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Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).

The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.

In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.

The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.

This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.

Research suggests that children in Hong Kong are at an elevated risk of emotional problems. Authoritarian parenting, a common parenting style in Hong Kong, is a critical factor associated with childhood mental health problems. The purpose of this paper is to evaluate the effectiveness of the 6As Positive Parenting Program (6As) in modifying parenting attitudes, reduction of parenting stress and increasing self-efficacy in positive parenting, among a sample of 82 Hong Kong parents. 6As focuses on prevention by instilling positive parenting beliefs and principles, thereby reducing reliance on authoritarian and related parenting styles.

The program was evaluated using a controlled pre-post-treatment design. Outcome measures were the Chinese Child-rearing Beliefs Questionnaire, Parental Stress Scale, Parenting Self-efficacy Scale and participant feedback. ANOVA and correlation were utilized to detect treatment effects and relationships between the degree of change among measures and subscales.

Relative to the control group, the 6As Positive Parenting Program significantly changed parents’ parenting attitudes, reduced parenting stress and increased self-efficacy in positive parenting. In sum, 97.6 percent of the participants agreed that the program is a good fit for the Hong Kong culture.

A larger sample would have been desirable for this study. One factor that limited analyzable data was that some of the participating organizations enrolled participants into the program who did not meet research inclusion criteria. Furthermore, the size of groups varied from 5 to 16 participants, which may have produced different group dynamics that added variability to outcomes. Future 6As parenting program research should attempt to standardize group size or to directly compare the effectiveness of smaller vs larger groups. Furthermore, as noted earlier, the research was conducted during the primary school application period, which may have heightened the parenting stress for parents of younger children.

The results suggest that an enhanced belief in authoritative, autonomy and training strategies could reduce parental stress and shift parents’ attitude toward a more positive approach in child-rearing.

There is considerable need for a holistically designed parenting training that is culturally credible and sensitive.

Findings suggest that positive parenting can enhance the parent–child relationship and reduce parental stress. The results support governmental, non-governmental organizational and community focus on positive practices for parenting training in Hong Kong.

Considering the relevance of understanding what influences environmentally sustainable consumer choices, the present study aims to examine and synthesize the key determinants factors from literature and outline a new conceptual framework for explaining green purchasing behaviors (GPBs).

A bibliometric analysis was conducted on 161 articles extracted from Web of Science and Scopus databases, which were systematically evaluated and reviewed, and represent the current GPB knowledge base. Content analysis, science mapping and bibliometric analysis techniques were applied to uncover the major theories and constructs from the state-of-the-art.

The evolving debate between altruistic and self-interest consumer motivations reveals challenges for rational-based theories, as most empirical applications are not focused on buying behaviors, but instead either on pro-environmental (non-buying) activities or on buying intentions. From the subset of leading contributions and emerging topics, nine thematic clusters are unveiled in this investigation, which were combined to create the new PSICHE framework with the purpose of predicting GPB: (P)roduct-related factors, (S)ocial influences, (I)ndividual factors, (C)oncerns about the environment, (H)abits and (E)motions.

By uncovering the multiple intervening factors in GPB decision processes, this study will assist practitioners and academics to move forward on how to foster more sustainable consumer behaviors.

The present study provides readers a summary of an unprecedentedly broad collection of papers, from which the key themes are categorized, the domain's intellectual structure is captured and an actionable framework for enhancing the understanding GPB is proposed. Four new thrust areas and a set of future research questions are included.

Studies of entrepreneurial intentions (EIs) have become increasingly common, informed usually by Ajzen’s (1991) theory of planned behaviour (TPB). Although the TPB postulates that beliefs determine EIs, the contents of the beliefs have not been properly studied, leaving EIs’ cognitive underpinnings and cognitive approaches to influencing EIs unclear. To clarify the TPB/EI-belief nexus, the study examines the conceptual background of entrepreneurial cognitions and elicits the beliefs of a group of nascent micro entrepreneurs (NMEs) to compare them with their TPB attitudes and EIs, facilitating assessing their mutual consistency as implied by the TBP.

The respondents are entrepreneurial novice clients of a micro business advisory organisation. Their TPB attitudes and EIs were measured using standard TPB/EI methods. Comparative causal mapping (CCM) combined with semi-structured interviewing was used to reveal the NMEs’ typical belief systems, presented as aggregated cause maps.

