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The purpose of this paper is to investigate the influence of behavioural attitudes towards the most popular social medium in the world, Facebook, amongst Millennials in South Africa (SA), and to determine whether various usage and demographic variables have an impact on intention-to-purchase and purchase perceptions.

Quantitative research was conducted by means of a survey among a sample of over 3,500 respondents via self-administered structured questionnaires in SA. A generalised linear model was used to analyse the data.

The results confirm that advertising on Facebook has a positive influence on the behavioural attitudes (intention-to-purchase and purchase) of Millennials who reside in SA. The usage characteristics, log on duration and profile update incidence, as well as the demographic influence of ethnic orientation also resulted in more favourable perceptions of Facebook advertising.

Research on Facebook advertising was only conducted in SA, whereas other emerging countries warrant further investigation to establish if they share the slight positive sentiment towards intention-to-purchase and purchase. This inquiry only provides a “snap shot” of behavioural attitudes, usage and demographic factors towards social media advertising, whereas future research could consider the development of cognitive, affective and behavioural attitudes towards Facebook advertising by employing longitudinal and qualitative research designs.

Organisations and managers should consider that their existing Facebook advertising strategies may only have a limited effect on intention-to-purchase and purchase in SA. However, certain usage characteristics, namely the more time spent logged on to Facebook and the greater frequency of profile update incidence, as well as the demographic variable, namely black and coloured Millennials, resulted in more favourable behavioural attitudes towards Facebook advertising. Hence, organisations and managers should be prepared to alter or adapt their Facebook advertising tactics accordingly when targeting the notoriously fickle Millennials.

This investigation found that Facebook advertising has a nominal positive influence on behavioural attitudes among Millennials, which is in congruence with the communications of the effect pyramid model that was established through traditional advertising research. This paper also makes a noteworthy contribution to attitudinal research in emerging countries where there is a dearth of research in social media advertising.

Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human brain functions, for example, recognize the speaker, sense the tone of the text. On this paper, we present the similarities of these with human cognitive functions. We establish a framework which gathers cognitive functions into nine intentional processes from the substructures of the human brain. The framework, underpins human cognitive functions, and categorizes cognitive computing functions into the functional hierarchy, through which we present the functional similarities between cognitive service and human cognitive functions to illustrate what kind of functions are cognitive in the computing. The results from the comparison of the functional hierarchy of cognitive functions are consistent with cognitive computing literature. Thus, the functional hierarchy allows us to find the type of cognition and reach the comparability between the applications.

In his 1943 paper “A Theory of Human Motivation”, Maslow suggested the “Hierarchy of Needs” as a classification system that described the stimuli for human behaviour. Presently, project behaviour research, which inspired this work, encourages undertaking research on behavioural aspects within and across organisational and project settings. Therefore, the purpose of this paper is to analyse project-based organisations’ (PBOs) seemingly reluctance in engaging in organisational learning from past project failures by drawing upon both institutional theory (since it focuses on how firms interact) and Maslow’s model within a project behaviour piece of research.

Interviews were held with purposively selected construction professionals from the UK construction industry, and data were analysed using thematic analysis.

Besides the need to learn from failures, PBOs’ main competing needs revolve around their “competitiveness”; “profitability and productivity”; “repeat business” and “reputation and partnering”. Mirroring these needs against Maslow’s hierarchy of needs, “competitiveness” and “profitability” are analogous to foundational “physiological” and “safety” needs. The need for “repeat business” and “reputation” is approximated with Maslow’s “affiliation” and “self-esteem” needs, and organisational learning is associated with “self-actualisation”. From an institutional theory perspective, such response to failure is influenced by the need to show legitimacy and conformity imposed by institutional factors.

Instead of taking a simplified approach to learning from failure such as the use of technological tools, PBOs and the sector at large should consider more robust approaches, by appreciating the influence of institutional factors and the external environment on their efforts to learn from failure.

Unlike past studies that present organisational learning within PBOs as a straightforward process, this study instead highlights the need of understanding various competing needs within a PBO and the external pressure.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

The purpose of this study is to validate multiplicative cycle that exists between the job readiness and satisfaction model explored by Matthews et al. (2018), the satisfaction and performance paradigmatic nuances analyzed by Judge et al. (2001) and Gu and Chi (2009), in addition to the expectancy model theorized by Vroom (1964). The motivation to transfer learning serves as a conveyable variable transmitted within a learning continuum that sustains cyclical outputs.

