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This study aims to understand the reasons for individuals switching from traditional banks to Internet-only banks and examine how switching intentions differ between Generation X and Generation Z. Notably, Generation Z, being digital natives, exhibits distinct characteristics compared to Generation X, who often referred to as digital immigrants. Given the technology-driven nature of Internet-only banks, a multi-group analysis between these two generations was conducted.

This study utilizes Bansal’s push–pull–mooring model as a framework to analyze switching intention. The study collected survey data from 383 Korean participants, consisting of 198 participants from Generation Z and 185 participants from Generation X.

The findings indicate that low satisfaction and discomfort are factors that push people to leave traditional banks. Specifically, Generation Z shows a significantly higher inclination to leave traditional banks due to discomfort. On the other hand, relative advantage, compatibility, observability and trialability are factors that pull people to switch to Internet-only banks. Generation X is more likely to consider adopting Internet-only banks when compatibility is high and complexity is low.

This study is the first to explore unique motivators for Generation Z, such as their discomfort with interpersonal interactions in the retail banking sector. These findings challenge earlier research emphasizing human interaction’s importance in technology adoption, offering insights into their future adoption of contactless services.

The purpose of this study is to advance the understanding of consumer innovativeness during aging. This study explores why older consumers have decreased innovativeness and how awareness of age-related change affects the adoption of innovation.

A survey was conducted on 200 older consumers aged 50 and older to investigate whether awareness of age-related change influences innovativeness.

The results show that awareness of age-related change causes older consumers to have a decreased tendency to adopt novel products. Moreover, the stereotype threat of older consumers is found to play a mediating role. Older individuals who sense they are negatively viewed as older people restrict their innovativeness to avoid situations that would confirm their incompetence to others. Furthermore, the effects of older consumers’ stereotype threat on innovativeness are moderated by self-monitoring. Older consumers who exhibit high self-monitoring cope with stereotype threat by showing increased innovativeness; however, the opposite effect occurs in older consumers with low self-monitors.

The findings deepen the understanding of older adults’ consumption behavior regarding innovative products and show why people are reluctant to adopt innovative products and services because they grow older by identifying the underlying process that hinders customer innovativeness.

This chapter extends the univariate forecasting method proposed by Wang, Luc, and Hsiao (2013) to forecast the multivariate long memory model subject to structural breaks. The approach does not need to estimate the parameters of this multivariate system nor need to detect the structural breaks. The only procedure is to employ a VAR(k) model to approximate the multivariate long memory model subject to structural breaks. Therefore, this approach reduces the computational burden substantially and also avoids estimation of the parameters of the multivariate long memory model, which can lead to poor forecasting performance. Moreover, when there are multiple breaks, when the breaks occur close to the end of the sample or when the breaks occur at different locations for the time series in the system, our VAR approximation approach solves the issue of spurious breaks in finite samples, even though the exact orders of the multivariate long memory process are unknown. Insights from our theoretical analysis are confirmed by a set of Monte Carlo experiments, through which we demonstrate that our approach provides a substantial improvement over existing multivariate prediction methods. Finally, an empirical application to the multivariate realized volatility illustrates the usefulness of our forecasting procedure.

The purpose of this paper is to identify the effects of algorithm teaching on the problem-solving skills of deaf-hard hearing students.

In this research, a pre-test and post-test problem-solving scale was applied to the single group (16 deaf-hard hearing students at a secondary school level) that had received algorithm education. Pre-test and post-test results were compared in order to see whether there was a significant difference among students in terms of their problem-solving attitudes. Students’ levels of performing the applications were examined through observation forms and their opinions about algorithm teaching were received.

As a result of the research, it was determined that implemented algorithm teaching had a significant effect on improving the problem-solving skills of the students.

Scratch training can be administered as either a compulsory or an optional course for hearing students as the Scratch programme offers the opportunity of teaching algorithmic reasoning with games, making the courses entertaining and giving students the chance to create their own designs which helps to improve their creative problem-solving skills and their motivation accordingly. Scratch teaching can be beneficial in developing students’ problem-solving behaviours and creativity.

This study aims to comprehend luxury brands' corporate social responsibility (CSR) strategies. In addition to facing a demand for new CSR strategies (consumer-centric CSR), changes in CSR discourse among luxury brands are observed. This study examines how CSR-related and luxury-related agendas relate in the news media, especially concerning the difference between traditional and new luxury brands.

A total of 117,171 fashion-related news articles were collected from January 2016 to December 2020. The word2vec method was used to determine the relationship between CSR and luxury agendas.

The results indicate that company-centric CSR is more prominent with traditional luxury brands, while consumer-centric CSR is more relevant for new luxury brands. In addition, specific CSR attributes and luxury-related attributes are associated with media discourse, which means that CSR and luxury are compatible.

