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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.

This study investigates how sustainability influences employer branding across generational cohorts – Generations Z, Y and X – and between two neighboring countries, Slovenia and Croatia, with different economic development levels.

A comparative cross-generational survey was conducted among respondents from Slovenia and Croatia to assess the impact of sustainability on employer brand perception. The survey explored generational attitudes toward sustainability and its integration into the employer value proposition.

The study found that all the generational cohorts view sustainability as an important factor in their evaluation of employer brands. Generation X showed the most favorable attitude toward sustainability, followed by Generation Z, highlighting the need for organizations to communicate sustainability efforts effectively to attract these groups. However, there were subtle differences between the countries, with Slovenian respondents indicating a slightly higher preference for sustainable practices. Additionally, while Generation Z may not have the same financial leverage as Generation X, their high valuation of sustainability in employer branding demonstrates their future influence as they enter the workforce.

Limitations include the survey’s conceptual framing, which may be inherently biased toward the more affluent Generation X’s capacity to prioritize sustainability and the focus on USA-based generational definitions, which may not be fully applicable across different cultural settings. Future research could address these limitations by refining the conceptual approach and expanding the sample to include more diverse geographical contexts.

By comparing responses from two economically distinct neighboring countries, the study reveals complex inter-generational dynamics and national contexts affecting sustainability’s role in employer attractiveness.

The world population over the age of 60 is expected to increase from 900 million in 2015 to two billion by 2050. Retirement homes have emerged as a prominent housing alternative and become a trend for the older adults; however, older population in Malaysia could have a negative view of retirement homes. Different generations could have different perceptions of the value of retirement homes. This study aims to explore the value of retirement homes across diverse age cohorts in Malaysia.

A qualitative approach is adopted for this study. Thematic analysis is used to analyse the interview transcripts obtained from semi-structured interviews.

The results indicated that baby boomers tend to have more negative values towards retirement homes, whereas Generations X and Y demonstrated more favourable and positive values for retirement homes.

This study serves as a useful reference for housing developers, policymakers and the management of retirement homes to better understand how different age cohorts value retirement homes, thereby encouraging relevant housing strategies to enhance the quality and support systems of retirement homes in society.

The purpose of this paper is to estimate the effect the five different generations and the key financial inclusion indicators of gender, education and location (rural–urban) in exacerbating disparities in financial inclusion in Kenya. This paper considers whether the five generational cohort groups in Kenya differ on the financial inclusion determinants and behaviour as predicted by common generational stereotypes.

The authors applied a multinomial logistic regression approach to nationally representative household survey data from Kenya to estimate the effect that key financial inclusion indicators have on belonging to one of the five generations: Z, Y, X, baby boomers and traditionalists.

The authors found significant links between all tested variables and financial inclusion. The authors found an access gap between Generations X and Y, with the latter being more prone to access and use financial services and products. These differences are compounded by gender and rurality. People in rural locations and women generally were found to have less access to financial services and products, thus causing significant exclusion of a large proportion of the population.

The research has important implications for governments, financial institutions and educational providers, notably on targeted policies and programmes that strategically aim to eliminate disparities and promote greater financial inclusion, denoting the value of such variables as generational differences and gender inclusivity.

This paper deepens the understanding of differences that can divide generations on financial inclusion.

The study investigates the predisposition of generational cohorts toward entrepreneurship in an emerging economy as entrepreneurship has arguably become a panacea for unemployment and sustainable economic development.

The study adopts descriptive and cross-sectional survey designs. The study also employs quantitative approach to collect the data from 1,000 workers in 20 selected private and public organizations in Ghana. The data were analyzed using descriptive statistics, correlation and hierarchical regression techniques.

The results reveal that baby boomers and Generation Z (Gen Z) have a higher predisposition toward entrepreneurship, while Generation X (Gen X) and Generation Y (Gen Y) have a lower predisposition toward entrepreneurship. However, the study found that baby boomers are more predisposed to entrepreneurship than all the generational cohorts. Furthermore, a generation may become entrepreneurs regardless of their gender. Finally, individuals with higher educational qualification (i.e. masters and doctorate) are more likely to become entrepreneurs in a given generation.