An archetype to explore the connection between the three hypothesized theories is created through a neural network program. Exploring this connection develops deeper understandings of the derivatives of employee motivation as it pertains to its effect on readiness, satisfaction, performance and achievement dyads. A detailed analysis of the literature leads to the hypothesis that the motivation to transfer learning creates a multiplicative effect among hypothesized relationships.

The neural network program scaffolds the proposed general belief that positive effects of transfer motives cause a cyclical effect that continues to perpetuate among hypothesized dyads. Conversely, if this motivation decreases or ceases among one or more dyads, the cyclical effect will retract and, eventually stop.

Based on the neurologic outcome, one central theme emerged: managers must offer opportunities to acquire knowledge through assistive mechanisms (i.e. training) by providing external stability through controlled channels that activates the motivation to transfer learning into new opportunities. The transference of this knowledge produces reconstructive growth opportunities through continuous learning thus increasing performance.

本研究的目的、除了驗證弗魯姆 (Vroom) (1964) 建立的「期望模型」理論外，也去驗證存在於工作準備就緒與馬修斯等人 (Matthews et al.) (2018) 所探索的滿足感模型之間的倍增週期，及質治等人 (Judge et al.) (2001) 和古與池 (Gu & Chi) (2009) 所分析的滿足感及表現之範式細微差別。學習轉移的動機作為一個被傳送至學習漸變體內的可輸送變量而運作，而這個學習漸變體是會維持週期性的輸出的。

透過神經網絡程序，創造一個用以探索這三個假設性理論之間的關係的原型。探究這些關係，會使我們更能深入了解僱員動機的衍生品，因這涉及僱員動機對準備就緒、滿足感、表現及功績二元體的影響。仔細分析文獻帶出了一個假設，就是: 學習轉移的動機會在各假設的關係裏創造一個倍增的效果。

這個神經網絡程序續步闡釋了一個被倡議的普遍觀念，那就是轉移動機的正面影響會帶來一個在假設性的二元體中會繼續持續下去的週期性效應。相反地，如果這動機在一個或多個二元體中減弱或停止，這週期性效應將會撤回及最終停止。

基於神經病學的結果，一個核心主題浮現了， 就是：管理人員必須提供透過輔助機制 (就是說：培訓) 而獲取知識的機會。方法是給會引發把學習轉為新機會的動機之受控渠道、提供外在穩定性。這知識的轉移，透過不斷學習而創造重建的成長，表現因而得以提升。

This study investigates the impact of large-scale teaching in higher education on students’ preparedness for the workforce within the context of evolving labour market demands, the expansion of higher education and the application of high-impact teaching strategies. It synthesizes perspectives on employer work readiness, the challenges and opportunities of large-scale teaching and strategies for fostering a dynamic academia-industry feedback loop. This multifaceted approach ensures the relevance of curricula and graduates’ preparedness while addressing the skills gap through practical recommendations for aligning teaching methodologies with employer expectations.

The research methodically examines the multifaceted challenges and opportunities inherent in large-scale teaching. It focuses on sustaining student engagement, maintaining educational quality, personalizing learning experiences and cultivating essential soft skills in extensive student cohorts.

This study highlights the critical role of transversal skills in work readiness. It also uncovers that despite its challenges, large-scale teaching presents unique opportunities. The diversity of large student groups mirrors modern workplace complexities, and technological tools aid in personalizing learning experiences. Approaches like peer networking, innovative teaching methods, real-world simulations and collaborative resource utilization enrich education. The importance of experiential learning for augmenting large-scale teaching in honing soft skills is emphasized.

This manuscript contributes to the discourse on large-scale teaching, aligning it with employer expectations and the dynamic requirements of the job market. It offers a nuanced perspective on the challenges and opportunities this educational approach presents, providing insights for crafting engaging and effective learning experiences in large cohorts. The study uniquely integrates experiential learning, co-creation in education and industry-academia feedback loops, underscoring their importance in enhancing student work readiness in large-scale teaching.

