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A narrative inquiry was conducted to explore the complexities of learning English and Korean as subject matter in cross-cultural contexts in contributing to teacher identity, with possible tensions of identity teachers experience as ethnic Koreans teaching at an international school in Korea that promotes non-Korean, international education in English as a “language of inclusion” and instruction. With expansions of international schools in South Korea, also growing are numbers of Korean teachers teaching at such schools as returnees, individuals with cross-cultural experience. Stories of one Korean language and literature teacher with international schooling experience were examined.

While identifying the practical benefits of acquiring English, she expresses her concern for the presumed loss of Korean as a product of the prioritized use of English on campus. Equally recognized are the diverse opportunities not commonly available at Korean public schools that the participant upholds from her own experience. She acknowledged that her opportunities for the development of English language skills to a high level of proficiency through international education is not commonly accessible to all students in the Korean public school system. She also considered possible impacts associated with prioritizing the use of English over Korean in her international education experience, including their influence on: her sense of identity as a teacher and as Korean; her cultural knowledge as Korean; and her teacher knowledge as she supports her students' learning of English as subject matter in ways that might, in turn, also impact their sense of identity as Korean.

This study investigated the moderating role of democracy in the relationship between corruption and foreign direct investment. The purpose of this study is to understand whether corruption has different effects on the location decisions of multinational enterprises (MNEs) depending on the regime type.

This study explored how institutional context influenced the impacts of corruption on the location decisions of MNEs, specifically using a sample of Chinese cross-border mergers and acquisitions between 2000 and 2020.

This study assessed the role of democracy in the relationship between corruption and the location decisions of Chinese MNEs. In general, this study found that Chinese MNEs were hindered by host country corruption, but that these detrimental effects were weaker in the presence of more effective democratic institutions.

This study contributes to the literature on institutional factors in international business through its simultaneous investigation of the effects of both democracy and corruption on the location decisions of MNEs. Moreover, there is a prevailing view that Chinese MNEs are willing to enter countries with high corruption, but the results of this study indicate that they are risk-averse in ways similar to their Western counterparts.

This study aims to assess the alignment of South Korea’s government-certified social enterprises (GCSEs) with prevailing social enterprise (SE) models, notably the entrepreneurial nonprofit, social cooperative and social business models delineated in the “Emergence of Social Enterprises in Europe” (Defourny and Nyssens, 2012, 2017a, 2017b) and the “principle of interest” frameworks (Defourny et al., 2021). Thereby, it seeks to situate these enterprises within recognized frameworks and elucidate their hybrid identities.

Analyzing panel data from 2016 to 2020 for 259 GCSEs, this study uses tslearn for k-means clustering with dynamic time warping to assess their developmental trajectories and alignment with established SE models, which echoes the approach of Defourny et al. (2021). We probe the “fluid” identities of semi-public sector SEs, integrating Gordon’s (2013) notion that they tend to blend various SE traditions as opposed to existing in isolation.

Results indicate that GCSEs do align with prevalent SE frameworks. Furthermore, they represent a spectrum of SE models, suggesting the versatility of the public sector in fostering diverse types of SEs.

The concept of a semi-public sector SE model has been relatively uncharted, even though it holds significance for research on SE typologies and public sector entrepreneurship literature. This study bridges this gap by presenting empirical evidence of semi-public SEs and delineating the potential paths these enterprises might take as they amalgamate various SE traditions.

Managing differences is a difficult undertaking, especially considering the difficulties arising from the unconscious functions of our brains. Organisations should strive to counteract the potentially harmful effects of unconscious bias by implementing policies that support bias-aware management and decision-making. Although it is obvious that bias cannot be completely eliminated, there is enough data, as discussed in this work, to demonstrate that unconscious bias and stereotypes can be addressed and decreased with mindfulness-based interventions (MBIs) to some extent. Mindfulness involves the process of bringing non-judgemental awareness to experience by striving for full attention in the present moment. In this context, including mindfulness practises into training programmes for equality, diversity, and inclusion may serve as an accelerator for recognising hidden biases, reducing stereotypes, eliminating discrimination, and encouraging cognitive changes. This chapter explains the ways in which MBIs can be used to promote cognitive changes and comprehend the automatic and unconscious nature of emotions and thoughts in order to remove barriers between all differences in the workplace.

This study aims to investigate the influence of environmental factors on individual personality traits associated with mobile paymens (MP) adoption using the technological personal environment (TPE) theory as a framework for the proposed theoretical model.

A total of 736 feedback from respondents was used to validate the proposed model using structural equation modeling. The model comprises Trust and Self-efficacy to explain MP adoption from a personal trait perspective. Meanwhile, environmental aspects are represented by social influence, vendor regulations and network externalities.

The result indicates that self-efficacy has the most significant direct effect on user intention to use MP, followed in decreasing order of significance by social influence, trust, vendor regulations and network externalities. Furthermore, social influence is the most contributing aspect from the environmental area that influences user intention directly and indirectly through trust and self-efficacy as mediators. Meanwhile, the moderating effect analysis also found that gender moderates the effect of user self-efficacy on MP adoption.

This study fills the gap by comparing trust and self-efficacy and exploring how those factors are developed and affected by the environmental aspect of MP usage. It was discovered that self-efficacy was the most influential construct influencing the adoption of MP. Social influence was identified as the primary environmental factor that directly impacts user intention regarding MP usage. Furthermore, gender was shown as a moderator, as males place a higher value on self-efficacy as a factor affecting their intention to embrace MP in comparison to females.

