance of the course during a semester by indicating exceptional situations, clarifying the activity flows, understanding the main process flow and revealing the students’ interactions. Findings also show that using the preliminary data analyses before process mining steps is also beneficial to understand the general pattern and expose the irregular ones.

The study highlights the benefits of analyzing event-log files of LMSs to improve the quality of online educational processes through a case study based on Moodle event-logs. The application framework covers preliminary analyses such as LCA before the use of process mining algorithms to reveal the exceptional situations.

Entrepreneurial passion has important implications for entrepreneurial success and psychological well-being. But their connections are complicated by the fact that three entrepreneurial passions (passion for inventing, passion for founding and passion for developing) can be combined differently according to their level and shape difference. A variable-centered approach cannot explain their relationship very well, by only focusing on the level difference and ignoring the different combination of entrepreneurial passion in subpopulations. The purpose of this study is to explore the function of entrepreneurial passion on entrepreneurial success and psychological well-being from a person-cantered approach.

In this study, the authors conducted latent profile analyses to identify different configurations of different entrepreneurial passions (passion for inventing, passion for founding, passion for developing) on two samples of Chinese students and entrepreneurs. Then in the sample of Chinese entrepreneurs, the authors utilized the DCON command in Mplus to provide comparisons among the profiles on entrepreneurial success and psychological well-being.

Based on identity theory, the authors found four entrepreneurial passion profiles across two samples—fully passionate, action-driven, interest-driven and dispassionate. Furthermore, the authors found that fully passionate entrepreneurs showed the highest level of entrepreneurial success, followed by action-driven, and then by interest-driven and dispassionate showed the lowest level. Action-driven entrepreneurs experienced the highest level of psychological well-being, followed by fully passionate entrepreneurs, then by interest-driven and dispassionate.

The results provide new insights into the nature and influence of entrepreneurial passion on entrepreneurial success and psychological well-being from a person-centered perspective.