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Gamification is a strategic approach employed by practitioners to foster meaningful engagement and enhance the acceptance of recommendations. Gamification affordances (e.g. achievement, self-expression, interaction, and cooperation) catalyze significant psychological processes in consumers, leading to behavioral changes. Despite its application, a gap remains in understanding how these gamification affordances in e-commerce contexts impact customers' perceived values and drive recommendation acceptances.

Employing affordance theory and perceived value theory as our foundation, we have crafted a comprehensive framework that addresses the multifaceted nature of e-commerce gamification, thereby unifying the fragmented knowledge in this area. We implemented a quantitative research design to empirically test the proposed model.

The research reveals that the four principal affordances of gamification – achievement, self-expression, interaction, and cooperation – significantly enrich consumer values across hedonic, utilitarian, and social dimensions. This enrichment facilitates an increased propensity for accepting recommendations.

This study provides a novel lens through which to view the influence of gamification affordances on recommendation acceptance within gamified e-commerce settings. It delineates the effects of each affordance on consumers' perceived value and highlights the pivotal affordances that shape gamified e-commerce experiences. These insights yield actionable strategies for practitioners aiming to refine e-commerce gamification designs and cultivate more engaging consumer interactions.

Service robots are increasingly prevalent in the hospitality industry. While studies have explored the concept of service robot risk awareness (SRRA) – an employee’s perception of service robots posing a threat to human labor – the impact of SRRA on robot abuse and its emotional mechanism through which it affects employees remains unclear. This research leverages emotional appraisal theory to investigate the mediating role of fear of robots in the relationship between SRRA and robot abuse. Additionally, considering the influential role of leadership in shaping emotional appraisal, this study aims to examine the moderating impact of transformational leadership.

To test the proposed model, time-lagged survey data were collected from 283 employees working under 54 leaders in 18 hotels in China. The model was analyzed using multilevel modeling in Mplus 7.3.

At the individual level, SRRA indirectly increases robot abuse through the mediation of fear of robots. However, there is a cross-level moderation: the indirect relationship is alleviated when leaders exhibit high levels of transformational leadership.

This study pioneers the concept of robot abuse in hospitality and tourism settings. It extends emotional appraisal theory by highlighting the significant mediating role played by fear of robots. Furthermore, demonstrating how transformational leadership can mitigate the effects of SRRA offers valuable insights for leadership selection and training to facilitate the successful implementation of service robots.

服务机器人在酒店业中日益普及。虽然研究已探讨了服务机器人风险意识（SRRA）的概念——即员工对服务机器人构成对人力劳动的威胁感知, 但SRRA对辱虐机器人及其对员工的情绪机制的影响仍不清楚。本研究利用情绪评估理论调查了恐惧对SRRA与机器人滥用之间关系的中介作用。此外, 考虑到领导在塑造情绪评估中的重要作用, 本研究还考察了变革型领导力的调节影响。

为了测试提出的模型, 收集了来自中国18家酒店中54位领导下的283名员工的时滞调查数据。该模型使用Mplus 7.3中的多层建模进行分析。

在个体水平上, SRRA通过恐惧对机器人的中介作用间接增加了辱虐机器人。然而, 研究发现跨层次调节变量：当领导展现出较高水平的变革型领导力时, 间接关系得到缓解。

本研究首创了服务在酒店和旅游领域的辱虐机器人行为概念。它通过突出恐惧对机器人的重要中介作用, 扩展了情绪评估理论。此外, 展示了变革型领导如何缓解SRRA的影响, 为领导选聘和培训提供了有价值的见解, 促进了服务机器人的成功实施。

In the context of the digital age, this study aims to investigate the impact of citizens' digital participation on the scientific and democratic decision-making processes of the government. Specifically, the authors focus on the factors influencing citizens' digital participation, with a particular emphasis on their digital skills.

Exploring the influence of citizens' digital skills on their digital participation is of great practical significance for eliminating the digital divide and for promoting a life characterized by enriched digital interactions with the public. This study selected the social consciousness survey database of Chinese netizens in 2017, used ordered Probit and OLS models, and comprehensively used the instrumental variable method (IV), causal stepwise regression method and bootstrap method to empirically verify and construct a mechanism model of the influence of digital skills on citizens' digital participation.