Studies on CSR in the luxury industry are not extensive in the literature. This study addresses this gap through a unique framework that combines agenda-setting theory and existing CSR literature and applies them to the luxury industry. Specifically, this study captures the development of each construct (company-centric CSR to consumer-centric CSR and traditional luxury to new luxury) and identifies the specific relationships between them. This result provides a novel view of the luxury industry indicating that it has evolved to encompass CSR-related values. The empirical results also offer practical implications for luxury marketing.

This study investigates how reward type (single vs. plural), reward characteristic (utilitarian vs. hedonic) and product involvement (high vs. low) affect the design of reward programs.

A 2 ✕ 2 ✕ 2 fractional factorial experimental design is constructed to explore the main factors influencing the effectiveness of reward programs on a sample of 436 Chinese customers.

The results indicate that reward type is an important determinant of customers' preference toward reward programs. Plural rewards are preferable to a single reward when the alternatives provide the same benefits, particularly in the low level of product involvement. In the high level of product involvement, reward characteristic has a significant effect on customers' preference. Hedonic rewards are more effective in building a program's value than utilitarian rewards. Moreover, reward characteristic interacts with reward type, positively impacting customers' preference toward reward programs.

This study suggests that managers should consider the effects of reward type, reward characteristic and product involvement to formulate attractive reward programs for sustainable business in China.

Heeding the call for insights into the Sub-Saharan African international marketing context, this study aims to empirically examine consumers' desires and motivations for buying counterfeit luxury goods. It examines influences on consumers' attitudes and purchase intentions related to counterfeit luxury goods in Rwanda, one of Sub-Saharan Africa's fastest-growing economies and growing luxury markets, developing and testing a model examining the effect of social context on personal attributes, providing evidence on economic and social-status factors as drivers for counterfeiting.

The data were collected using an online survey administered in Rwanda to consumers who had previously purchased luxury goods and counterfeits. A total of 312 valid responses were analyzed using structural equation modeling.

This study found that normative and informational influences had a positive effect on Rwandan consumers' attitude toward purchasing counterfeit luxury products, with attitude influencing purchase intentions directly and indirectly, through mediating variable desire for status or through value consciousness and desire for status.

The study contributes to academic research − one of the first empirical studies to examine consumers' desires and motivations for buying counterfeit luxury goods in Sub-Saharan Africa, providing insights that benefit scholars and practitioners seeking to better understand a market where more than half of the world's fastest economies are located.

Individuals’ daily leisure activities undertaken close to home often appear in tourism contexts when individuals are away from home. Previous studies have suggested that such leisure-tourism connection behaviors are enhanced by leisure involvement and leisure habits. However, few studies have examined if such a connection may have variations by life stage and gender. Therefore, this study aims to examine the roles of life stage and gender in consistency between leisure and tourism, in consideration of involvement and habit. The study samples were university graduates (n = 681) who had graduated from a university in the United States and were currently working and university students (n = 706) who were enrolled and taking classes at a university in the United States.

Data were analyzed using descriptive analysis, exploratory factor analysis, t-test, two-way ANOVA and multiple regression analysis.

The findings revealed differences in the effects of leisure involvement and habit factors on the leisure-tourism connection behaviors by life stage and gender. More details are presented in this paper.

This study is the first study to examine the leisure-tourism connection behaviors in consideration of life stage and gender.

The purpose of this paper is to establish a model‐based framework allowing the simulation, analysis and optimization of friction stir welding (FSW) processes of metallic structures using industrial robots, with a particular emphasis on the assembly of aircraft components made of aerospace aluminum alloys.

After a first part of the work dedicated to the kinetostatic and dynamical identification of the robotic mechanical system, a complete analytical model of the robotized process is developed, incorporating a dynamic model of the industrial robot, a multi‐axes macroscopic visco‐elastic model of the FSW process and a force/position control unit of the system. These different modules are subsequently implemented in a high‐fidelity multi‐rate dynamical simulation.

The developed simulation infrastructure allowed the research team to analyze and understand the dynamic interaction between the industrial robot, the control architecture and the manufacturing process involving heavy load cases in different process configurations. Several critical process‐induced perturbations such as tool oscillations and lateral/rotational deviations are observed, analyzed, and quantified during the simulated operations.

The presented simulation platform will constitute one of the key technology enablers in the major research initiative carried out by NRC Aerospace in their endeavor to develop a robust robotic FSW platform, allowing both the development of optimal workcell layouts/process parameters and the validation of advanced real‐time control laws for robust handling of critical process‐induced perturbations. These deliverables will be incorporated in the resulting robotic FSW technology packaged for deployment in production environments.

The paper establishes the first model‐based framework allowing the high‐fidelity simulation, analysis and optimization of FSW processes using serial industrial robots.