BEHAVIORAL FACTORS OF INTERNAL AUDITORS AND ENTERPRISE RISK MANAGEMENT EFFECTIVENESS ASSESSMENT OF MALAYSIAN STATUTORY BODIES

This study used the theory of planned behavior to examine the relationship between internal auditors’ behavioral factors and intention to evaluate enterprise risk management (ERM) effectiveness of Malaysian statutory bodies. Unlike prior literature, this study also included a test on individual attitude towards risk in addition to attitude towards behavior, subjective norms, and perceived behavioral control. Analysis on 108 received responses showed that subjective norms and perceived behavioral control had positive relationships with the intention to assess ERM effectiveness. Nevertheless, the influence of attitude was not substantiated. The results imply that attitude is not an important factor when individuals do not have total process ownership. Managers of statutory bodies and heads of internal audit departments need to shape internal auditor behavior by instituting social and administrative norms and instilling a positive perception about the ability to perform tasks within the organization. This study also shows that individuals have no total ownership in a process, thus focusing efforts on shaping individual attitude is not practical. This issue is critical because successful ERM implementation depends on internal auditors’ intention to evaluate its effectiveness. An effective ERM can reduce the risks of waste, inefficiencies, corruption, malpractices, and public–private partnerships associated with the public sector.

Computer Programming E-Learners’ Personality Traits, Self-Reported Cognitive Abilities, and Learning Motivating Factors

Educational systems around the world encourage students to engage in programming activities, but programming learning is one of the most challenging learning tasks. Thus, it was significant to explore the factors related to programming learning. This study aimed to identify computer programming e-learners’ personality traits, self-reported cognitive abilities and learning motivating factors in comparison with other e-learners. We applied a learning motivating factors questionnaire, the Big Five Inventory—2, and the SRMCA instruments. The sample consisted of 444 e-learners, including 189 computer programming e-learners, the mean age was 25.19 years. It was found that computer programming e-learners demonstrated significantly lower scores of extraversion, and significantly lower scores of motivating factors of individual attitude and expectation, reward and recognition, and punishment. No significant differences were found in the scores of self-reported cognitive abilities between the groups. In the group of computer programming e-learners, extraversion was a significant predictor of individual attitude and expectation; conscientiousness and extraversion were significant predictors of challenging goals; extraversion and agreeableness were significant predictors of clear direction; open-mindedness was a significant predictor of a diminished motivating factor of punishment; negative emotionality was a significant predictor of social pressure and competition; comprehension-knowledge was a significant predictor of individual attitude and expectation; fluid reasoning and comprehension-knowledge were significant predictors of challenging goals; comprehension-knowledge was a significant predictor of clear direction; and visual processing was a significant predictor of social pressure and competition. The SEM analysis demonstrated that personality traits (namely, extraversion, conscientiousness, and reverted negative emotionality) statistically significantly predict learning motivating factors (namely, individual attitude and expectation, and clear direction), but the impact of self-reported cognitive abilities in the model was negligible in both groups of participants and non-participants of e-learning based computer programming courses; χ² (34) = 51.992, p = 0.025; CFI = 0.982; TLI = 0.970; NFI = 0.950; RMSEA = 0.051 [0.019–0.078]; SRMR = 0.038. However, as this study applied self-reported measures, we strongly suggest applying neurocognitive methods in future research.

Associations between Depression, Anxiety, Fatigue, and Learning Motivating Factors in e-Learning-Based Computer Programming Education

Quarantines imposed due to COVID-19 have forced the rapid implementation of e-learning, but also increased the rates of anxiety, depression, and fatigue, which relate to dramatically diminished e-learning motivation. Thus, it was deemed significant to identify e-learning motivating factors related to mental health. Furthermore, because computer programming skills are among the core competencies that professionals are expected to possess in the era of rapid technology development, it was also considered important to identify the factors relating to computer programming learning. Thus, this study applied the Learning Motivating Factors Questionnaire, the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder Scale-7 (GAD-7), and the Multidimensional Fatigue Inventory-20 (MFI-20) instruments. The sample consisted of 444 e-learners, including 189 computer programming e-learners. The results revealed that higher scores of individual attitude and expectation, challenging goals, clear direction, social pressure, and competition significantly varied across depression categories. The scores of challenging goals, and social pressure and competition, significantly varied across anxiety categories. The scores of individual attitude and expectation, challenging goals, and social pressure and competition significantly varied across general fatigue categories. In the group of computer programming e-learners: challenging goals predicted decreased anxiety; clear direction and challenging goals predicted decreased depression; individual attitude and expectation predicted diminished general fatigue; and challenging goals and punishment predicted diminished mental fatigue. Challenging goals statistically significantly predicted lower mental fatigue, and mental fatigue statistically significantly predicted depression and anxiety in both sample groups.

Smartphone Brand Loyalty and Consumer Heterogeneity

Research Question: The purpose of this study is to examine the effect of sales promotion and advertisement on brand association and brand loyalty of Samsung smartphones via the analysis of gender and age as moderating variables. Motivation: The motivation for this study emerges from the fact that the effect of sales promotion and advertisement on brand loyalty have not considered the effects of consumer heterogeneity such as age and gender. Idea: The core idea of this study is to verify the effect of monetary promotion, non-monetary promotion, perceived advertising, and individual attitude towards brand association and brand loyalty through the moderate effects of age and gender. Data: This research was carried out in South Jakarta, Indonesia by employing a simple random sampling method and questionnaires distributed to 100 respondents. Tools: Data were analyzed by using Partial Least Square Structural Equation (PLS-SEM) method and the SmartPLS 3.0 software. The PLS-SEM was performed with a two-step approach by analyzing the outer and inner model, afterwards followed by a multi-group analysis to analyze moderating effects of both variables of gender and age. Findings: The findings indicate that non-monetary promotion and individual attitude towards advertising significantly affect brand association while brand association significantly affects brand loyalty. Gender and age-specific analyses indicate that gender differences significantly moderate the influence of individual attitude towards advertising on brand association and age differences significantly moderate the effect of monetary promotion on brand association. Moreover, women, men, younger and older consumers behave differently towards sales promotion. Contribution: This study contributes to the literature by adding empirical evidences in terms of how different consumers respond to sales promotion and advertising as well as further effects on brand association and brand loyalty.

Cognitive Matrices of the HERO — ANTIHERO Conceptual Opposition: a comparative analysis

This article presents a comparative study of the cognitive matrices of the binary opposition HERO — ANTIHERO in the Russian and English conceptual spheres through the prism of anthropocentric approaches. The cognitive-matrix analysis helps to distinguish cognitive matrices of the binary opposition HERO — ANTIHERO in “Doctor Zhivago” by B. Pasternak and “Death of a Hero” by R. Aldington. The research points out that there are isomorphic and allomorphic features in the linguo­cognitive models. Isomorphic features express similar cognitive processes and both writers’ deep concern over the political situation during the war; on the other hand, allomorphic features depict heroes and authors’ certain culture-specific mentalities and visions of the world. The comparative analysis of language means and cognitive mechanisms of the binary opposition HERO — ANTIHERO reveals the antonymous nominations of the concepts representing the dialectical unity of opposites and reflects the authors’ individual attitude to the war and heroism in the works under consideration.