The purpose of this paper is to challenge how we have traditionally thought about organisations and introduce two frameworks to enable us to understand how change in organisations might be facilitated better.

The paper discusses organisations as complex adaptive systems and uses complexity theory to inform two new frameworks for facilitating organisational learning and change.

In order for organisational learning to occur we need to change our mind-set of how we see organisations and to think of learning not just as individual but also as generative “communicative action” that emerge out of collaborative relationships.

The frameworks proposed are grounded in organisational learning literature and the experience of the author. The proposed agenda for organisational learning has yet to be acted upon and evaluated.

The frameworks can be used to enhance understanding of learning and change in organisations. The agenda for enabling organisational transformation identifies key steps to put the ideas developed in the paper into practice.

The approach advocated for use within organisations is one of empowerment and collaboration rather than top down direction.

The paper introduces new frameworks and a practical agenda to bring about organisational transformation through work-applied learning.

China is currently developing and promoting an industrial cluster policy at the government level. By enacting the ‘Opinion on promoting industrial cluster development’, China is supporting the development of industrial clusters. Building an industrial cluster is done by using a single factor but requires many additional factors like regional characteristics, competitiveness factors are also diversified. To evaluate the competitiveness of the Chinese automobile industry cluster, a competitiveness element index should be developed and a competitiveness evaluation method is needed to evaluate the importance of each element. To accomplish this objective, this research applied the analytic hierarchy process (AHP) and focused on the importance of the competitiveness elements.

This research investigated the character is tics regarding cases of clusters and also analyzed the competitiveness of the Changchun automobile cluster located in northeastern China. The purpose of this research is to help Korean enterprises who enter China in the hopes that Korea will emerge as a top automobile production country.

This paper aims to develop indicators of happiness in learning of the Thai open university (TOU)'s undergraduate students.

Sampling for the study was comprised of two groups. Group I comprised eight lecturers who are experts in their disciplines and six students who were purposively sampled. The focus group was used to validate the appropriateness of the indicators. In Group II, 332 students were engaged in a multistage sampling process. The responses were analyzed using descriptive statistics, coefficient correlation, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The indicators of happiness in learning of undergraduate students of TOU were classified in six categories. These included satisfaction with learning environment (five indicators), learning anxiety (five indicators), satisfaction with learning (five indicators), enthusiasm to learn (six indicators), self-satisfaction (six indicators) and readiness to learn (seven indicators). The six categories explained happiness in learning of undergraduate students of TOU at the 65% and fit empirical data.

The TOU can use the indicators for the assessment of happiness in learning of its students as well as guidelines for the improvement of its student learning environments.

There have been very few studies on indicators of happiness in learning of TOU students. Most were done at the basic education level. This study disclosed the six factors affecting happiness in learning of TOU students; therefore, it should inspire and draw attention of many in the field of higher education distance learning.

A transition toward sustainable development requires engagement of university students in transformative learning. Therefore, quality frameworks and processes should support deep approaches to sustainable development in higher education. Research and initiatives that connect sustainable development, higher education and quality assurance (QA) are lacking. This study aims to explore to what extent quality assurance agencies in Europe support transformative learning for sustainable development in their frameworks.

The authors conducted a qualitative analysis of national QA frameworks in the European Higher Education Area (EHEA) to assess whether they support transformative learning for sustainable development. First, frequency analysis was undertaken; second, a blended coding approach was used to investigate whether and how transformative learning for sustainable development is addressed.

Overall, the authors found little support for transformative learning for sustainable development in most QA frameworks. One exception is the framework of the United Kingdom, which includes a specific guide on education for sustainable development wherein transformative learning is prominently mentioned. To a lesser extent, some support exists in the frameworks of Estonia, Holy See, Romania, Sweden, Switzerland and Ukraine. Although the transformative learning for sustainable development approach is not explicitly mentioned in most QA frameworks, many of them contain opportunities to highlight it. France and The Netherlands offer guidelines and criteria for acquiring a sustainable development label, while Andorra suggests including the sustainable development goals in institutional quality assessment.

The research provides the first map of how countries within the EHEA support transformative learning for sustainable development in national QA systems.