Search results

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.

Previous research has focused on the outcomes of telework, investigating the advantages and disadvantages of teleworking for employees. However, these investigations do not examine whether there are differences between teleworkers when evaluating the advantages and disadvantages of teleworking. The aim of this study is to identify of distinct classes of teleworkers based on the advantages and disadvantages that teleworking has for them.

This study used secondary survey data collected by the Spanish National Statistics Institute (INE). A sample of 842 people was used for this study. To identify the distinct classes of teleworkers, their perceived advantages and disadvantages of teleworking were analyzed using latent class analysis.

Three different classes of teleworkers were distinguished. Furthermore, sociodemographic covariates were incorporated into the latent class model, revealing that the composition of the classes varied in terms of education level, household income, and the amount of time spent on teleworking per week. This study also examined the influence of these emergent classes on employees’ experience of teleworking.

This study contributes to previous research investigating if telework is advantageous or disadvantageous for teleworkers, acknowledging that teleworkers are not identical and may respond differently to teleworking.

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.

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 this study is to explore how consumers apply clean-eating criteria to a range of food characteristics, and the extent to which individuals are consistent in how they apply clean-eating criteria across products. Further, this study investigates how the clean-eating approach relates to underlying food choice motives.

Data were collected in a consumer survey (n = 666) in Sweden, where participants were prompted about the importance of a set of intrinsic food attributes of the “free-from” and “added” types, for three different food product types (bread, processed meat, ready meals). Data were analyzed using latent class cluster analysis, to explore segments of consumers that place similar importance to the food characteristics and hold similar food choice motives.

Clean eating can be described by two distinctly different attainment strategies: avoiding undesirable characteristics or by simultaneously approaching desirable characteristics. Notably, individuals who apply clean-eating criteria in their food choices strive for healthy, natural and environmentally friendly food, but the clean-by-approach strategy implies a stronger focus on personal health in the form of weight control.

While claims and labels on food packages concerning clean eating are implemented by food manufacturers, it remains unregulated. This study provides information for future regulations on how consumers apply clean-eating criteria, and their motives thereof. Further, the results provide insights food manufacturers regarding motives for clean eating in different consumer segments.

This exploratory research aims to identify the effect of perceived stress level and self-efficacy on management quality and what practices and theories need to be enhanced to improve management quality under volatility business environments.

The study surveyed 291 working women, using the Perceived Stress Scale and the General Self-Efficacy Scale. Latent class analysis (LCA) for classifications of respondents, using categorical observed variables and MANCOVA, are applied to determine the relationship between stress and self-efficacy on the assigned classes.

The study suggests that in a highly volatile business environment, where stress is high, affecting management quality, managers as individuals fall into one of four classes that describe their techniques of coping with the stress, namely Uncommitted Experimenters, Try Anything, Intrinsically Motivated and Externally Motivated. Techniques of stress management classification are significantly related to the combined perceived stress and self-efficacy measures, with Externally Motivated respondents as the classification with a significant mean difference.

The main limitation of the study at hand refers to the sample size versus the number of potential factors of stress. This limitation highlights the need for further data gathering and research in this area, as stress is a critical factor of performance and often ignored in traditional management theories. Another limitation of this study is the lack of in-depth analysis of the use of meditation; its benefits and how to best use this practice in traditional work settings.

The outcome of the study could have significant implications for quality of management in business, private and social sectors by providing meditation as a tool for employees and stakeholders to handle stress in conflict zones.

Using stress management techniques might prove to be a low-cost tool for better quality management of human assets.

The authors study focuses on women in volatile economic turmoil, natural devastations, conflict areas and politically insecure environments. This socioeconomic segment was rarely scrutinized despite its direct effect on a large number of economies hosting a sizeable portion of the world’s population. Interesting potential results highlight the relationship between the respondents in the Intrinsically Motivated class and stress reduction for the benefit of management quality.

Understanding the multifaceted images of tourism destinations is critical for effective destination marketing and management strategies. Traditional approaches, including conceptualization of destination images or analysis of their antecedents and consequences, are commonly used. This study aims to advocate the inclusion of visitors’ latent profiles based on cognitive images to enrich the evaluation and formulation of destination marketing and management strategies.

The analysis focuses on Serbia, an emerging destination, that attracts an increasing number of first-time, repeat and prospective visitors. Exploratory factor analysis and confirmatory factor analysis were used to test the potential dimensions (tangible and intangible cultural destination; infrastructural and accessible destination; active, nature and family destination; sensory and hospitable destination; and welcoming, value for money (VFM) and safe destination) of the cognitive destination image factors scale while subtypes (profiles) were obtained using latent profile analysis (LPA).