Highly committed, motivated and engaged employees assure organizational success and competitiveness. The study aims to examine the association between human resource development (HRD) practices and employee engagement with organizational commitment as a mediating variable.

Data were collected from 760 employees of 13 star-rated hotels comprising 5 (five-star) and 8 (four-star). The data supported the hypothesized relationships. Structural equation modeling was used to evaluate the proposed model and hypotheses. Construct validity and reliability were established through confirmatory factor analysis.

The results indicate that HRD practices and affective commitment are significantly associated. HRD practices and continuance commitment were shown to be non-significantly associated. HRD practices and normative commitment were shown to be non-significantly associated. Employee engagement and organizational commitment are significantly associated. The results further show that organizational commitment mediates the association between HRD practices and employee engagement.

The generalizability of the findings will be constrained due to the research's hotel industry focus and cross sectional data.

The study's findings will serve as valuable pointers for stakeholders and policymakers of the hotel industry in the adoption, design and implementation of proactive HRD interventions to keep highly engaged and committed employees for organizational competitiveness and sustainability.

By evidencing empirically that organizational commitment mediates the nexus between HRD practices and employee engagement, the study extends the literature.

Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping.

Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model.

The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping.

This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.

Despite the significance of donations (Sadaqah) via mobile payment in Islamic countries, little is known about the variables influencing continuance intention toward using m-payment for donations (Sadaqah). Based on the stimulus-organism-response (S-O-R) model, this research explores the influence of perceived quality (i.e. system, information, service) as a stimulus on customer satisfaction, engagement and delight as organisms, which then affects continuance intention toward using m-payment for donations (Sadaqah) as a response. Moreover, the study investigates the moderating role of Islamic religiosity.

Using partial least squares structural equation modeling (PLS-SEM), a representative data sample of 419 Egyptian Muslims was analyzed to test hypotheses.

The findings revealed that all perceived quality constructs significantly positively affect customers' satisfaction. Customer satisfaction, in turn, positively affects customer engagement and delight. Moreover, customer engagement, delight and Islamic religiosity significantly positively affect continuance intention toward using m-payment for donations (Sadaqah). The findings also revealed that Islamic religiosity moderates the influence of customer engagement and customer delight on continuance intention toward using m-payment for donations (Sadaqah).

This is the first study to examine using m-payment for donations (Sadaqah) in an Islamic environment based on the S-O-R model.

Amidst the turbulent tides of geopolitical uncertainty and pandemic-induced economic disruptions, the information technology industry grapples with alarming attrition and aggravating talent gaps, spurring a surge in demand for specialized digital proficiencies. Leveraging this imperative, firms seek to attract and retain top-tier talent through generous compensation packages. This study introduces a holistic, integrated theoretical framework integrating machine learning models to develop a compensation model, interrogating the multifaceted factors that shape pay determination.

Drawing upon a stratified sample of 2488 observations, this study determines whether compensation can be accurately predicted via constructs derived from the integrated theoretical framework, employing various cutting-edge machine learning models. This study culminates in discovering a random forest model, exhibiting 99.6% accuracy and 0.08° mean absolute error, following a series of comprehensive robustness checks.

The empirical findings of this study have revealed critical determinants of compensation, including but not limited to experience level, educational background, and specialized skill-set. The research also elucidates that gender does not play a role in pay disparity, while company size and type hold no consequential sway over individual compensation determination.

The research underscores the importance of equitable compensation to foster technological innovation and encourage the retention of top talent, emphasizing the significance of human capital. Furthermore, the model presented in this study empowers individuals to negotiate their compensation more effectively and supports enterprises in crafting targeted compensation strategies, thereby facilitating sustainable economic growth and helping to attain various Sustainable Development Goals.

The cardinal contribution of this research lies in the inception of an inclusive theoretical framework that persuasively explicates the intricacies of a machine learning-driven remuneration model, ennobled by the synthesis of diverse management theories to capture the complexity of compensation determination. However, the generalizability of the findings to other sectors is constrained as this study is exclusively limited to the IT sector.

Even though it is widely used, reinforced concrete (RC) is susceptible to damage from various environmental factors. The hazard of a fire attack is particularly severe because it may cause the whole structure to collapse. Furthermore, repairing and strengthening existing structures with high-performance concrete (HPC) has become essential from both technical and financial points of view. In particular, studying the postfire behavior of HPC with normal strength concrete substrate requires experimental and numerical investigations. Accordingly, this study aims to numerically investigate the post-fire behavior of reinforced composite RC slabs.

Consequently, in this study, a numerical analysis was carried out to ascertain the flexural behavior of simply supported RC slabs strengthened with HPC and exposed to a particularly high temperature of 600°C for 2 h. This behavior was investigated and analyzed in the presence of a number of parameters, such as HPC types (fiber-reinforced, 0.5% steel, polypropylene fibers [PPF], hybrid fibers), strengthening side (tension or compression), strengthening layer thickness, slab thickness, boundary conditions, reinforcement ratio and yield strength of reinforcement.

The results showed that traction-separation and full-bond models can achieve accuracy compared with experimental results. Also, the fiber type significantly affects the postfire performance of RC slab strengthened with HPC, where the inclusion of hybrid fiber recorded the highest ultimate load. While adding PPF to HPC showed a rapid decrease in the load-deflection curve after reaching the ultimate load.

The proposed model accurately predicted the thermomechanical behavior of RC slabs strengthened with HPC after being exposed to the fire regarding load-deflection response, crack pattern and failure mode. Moreover, the considered independent parametric variables significantly affect the composite slabs’ behavior.