The findings imply that entrepreneurial opportunities (such as ease of doing business, favorable business regulations, access to credit facilities, low interest rate, ease of registering business, start-up capital, etc.) should be created by government and its stakeholders to serve as stimuli for members of these generations (particularly baby boomers and Gen Z) to participate fully in entrepreneurial activities. In addition, the culture of “go to college and graduate with the expectation of government employment” and “job for life” should be discouraged to allow members of Gen X and Gen Y build up entrepreneurial mindsets.

This study contributes to generational cohorts and entrepreneurship literature by providing a perspective from the cultural and socio-economic background of an emerging economy. Additionally, this study demonstrates that irrespective of gender, one may become an entrepreneur and highly educated individuals tend be entrepreneurs.

The purpose of the study is to investigate the differences between generational groups (specifically Generations X, Y and Z) in terms of variables that influence organisational commitment and intention to stay within an organisation. The aim is to fill the research gap in understanding how different factors influence commitment and retention across different generations.

This study follows a quantitative approach based on cross-sectional survey data. The respondents were employees of Generations X, Y and Z. The data were analysed using partial least squares structural equation modelling and multigroup analysis.

The results of the study indicate several relationships between variables and organisational commitment/intention to stay. Person-organisation fit is positively related to organisational commitment, and work-life balance is positively related to both organisational commitment and intention to stay. The mediation of organisational commitment shows a positive relationship with person-organisation fit and work-life balance. In addition, there are positive relationships between organisational culture and both organisational commitment and intention to stay, as well as a positive relationship between person-organisation fit and intention to stay. Furthermore, all three Generations (X, Y and Z) show positive relationships between organisational commitment and intention to stay.

The implications of the study are twofold. First, it provides theoretical contributions by uncovering the relationships between various variables and organisational commitment/retention. Second, it provides practical implications for organisations by highlighting the importance of person-organisation fit, work-life balance and organisational culture in fostering commitment and retention among employees of different generations.

The originality and value of this study lies in its exploration of the differences between generational groups in terms of variables affecting organisational commitment and intention to stay. By addressing this research gap, the study contributes to the existing literature on organisational commitment and retention. The detailed presentation of theoretical contributions, practical implications, limitations and suggestions for future research enhances the overall value of the study.

This comparative research examines the factors influencing individuals' purchase intention toward green housing. By examining these factors, this study provides fruitful insights into the purchase intentions and behaviors for greenhouses among individuals of different age groups in India.

Data were gathered from Generation (Gen) X (313) and Generation (Gen) Y (297) using self-administered questionnaires. The “partial least squares structural equation modeling” was used to test the hypotheses.

The outcome shows that attitude and green trust substantially impact the green purchase intention of Gen X and Y. More specifically, environmental knowledge insignificantly influences the green purchase intention of Gen X while significantly influencing Gen Y. However, perceived risk insignificantly affects the purchase intention of both Gen X and Y. Consequently, green purchase intention substantially impacts the green purchase behavior in both studies.

This research focuses primarily on India; future research may be conducted in different geographical contexts. This study could also be extended to all age groups individuals.

The findings of this article facilitate policymakers, real estate developers and professional bodies in formulating strategies for sustainable nations in the future.

The current article is the initial empirical attempt to examine the home-buying decisions of individuals in India. Moreover, the role of Generation X and Generation Y in green housing purchase decisions will provide fruitful insights into how different age groups impact the decision-making process of green housing.

This study aims to analyze the importance and performance of customer-facing technologies in luxury hotels. The study also assessed differences between and within the four generations in the importance-performance analysis (IPA).

Data were collected using a Qualtrics panel of recent luxury hotel customers in the USA belonging to all four generations. The cross-generational IPA was conducted using t-tests and (ANAOVA).

The IPA matrix concentrated most technology items in either low importance – low performance or high importance – high performance quadrants. One-way ANOVA revealed significant differences between generations on the importance ratings of all technology items except wireless charging power solutions and on the performance ratings of all technology items. Furthermore, post hoc tests indicated that millennials rated luxury technology most favorably among the four cohorts, followed by generations Z, X and Baby Boomers. In addition, significant differences between the importance and performance of many technology items within each generational cohort were observed. Overall, Wi-Fi was unanimously ranked across generations as the most important technology among luxury guests, but it was the only one that scored lower in performance than importance.