The empirical findings indicate a noteworthy positive association between citizens' proficiency in digital skills and their active engagement in digital activities. This relationship is positively mediated by factors such as political interest and attention to social issues, underscoring their role in encouraging greater digital participation. Conversely, national identity exhibits a counteractive influence on this mechanism, potentially discouraging digital engagement. Notably, the impact of digital skill mastery on digital participation is more pronounced among non-elderly individuals and those residing in metropolitan areas, highlighting the significance of demographic characteristics in this context.

These research results can help the government and other organizations make better decisions and facilitate improvement of citizens' digital participation by promoting their mastery of digital skills.

In the supply chain disruption risk, the issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

Considering the influence of irrational emotions of decision makers, an evaluation model is designed by the regret theory and VIKOR method, which makes the decision-making process closer to reality.

The paper has some innovations in the evaluation index system and evaluation model construction. The method has good stability under the risk of supply chain interruption.

The mixed evaluation information is used to describe the attributes, and the evaluation index system is constructed by the combined method of the social network analysis method and the literature research method to ensure the accuracy and accuracy of the extracted attributes. The issue of supplier evaluation and selection is solved by an extended VIKOR method based on regret theory.

There are over 300,000 male migrant workers in Singapore. Around 600 major workplace injuries are reported in Singapore each year, mainly in the manufacturing and construction injuries. Migrant workers who are affected by workplace injuries often face many challenges, including not being able to work and thus may be repatriated to their home countries, which affects their financial status and that of their families, whom they support. This research aims to explore the knowledge, attitudes and beliefs of injured migrant workers in Singapore, towards disability and vocational rehabilitation.

Fifteen male migrant workers, from Bangladesh, China and India, who had acquired disabling injuries in their workplaces in Singapore, were identified through purposive sampling. They were interviewed by a male interviewer, either in Mandarin Chinese or with the assistance of interpreters for Bengali-English and Tamil-English. Interviews were recorded, transcribed, translated to English, then analysed thematically.

The interviewees generally had a pessimistic outlook on their disability, which often impacted negatively on their self-worth and familial relationships. Many of them also had little knowledge of vocational rehabilitation and had not yet seriously considered future job prospects.

To the best of the authors’ knowledge, there are no similar studies exploring the knowledge, attitudes and beliefs of injured migrant workers in Singapore towards disability and vocational rehabilitation.

Drawing from resource orchestration theory, this research proposed an integrative model that leverages insights into counter resource constraints and uncertainty in start-up business model innovation (BMI). It investigated the influences of entrepreneurial networks and effectuation on BMI through bricolage in uncertain environments.

The research surveyed 481 start-ups in China. LISREL 8.80 and SPSS 22.0 were employed to test the validity and reliability of key variables, respectively. Additionally, hypotheses were examined through multiple linear regression.

First, entrepreneurial networks and effectuation were positively related to BMI, and combining these two factors improved BMI for start-ups. Second, bricolage contributed to BMI and played mediating roles in translating entrepreneurial networks and effectuation into BMI. Third, environmental uncertainty weakened the linkage between bricolage and BMI.

Future research should replicate the results in other countries because only start-ups in China were investigated in the study, and it is necessary to extend this research by gathering longitudinal data. This research emphasized the mediating effects of bricolage and the moderating influence of environmental uncertainty, and new potential mediating and moderating factors should be explored between resources and BMI.

There are three significant theoretical contributions. First, the findings enrich the literature on the complex antecedents of BMI by combining the impacts of entrepreneurial networks and effectuation. Second, an overarching framework is proposed explaining how bricolage (resource management) links entrepreneurial networks and effectuation and BMI. Third, it demonstrates the significance of environmental uncertainty in the bricolage–BMI linkage, deepening the understanding of the bricolage boundary condition.

Wine producers and marketing professionals increasingly recognize the significance of online wine reviews. Emotions have long been acknowledged as influential in online review behaviors. However, considering the multisensory nature of the wine experience, consumers’ wine expertise also plays a substantial role. Hence, this study aims to examine the online review behaviors exhibited by wine consumers through the dual lens of wine expertise and emotionality.