The NMEs have uniform, relatively detailed belief systems about entrepreneurship and micro business. The belief systems are consistent with theory- and context-based expectations and logically aligned with the NMEs’ expressed TPB attitudes and EIs. CCM provides an accessible method for studying contents of entrepreneurial cognitions.

It was not possible to study “entrepreneurship-negative” respondents or the intensity or origins of some specific beliefs.

Diagnosing and better understanding beliefs can benefit entrepreneurship education and development, in general or connected with TPB/EI studies.

The study reveals entrepreneurial belief systems systematically, evidently not done before generally or in terms of “everyday” micro entrepreneurship or TPB. It clarifies and supports the TPB notion that beliefs underpin actors’ attitudes and intentions.

Football exists and evolves in a dynamic ecosystem, displaying a massive and multidimensional influence on most contemporary societies, and football has grown into a significant industry with a plethora of stakeholders. This research is the first to comprehensively identify the key industry stakeholders and their distinct value, from the individual club perspective, and to conceptualise and test their interrelationship toward the development of a corresponding framework of club benefits.

The study applied a multilevel approach to collect and verify qualitative data. It initially developed a preliminary conceptual framework, which was first validated by an expert panel and was subsequently extensively tested in the Cyprus-specific context, which offered fertile ground for such a study. The empirical stage rested on 41 semi-structured, face-to-face interviews with very high-ranking individuals from the top nine football clubs, as well as with key industry stakeholders.

Though the examined industry is partly in line with international norms, it is also highly affected by unique characteristics that alter the various stakeholders' role, producing (even negative) value of varied typologies that is directly linked with the industry's financial, sporting, cultural and social conditions.

The research ultimately presents scholars, practitioners and policymakers with a systemic and comprehensive understanding of the individual club stakeholder value offerings, delivers a tested framework as a tool for social and business management and prescribes future avenues for research, governance and practice.

Extant studies on the subject are either partial or focus on individual stakeholders and evidently lack requisite scientific comprehensiveness. The current research bridges this significant gap in knowledge by exhaustively identifying the key industry stakeholders, explicating their relative social, economic or other value in the individual club perspective and developing a value-based stakeholder framework.

German (corporate-) real estate management departments have been facing the challenge of poor data quality for years. This holds them back from generating efficiency potentials via the use of new methods from the field of digitalisation and from coping with the increasing requirements from the ESG context. The purpose of this paper is to explore why German (corporate-) real estate managements (do not) share data with their real estate service providers to address the data quality challenge and identify possible solutions.

To answer the research question, the reasoned action approach, an established theory from psychology for predicting human behaviour, is used. The relationships between the constructs are determined using linear regression. The study participants are almost exclusively from Germany.

The organisational milieu (perceived behavioural control) has a significant impact on the behaviour of sharing data with real estate service providers. Especially the change of contractual arrangements (data-driven contracts) seems to be crucial for the improvement of information logistics.

To the best of the author’s knowledge, for the first time, the reasoned action approach is used within the German real estate industry to predict organisational behaviour in the context of digitalisation.

This paper aims to explore how leaders can develop value-based leadership for sustainable quality development in Lean manufacturing.

A qualitative meta-analysis was conducted using data from a three-year study of Lean manufacturing in Sweden using the Shingo business excellence model as an analytical framework.

This study demonstrates that leaders can develop value-based leadership to support Lean manufacturing by defining and articulating the organization’s values and accompanying behaviors that are needed to support the strategic direction; creating forums and time for leaders to identify the why behind decisions and reflect on their experiences to be able to lead a transformative process; and using storytelling to create a coaching culture to connect values and behaviors, to the processes and systems of work.

This paper contributes insights for developing value-based leadership to support a systemic approach to sustainable quality development in lean manufacturing. Findings are based on a limited case sample size of three manufacturing companies in Sweden.

The findings were derived using a unique methodological approach combining storytelling, appreciative inquiry and coaching with traditional data collection methods including surveys and interviews to identify, define and shape value-based leadership in Lean manufacturing.

The purpose of this paper is to supply an in-depth description of the educators’ values, beliefs and confidence changing from a traditional learning environment to a learning environment integrating technology.

