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The explosion of data due to the sophistication of information and communication technology makes it simple for prospective tourists to learn about previous hotel guests' experiences. They prioritize the rating score when selecting a hotel. However, rating scores are less reliable for suggesting a personalized preference for each aspect, especially when they are in a limited number. This study aims to recommend ratings and personalized preference hotels using cross-domain and aspect-based features.

We propose an aspect-based cross-domain personalized recommendation (AsCDPR), a novel framework for rating prediction and personalized customer preference recommendations. We incorporate a cross-domain personalized approach and aspect-based features of items from the review text. We extracted aspect-based feature vectors from two domains using bidirectional long short-term memory and then mapped them by a multilayer perceptron (MLP). The cross-domain recommendation module trains MLP to analyze sentiment and predict item ratings and the polarities of the aspect based on user preferences.

Expanded by its synonyms, aspect-based features significantly improve the performance of sentiment analysis on accuracy and the F1-score matrix. With relatively low mean absolute error and root mean square error values, AsCDPR outperforms matrix factorization, collaborative matrix factorization, EMCDPR and Personalized transfer of user preferences for cross-domain recommendation. These values are 1.3657 and 1.6682, respectively.

This study assists users in recommending hotels based on their priority preferences. Users do not need to read other people's reviews to capture the key aspects of items. This model could enhance system reliability in the hospitality industry by providing personalized recommendations.

This study introduces a new approach that embeds aspect-based features of items in a cross-domain personalized recommendation. AsCDPR predicts ratings and provides recommendations based on priority aspects of each user's preferences.

This study aims to investigate the impact of consumer ethnocentrism on consumers' evaluation of blockchain-based traceability information. It also examined how the use of quick response (QR) codes for traceability affects consumers' evaluation of traceable food products.

An online choice experiment was conducted to determine consumers' evaluation of the blockchain-based traceability of Feta cheese with a quota sample of 715 Greek consumers. Pearson bivariate correlation and mean comparison were used to examine the relationship between consumer ethnocentrism and QR use behaviour. Random parameter logit models were employed to examine consumers’ valuation of the examined attributes and interaction terms.

The results show that ethnocentric consumers are willing to pay more for blockchain-based traceability information. Ethnocentric consumers tend to scan QR codes with traceability information. Spending more time reading traceability information embedded in QR codes does not lead to a higher willingness-to-pay (WTP) for traceable food products.

The findings suggest that patriotic marketing messages can draw consumers' attention to blockchain-based traceability information. The modest WTP for and low familiarity with blockchain-based traceability systems raise the need for educating consumers regarding the benefits of blockchain in traceability systems.

This is the first study to provide timely empirical evidence of a positive WTP for blockchain-based traceability information for a processed dairy product. This study is the first to attempt to distinguish the effects of the intention to scan QR codes and reading information embedded in QR codes on consumers’ valuation of food attributes.

With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.

In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.

Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.

In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.

Drawing upon the social identity theory (SIT), the present study aims to examine the moderating role of abusive supervision (AS) and job embeddedness (JE) in the relationship between career plateau (CP) and counterproductive work behaviour (CWB). The research also aims to investigate whether JE moderated the moderating effect of AS on the CP–CWB relationship.

The hypotheses were tested with two-wave survey data collected from 290 employees working in India’s banking, financial services and insurance sector. Data were analysed using moderation and moderated moderation analyses on PROCESS v 4.1 macro.

Results showed that AS moderated the CP–CWB relationship, whereas the moderating role of JE was not observed. However, JE was seen to moderate the moderating effect of AS, supporting the moderated moderation framework.

The present study adds value to the existing literature by connecting SIT with hierarchical layers. The supervisor themselves may stay longer in their current positions and block the subordinates’ progress. This impacts the social image of the subordinates. The study enriches the CP literature by highlighting that CP may lead to CWB, as the employees who perceive CP hit back at the organisation for being unfairly treated and not getting the career progression due to their supervisor.

The study provides important implications for the supervisors who need to introspect if their behaviour is viewed as abusive by the career-plateaued employees. They need to mentor the employees, especially those with higher career aspirations, and provide them with various career avenues. Furthermore, organisations should make all possible efforts to embed the employees within their jobs as the embedded employees can better take the shock of CP.

Drawing on the SIT, the study contributes uniquely to the employee behaviour literature by investigating the impact of CP, AS and JE on CWB in hierarchically flatter organisations. This is the first study to investigate the moderated moderation model of AS and JE in the CP–CWB relationship in the context of employees’ social status within the organisation.

In this viewpoint article, the authors recognize the increased focus in health systems on co-design for innovation and change. This article explores the role of leaders and mangers in developing and enhancing a culture of trust in their organizations to enable co-design, with the potential to drive innovation and change in healthcare.

Using social science analyses, the authors argue that current co-design literature has limited focus on interactions between senior leaders and managers, and healthcare staff and service users in supporting co-designed innovation and change. The authors draw on social and health science studies of trust to highlight how the value-based co-design process needs to be supported and enhanced. We outline what co-design innovation and change involve in a health system, conceptualize trust and reflect on its importance within the health system, and finally note the role of senior leaders and managers in supporting trust and responsiveness for co-designed innovation and change.