The cognitive image component encompasses the perceived attributes of a destination, whether derived from direct experience or acquired through other means. The study identified the following profiles: conventional destination; sensory and hospitable destination; welcoming, VFM and safe destination; secure and active family destination and accessible cultural destination, which are presented individually with their sociodemographic assets.

The main contribution of the paper is the application of a novel method (LPA) for profiling visitor segments based on cognitive destination image. From a theoretical perspective, this research contributes to the extant body of literature pertaining to the destination image, thereby facilitating the identification of discrete latent visitor segments and elucidating noteworthy differences among them concerning a cognitive image.

The purpose of this study is to determine the influence of project critical success factors (CSFs) on change management in the context of business process management (BPM). Despite widespread interest in BPM, the existing literature is insufficient in addressing the antecedents that contribute to change management in business process projects.

Key factors of change management success in BPM projects were initially identified in a systematic literature review (SLR) and were used as antecedents of change management through a structural equation modeling (SEM) with 464 business project stakeholders. Next, a neural network analysis allowed the key factors to be ranked non-linearly. Finally, a latent class analysis (LCA) was performed to determine the sample's heterogeneous groups based on their project management characteristics.

Project management, top management support and technological competencies were the main CSFs identified as having positive effects on change management. The most important factor is project management, followed by top management support, which plays a crucial mediating role in enabling change management. Although relevant, technological competencies were secondary in the study. Regarding project management CSF, four heterogeneous classes of individuals were determined.

Although this study provides an opportunity to observe CSFs, it does not address the need to analyze the phenomenon in different classifications of projects, regarding maturity, complexity, project management approach and other aspects that differentiate projects in a meaningful way.

The study allows practitioners to understand the critical factors underlying change management and take necessary actions to manage it, recognizing that individuals have heterogeneous profiles regarding project management.

This study pioneeringly discusses the CSFs of change management BPM projects to enable successful change management, ranking the main factors and mapping heterogeneous profiles.

This research aims to replicate the work of Oberholster et al. (2013) on expatriation motivation through a generalization and extension replication. Additionally, it aims to contribute to the Self-Initiated Expatriates (SIEs) literature by studying the Basic Psychological Needs (BPNs) of SIEs as proposed by the Self-Determination Theory (SDT).

This research used Latent Class Analysis (LCA) with covariate estimation to create five clusters based on survey data from 179 SIEs. Additionally, the replication procedure followed recommendations by Dau et al. (2022) to produce a constructive replication.

Besides validating clusters in the original study, one new cluster was found. Furthermore, identifying the BPNs of the clusters helped in understanding the mechanism that motivates them.

By studying the BPNs as per the SDT, this research contributes to our understanding of the psychological factors that shape expatriates' motivations and experiences. This can inform the knowledge developed in the international mobility theories and the models related to SIEs' psychological well-being.

Building on the results of this research, organizations can tailor recruiting and retaining strategies to the specific BPNs of different SIEs groups. Organizations can motivate SIEs, enhance their job satisfaction and loyalty, predict their success, and support their psychological well-being.

A generalization and extension replication value lies in testing the validity and reliability of previous findings in new contexts. The originality in this research stems from its utilization of the BPNs from SDT to explain SIEs' motivation and evaluate their psychological well-being.

This study aims to advance the understanding on individual variations in PhD candidates’ personal interest in their doctorate and supervisory and research community support, and several individual and structural attributes potentially having an impact on the profiles.

The authors explored the interrelationship between personal interest – social support profiles, and nationality, gender, research group and study status and the risk of dropping out. A total of 768 PhD candidates from a research-intensive university in Finland responded to a modified version of the cross-cultural doctoral experience survey. Latent profile analysis was used to explore the individual variations in PhD candidates’ interest and support from the supervisor and research community.

Three distinctive PhD interest-social support profiles were detected; the high interest–high support profile (74.4%, n = 570), the high interest–moderate support profile (18.2%, n = 140) and the moderate interest–moderate support profile (7.4%, n = 56). The profiles exhibited high to moderate levels of research, development and instrumental interest. Individuals in the high interest–moderate support and in the moderate interest–moderate support profiles were more prone to consider dropping out from their PhD than in the high interest–high support profile.

The results indicate that by cultivating PhD candidates’ interest and providing sufficient supervisory and the research community offers a means for preventing candidates from discontinuing their doctorate. Hence, building a supportive learning environment that cultivates a PhD candidate’s personal interest is likely to reduce high dropout rates among the candidates.