The findings of this study contribute to hospitality scholarship in two primary ways: the importance and performance of technology and generational differences. The results advance the understanding of the impact of generational factors on customer-facing technological adoptions in the luxury hotel sector.

Technologies that are pervasive in the home also become vital offerings for hotels. The more pervasive technology, the more a luxury hotel must work to ensure that it performs at optimal levels. Additionally, which technologies are most important to targeted generations are provided so practitioners may budget for their implementation.

This research is a pivotal step forward in unraveling the intricate interplay between generational factors and technological evaluations, providing a foundation for future research and practical applications in a rapidly evolving technological landscape in the hospitality industry.

The study aims to explore the influence of conscious business practices (CBPs) on the reputational capital (RC) of SMEs with the generation of the manager (X/Y) as a moderator of such relationships.

The authors conducted empirical research based on a cross-sectional survey on 115 Western Mexican SME managers using PLS structural equation modeling to test the proposed hypotheses.

SMEs RC is nurtured by adopting two CBPs. The effect on RC may differ according to managers’ generation. In Western Mexican SMEs, Gen X managers perceive that a higher purpose is more important for building RC, while conscious culture comes first for millennials.

The generalisability of the findings is decreased, given that the study relied on convenience and non-probabilistic sampling in one economy. The lack of previous studies on SMEs, and the difficulty in conducting research in an emerging economy, gives the findings an importance in furthering research.

It contributes to strengthen SMEs’ RC through CBPs.

It broadens the perspective of SMEs in emerging economies to adopt CBPs for increasing their RC. This relationship varies depending on the managers’ generation.

The study used the quantitative approach to explore the perception of Mexican Gen X managers and millennials on the relationship between CBPs and their effects on RC.

The purpose of this study is to investigate and demonstrate the advancements achieved in the field of chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Typical convolutional neural networks (CNNs) are unable to capture both local and global contextual information effectively and apply a uniform operation to all pixels in an image. To address this, we propose an innovative approach that integrates a dynamic convolution operation at the encoder stage, improving image encoding quality and disease detection. In addition, a decoder based on the gated recurrent unit (GRU) is used for language modeling, and an attention network is incorporated to enhance consistency. This novel combination allows for improved feature extraction, mimicking the expertise of radiologists by selectively focusing on important areas and producing coherent captions with valuable clinical information.

In this study, we have presented a new report generation approach that utilizes dynamic convolution applied Resnet-101 (DyCNN) as an encoder (Verelst and Tuytelaars, 2019) and GRU as a decoder (Dey and Salemt, 2017; Pan et al., 2020), along with an attention network (see Figure 1). This integration innovatively extends the capabilities of image encoding and sequential caption generation, representing a shift from conventional CNN architectures. With its ability to dynamically adapt receptive fields, the DyCNN excels at capturing features of varying scales within the CXR images. This dynamic adaptability significantly enhances the granularity of feature extraction, enabling precise representation of localized abnormalities and structural intricacies. By incorporating this flexibility into the encoding process, our model can distil meaningful and contextually rich features from the radiographic data. While the attention mechanism enables the model to selectively focus on different regions of the image during caption generation. The attention mechanism enhances the report generation process by allowing the model to assign different importance weights to different regions of the image, mimicking human perception. In parallel, the GRU-based decoder adds a critical dimension to the process by ensuring a smooth, sequential generation of captions.

The findings of this study highlight the significant advancements achieved in chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Experiments conducted using the IU-Chest X-ray datasets showed that the proposed model outperformed other state-of-the-art approaches. The model achieved notable scores, including a BLEU_1 score of 0.591, a BLEU_2 score of 0.347, a BLEU_3 score of 0.277 and a BLEU_4 score of 0.155. These results highlight the efficiency and efficacy of the model in producing precise radiology reports, enhancing image interpretation and clinical decision-making.

This work is the first of its kind, which employs DyCNN as an encoder to extract features from CXR images. In addition, GRU as the decoder for language modeling was utilized and the attention mechanisms into the model architecture were incorporated.