Healthcare needs leaders and managers to embrace co-design that drives innovation now and in the future through people – leading to better healthcare for society at large. As authors we argue that it is now the time to shift our focus on the role of senior managers and leaders to embed co-design into health and social care structures, through creating and nurturing a culture of trust.

Building public trust in the health system and interpersonal trust within the health system is an ongoing process that relies upon personal behavior of managers and senior leaders, organizational practices within the system, as well as political processes that underpin these practices. By implementing managerial, leadership and individual practices on all levels, senior managers and leaders provide a mechanism to increase both trust and responsiveness for co-design that supports innovation and change in the health system.

Humane Entrepreneurship (HumEnt) is strongly purpose-oriented and characterized by a focus on inclusiveness and social and environmental sustainability, with attention to both internal and external stakeholders and their needs. In the attempt to provide new research in this field, this study aims to conduct an empirical investigation within the theory of HumEnt and, in particular, of the Human Resource Orientation (HRO) model among Italian Small and Medium-size Enterprises.

Based on quantitative data, this study used a deductive approach to investigate the relationship between the HumEnt model and firms’ relational embeddedness with different types of stakeholders (value chain stakeholders and societal stakeholders, respectively). More concretely, to investigate the relationships between the dimensions of the HumEnt model and firms’ relational embeddedness, partial least squares structural equation modeling was applied.

Findings of this study suggest that Entrepreneurial Orientation (EO) directly contributes only to value chain embeddedness. However, the results also show that if EO is mediated by an HRO (i.e. companies with a high HRO), a high level of societal embeddedness is also present.

This study represents a first attempt to provide comprehensive empirical evidence about the different dimensions characterizing the HumEnt theoretical model, and to highlight their relevance in supporting companies’ relational embeddedness capacity with different categories of stakeholders.

In the 21st century, placing higher education institutions in the global world has become the norm. Therefore, many higher education institutions in Ghana and across the globe have set out to internationalise or become world-class universities as part of their strategic ambitions. Thus, finding ways to become visible on a global scale and transcend beyond the countries in which they operate has become of major interest to most universities. The authors of this chapter were curious to determine how universities adopt imported organisational templates as a strategic ambition. One should not assume that the semblance of such imported concepts is mere institutional isomorphism stemming from internationalisation and globalisation. The study employed semi-structured interviews and institutional documents as data collection tools among ten (10) university actors in a flagship university in Ghana. The study used postcolonial theory to critically examine the drivers and current practices embedded in dominant hegemonic global discourses, such as internationalisation. The findings revealed that the drivers and reforms underpinning university internationalisation ambition are framed within economic rationalities, producing human capital, self-marketisation to promote visibility, and a quest for global competition couched within global neoliberal ideology. The study recommends the need for university actors to (re)focus and (re)evaluate university internationalisation discourse to ensure a balance between local relevance and global forces.

A clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as causing viewers to feel tricked and unhappy, causing long-term confusion, and even attracting cyber criminals. Automatic detection algorithms for clickbait have been developed to address this issue. The fact that there is only one semantic representation for the same term and a limited dataset in Chinese is a need for the existing technologies for detecting clickbait. This study aims to solve the limitations of automated clickbait detection in the Chinese dataset.

This study combines both to train the model to capture the probable relationship between clickbait news headlines and news content. In addition, part-of-speech elements are used to generate the most appropriate semantic representation for clickbait detection, improving clickbait detection performance.

This research successfully compiled a dataset containing up to 20,896 Chinese clickbait news articles. This collection contains news headlines, articles, categories and supplementary metadata. The suggested context-aware clickbait detection (CA-CD) model outperforms existing clickbait detection approaches on many criteria, demonstrating the proposed strategy's efficacy.

The originality of this study resides in the newly compiled Chinese clickbait dataset and contextual semantic representation-based clickbait detection approach employing transfer learning. This method can modify the semantic representation of each word based on context and assist the model in more precisely interpreting the original meaning of news articles.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

At the moment, in terms of both research and commercial products, smart shoe technology and applications seem not to attract the same magnitude of attention compared to smart garments and other smart wearables such as wrist watches and wrist bands. The purpose of this study is to fill this knowledge gap by discussing issues regarding smart shoe sensing technologies, smart shoe sensor placements, factors that affect sensor placements and finally the areas of smart shoe applications.

Through a review of relevant literature, this study first and foremost attempts to explain what constitutes a smart shoe and subsequently discusses the current trends in smart shoe applications. Discussed in this study are relevant sensing technologies, sensor placement and areas of smart shoe applications.

This study outlined 13 important areas of smart shoe applications. It also uncovered that majority of smart shoe functionality are physical activity tracking, health rehabilitation and ambulation assistance for the blind. Also highlighted in this review are some of the bottlenecks of smart shoe development.

To the best of the authors’ knowledge, this is the first comprehensive review paper focused on smart shoe applications, and therefore serves as an apt reference for researchers within the field of smart footwear.