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This study elucidated the connections among the influence of Singaporean hawkers, local gastronomy involvement, and the three dimensions of authenticity (objective, constructive, and existential). Furthermore, it investigates how personal nostalgia affects the cultural identity of hawkers.

A self-administered questionnaire was created to assess hawker influence, gastronomy involvement, authenticity, personal nostalgia, and hawker cultural identity. Survey data was gathered from 401 Singapore residents aged 18 and older.

Results of the structural equation modeling revealed various significant aspects of hawker influence, including physical and social environments, uniqueness and cultural significance, and hygiene and food safety. Hawker influence and local gastronomy contributed to objective authenticity, which, in turn, affected constructive and existential authenticity, ultimately shaping personal nostalgia and hawker cultural identity.

The study offers guidance for stakeholders in sustaining hawker culture, emphasizing authenticity’s role and the importance of nostalgia in identity formation. By aligning with the progressive nature of Singapore, these implications aim to ensure the continued thriving of this invaluable legacy for generations to come.

The study affirms relationships between hawker influence, local gastronomy involvement, and authenticity constructs. It emphasizes the hawker’s role and gastronomy involvement in influencing individuals’ perceived authenticity and accentuates the potential for authenticity in strengthening national branding.

Humanoid social robots (HSRs) are an innovative technology revitalizing various service sectors, such as the hospitality industry. However, limited research has explored how anthropomorphic features of HSRs influence user satisfaction with the services delivered by HSRs. To address this, a research model was proposed to evaluate how three distinct anthropomorphic features: appearance, voice and response, impact the perceived values (i.e. utilitarian, social and hedonic values) of HSRs, which, in turn, influence user satisfaction.

Data from an online survey of hotel customers was utilized to test the research model (N = 509).

The results indicated that appearance, voice, and response affect perceived utilitarian, hedonic and social values differently. The response feature of HSRs demonstrated the strongest impact on perceived utilitarian, social and hedonic values. In addition, voice affected all three perceived values, while appearance only affected perceived utilitarian and social values. Furthermore, perceived utilitarian, hedonic and social values showed positive impacts on user satisfaction, with hedonic value being the most influential factor.

This study contributes to the literature on HSRs and anthropomorphism by explaining how different anthropomorphic features affect users’ value perceptions and user satisfaction with HSR services by utilizing the stimulus-organism-response (SOR) framework.

Hospitality and tourism businesses often face environmental criticism as they rely heavily on natural resources to operate. Therefore, as a recent trend, hospitality companies are trying to adopt an environmentally friendly approach. Thus, this study sought to investigate the determinants of employee intention to engage in environmentally responsible actions in the workplace, drawing on the theory of planned behavior (TPB) and the value-belief norm (VBN) theory.

This study employed the fuzzy-set qualitative comparative analysis (fsQCA) to discover sufficient configurations for predicting employees’ intentions.

The result has provided recipes with an efficient combination of factors that can influence employees’ intention to undertake environmentally responsible behaviors.

This study contributes to the body of knowledge regarding sustainable behavior among employees and sustainability in the travel and hospitality sector. The findings of this research also provide managers and operators of sustainable hospitality businesses with guidance on how to enhance their staff members' environmentally friendly behaviors at work.

This paper aims to investigate how institutional entrepreneurs in a mature field acquire different forms of legitimacy through various narrative strategies, as revealed by a historical analysis of the Late Qing Dynasty of China. Specifically, the study seeks to illuminate the narrative techniques employed by these entrepreneurs to build multi-level legitimacies for their new systems during the national crises of the late 19th century.

This study employs a qualitative approach based on three historical case studies of Westernization, namely advocates, reformists and revolutionaries during the Late Qing Dynasty of China. It delves into the institutional entrepreneurial activities of these groups, investigating how they navigated and influenced their sociopolitical context through narrative strategies.

The findings reveal that institutional entrepreneurs utilize various narrative techniques to build legitimacy. These include (1) modifying and disseminating narratives at the proper time, (2) ascribing their proposed system to cultural tradition by reinterpreting classical works and (3) offering understandable and concrete promises to stakeholders. The study also identifies an evolving pattern of narratives underpinned by mutual learning and continuous iteration among different factions of institutional entrepreneurs.

This paper adds new insights to the literature on institutional entrepreneurs and, more broadly, to institutional research literature by advancing our understanding of the discursive dynamics underlying institutional changes. It unveils the complex interplay of narrative techniques and legitimacy building in the context of societal and institutional upheaval, providing a nuanced understanding of the role of narratives in institutional entrepreneurship.