The descriptive case study design was employed using descriptive statistical analysis and inductive analysis on the data collected.

Themes on a high level of confidence, the importance of professional development and training, self-motivation, and excitement about the way technology can enhance the learning, along with concerns over the lack of infrastructure and support for integrating technology, and about the ability of students to use the technology tools for higher ordered thinking surfaced.

Additional research may include a more diverse population, including educators at the kindergarten to high school level. Another recommendation would be to repeat the study with a population not as vested in technology.

A pre-assessment of the existing values, beliefs and confidence of educators involved in the change process will provide invaluable information for stakeholders on techniques and strategies vital to a successful transition.

To effectively meet the learning styles of Generation Z and those students following, educators need be able to adapt to quickly changing technology, be comfortable with students who multitask and be open to technology-rich teaching and learning environments.

This study filled a gap in the literature where little information on the humanistic challenges educators encounter when integrating technology into their learning environment providing insights into the values, beliefs and level of confidence of educators experiencing change.

Migrants play an essential role in economic and societal outcomes of the host society, both as members of the workforce and as citizens. However, integration and finding employment after migration remain critical issues. The purpose of this paper is to employ an evidence-based quantitative approach to identify migrant workers’ most important qualifications from an employer perspective and to explore factors that influence employer perception of migrants.

This study uses European Social Survey data that contain responses from managers in European countries in 2014 (n=2,828) and 2016 (n=3,014). Confirmatory factor analysis and structural equation modelling are used to analyse the data.

For managers, migrants’ commitment to the host country’s way of life is more important than their job skills, educational level and language proficiency. The effects of managers’ individual characteristics, including demographics, expectancies and personal values, on their general attitude towards migrants are also quantified.

The study’s outcomes can assist migrants to develop the qualifications most valued by employers, and allow policymakers to integrate the organizational perspective into policies and initiatives for integration of migrant labour.

Through HR practices, organizations significantly affect migrants’ career outcomes. Yet research on migrant workers from an organizational and managerial perspective is limited. This study identifies migrant workers’ most important qualifications from an employer perspective. It also explores which individual characteristics most influence organizational decision-makers’ perception. Utilizing a cross-cultural and longitudinal data set provides a unique opportunity to generate generalizable findings.

The diversity of perspectives means that one can find many factors and models of proenvironmental behavior. However, they typically suffer from limitations and varying degrees of validity in specific contexts, suggesting that today the prime goal should be to learn and improve the models which have been already developed. In this study, the authors build on the model for predicting proenvironmental behavior developed by Oreg and Katz-Gerro (2006), namely one of the most comprehensive cross-national proenvironmental behavior models and one of the few not to be limited to either a local or single-country context or specific proenvironmental behavior.

By using the statistical matching technique, the authors merged data from two existing databases without common identifiers – the International Social Survey Program (environmental module) and the European Social Survey (Round 5). The resulting multinational data concerning 9,710 observations enabled a replication with extensions of Oreg and Katz-Gerro's (2006) proenvironmental behavior model that incorporates newly added Schwartz's theory of human values. To achieve the study's main objective, that is, to present improvements to the original model of proenvironmental behavior, the authors used structural equation modeling (SEM) procedures to estimate four competing models in the R program.

This study implies that Schwartz's individually measured motivational types of values (benevolence [BE], universalism [UN], self-direction [SD]) are predictors of people's proenvironmental behavior, while his conceptualization of post-materialism yields a better model fit than Inglehart's country-level post-materialism scores. The results also corroborate previous findings that post-materialist values can stimulate proenvironmental behaviors through attitudes, perceived behavioral control and intentions. The present study reveals that proenvironmental attitudes did not change substantially in the 10-year period, even though the world's environmental and sustainability challenges have largely increased. Surprisingly, the mean value of several of the perceived threat variables even decreased.

The authors externally validate one of the most comprehensive proenvironmental behavior models by reproducing it using new multinational large-sample data with nearly 10,000 observations collected 10 years later. The most significant addition to the original model introduced in the current study is the inclusion of Schwartz's motivational types of values, which are measured at the individual level, namely BE, UN and SD. The authors also extend the model by adding proenvironmental behavior measures and group the construct into three latent variables: saving natural resources, green purchasing and environmental activism.