The purpose of this teaching case is to introduce students to an alternative business model as practiced by the Haier Group, a Chinese company, and how that model was used to turn around an acquired company in the United States of America (USA). The explicit teaching objectives are threefold. First, the case provides insights into Haier’s unique employee-centered culture. Second, Haier’s efforts to transfer parts of its culture to the newly acquired General Electric (GE) Appliance Division are discussed. Third, to improve the performance of the acquired division, Haier had to invest in people, equipment and new product technology.

This case is based on both primary and secondary research. The authors interviewed the chief executive officer. In addition, one of the authors spent a week in China observing and participating in meetings at the Haier Group. Both before and after the interviews, the authors searched both print and electronic media for additional information.

The case describes how Haier, a large Chinese appliance manufacturer, learned from its own difficult growth in building an employee- and client-driven organization. Haier was able to transfer key aspects of its culture, management practices and technology to help turnaround the well-known American appliance brand GE. The results of the first five years have been financially successful and investment in new product technology (Smart Home) bodes well for the future.

This case represents only one successful turnaround of one acquisition, GE Appliances, by the Haier Group in the USA. Whether the changes introduced would work with other acquisitions in other countries is unknown. Thus, additional follow-up research needs to be done.

This case brings into question the traditional, hierarchical, bureaucratic, spreadsheet-driven model of management that is the predominant model taught and practiced in the USA. Others, such as Gary Hamel and Michele Zanini, have also raised the same question. This case introduces readers to another way and is just one more example of how managers who practice a high engagement style and share financial success with workers can outperform those who do not.

This case documents the introduction of nontraditional management and human resource management practices by a foreign, Chinese company, into what at one time had been a highly regarded division of a traditional major American corporation. GE had become known for strident labor-management relationships. The employees’ acceptance of the alternative approach to management was in doubt prior to the acquisition, but over the past five years, the labor–management relationship appears to have improved as well as the profitability of the division.

Although the acquisition of the GE Appliance Division by the Haier Group has been widely reported in the press, knowledge of how the acquisition was successfully turned around from a money-losing GE Division to a profitable and growing portion of the Haier Group has been largely ignored in both the popular press and in instructional material for the classroom. This case study seeks to ameliorate the latter deficiency.

Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in the scientific domain. However, obtaining fine-tuning data for scientific NLP tasks is still challenging and expensive. In this paper, the authors propose the mix prompt tuning (MPT), which is a semi-supervised method aiming to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks.

Specifically, the proposed method provides multi-perspective representations by combining manually designed prompt templates with automatically learned continuous prompt templates to help the given academic function recognition task take full advantage of knowledge in PLMs. Based on these prompt templates and the fine-tuned PLM, a large number of pseudo labels are assigned to the unlabelled examples. Finally, the authors further fine-tune the PLM using the pseudo training set. The authors evaluate the method on three academic function recognition tasks of different granularity including the citation function, the abstract sentence function and the keyword function, with data sets from the computer science domain and the biomedical domain.

Extensive experiments demonstrate the effectiveness of the method and statistically significant improvements against strong baselines. In particular, it achieves an average increase of 5% in Macro-F1 score compared with fine-tuning, and 6% in Macro-F1 score compared with other semi-supervised methods under low-resource settings.

In addition, MPT is a general method that can be easily applied to other low-resource scientific classification tasks.

This study quantitatively investigates the impacts of digital and learning orientations on supply chain resilience (SCR) and firm performance (FP), aiming to fill the gaps in understanding their specific impacts in the context of Industry 4.0 developments and supply chain disruptions.

This study utilized survey techniques and structural equation modelling (SEM) to gather and analyse data through a questionnaire based on a seven-point Likert scale. Hypotheses were formulated based on an extensive literature review and tested using Amos software.

The study confirms SCR’s significant impact on FP, aligning with existing research on resilience’s role in organizational competitiveness. This study uncovers the nuanced impacts of digital and learning orientations on SCR and FP. Internal digital orientation (DOI) positively impacts SCR, while external digital orientation (DOE) does not. Specific dimensions of learning orientation – shared vision (LOS), open-mindedness (LOO) and intraorganizational knowledge sharing (LOI) – enhance SCR, while commitment to learning (LOC) does not. SCR mediates the relationship between DOI and FP but not between DOE and FP.

This research focuses on digital and learning orientations, recommending that future studies investigate other strategic orientations and examine the specific contributions of various digital technologies to SCR across diverse contexts.

The empirical findings emphasize the significance of developing internal digital capabilities and specific learning orientations to enhance SCR and FP, aligning these initiatives with resilience strategies.

This study advances knowledge by distinguishing the impacts of internal and external digital orientations and specific learning dimensions on SCR and FP, offering nuanced insights and empirical validation.

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.