Two studies were conducted to address the research question. Study 1 explored the relationship among expertise, emotionality and review behaviors using a panel data model, with a data set consisting of 4,600,922 reviews from Vivino.com. Study 2 used a multigroup structural equation modeling (SEM) analysis using data obtained from an online survey. Study 2 aimed to investigate the interactive impact of emotionality and expertise on online review intention mediated by customer engagement.

The findings from Study 1 demonstrated a positive correlation between emotionality and online wine reviews. In addition, expertise displayed a bell-shaped relationship with both emotionality and online wine reviews. Study 2, in turn, uncovered that novices and experts experienced a direct influence of emotionality on their review intentions. In contrast, for those classified as ordinary, the influence of emotionality on review intention occurred indirectly through the mediation of customer engagement.

This paper extends the current literature on online wine review by integrating the effect of emotion and expertise on online wine review behaviors, expanding the examination of Dunning–Kruger effect in the wine literature. It also adds value by introducing emotionality and the Evaluative Lexicon into the hospitality literature, extending the measurement of emotion from valence and extremity to a third dimension, emotionality, in hospitality and wine domains.

The density peak clustering algorithm (DP) is proposed to identify cluster centers by two parameters, i.e. ρ value (local density) and δ value (the distance between a point and another point with a higher ρ value). According to the center-identifying principle of the DP, the potential cluster centers should have a higher ρ value and a higher δ value than other points. However, this principle may limit the DP from identifying some categories with multi-centers or the centers in lower-density regions. In addition, the improper assignment strategy of the DP could cause a wrong assignment result for the non-center points. This paper aims to address the aforementioned issues and improve the clustering performance of the DP.

First, to identify as many potential cluster centers as possible, the authors construct a point-domain by introducing the pinhole imaging strategy to extend the searching range of the potential cluster centers. Second, they design different novel calculation methods for calculating the domain distance, point-domain density and domain similarity. Third, they adopt domain similarity to achieve the domain merging process and optimize the final clustering results.

The experimental results on analyzing 12 synthetic data sets and 12 real-world data sets show that two-stage density peak clustering based on multi-strategy optimization (TMsDP) outperforms the DP and other state-of-the-art algorithms.

The authors propose a novel DP-based clustering method, i.e. TMsDP, and transform the relationship between points into that between domains to ultimately further optimize the clustering performance of the DP.

The drone food delivery service (DFDS) is a revolutionary technology owing to its ability to reduce delivery costs, alleviate traffic congestion, and offer a more environmentally friendly alternative compared to traditional delivery methods. While studies have been conducted to understand consumers’ intentions towards DFDS, very few of them considered internal factors such as personality traits. Considering the aforementioned factors, this research employs the belief-desire-intention (BDI) model and the big five personalities (BFP) traits to explore how personality traits (neuroticism, extraversion, agreeableness, conscientiousness, and openness) moderate the associations between the desire for DFDS and consumers’ intention to use DFDS (ITU).

Survey questionnaires were distributed online via Facebook and WhatsApp. A total of 359 responses were considered valid, and the study employed the partial least squares structural equation modelling approach to test the hypotheses.

The study revealed a positive impact of the desire for DFDS on ITU. Additionally, extraversion and agreeableness were found to moderate the effect of the desire for DFDS on ITU.

This study is the first in DFDS literature to employ the BDI model, showcasing its effective application in understanding the desire-to-intention relationship. Also, this is the first study that explores the moderating role of the BFP traits in the context of DFDS usage intention. The results provide insights for developing marketing strategies to encourage DFDS usage intention based on consumers' personality traits.

The purpose of this paper is to analyze manufacturers' production decisions and governments' low-carbon policies in the context of influencer spillover effects.

This paper investigates the impact of the social influencer spillover effect on manufacturers' production decisions when they collaborate with intermediary platforms to sell products through marketplace or reseller modes. Game theory and static numerical comparison are used to analyze our models.

Firstly, under low-carbon policies, the spillover effect does not always benefit manufacturer profits and changes non-monotonically with an increasing spillover effect. Secondly, in cases where there are both a carbon emission constraint and a spillover effect present, if either the manufacturer or intermediary platform holds a strong position, then marketplace mode benefits manufacturer profits. Thirdly, regardless of business mode used when environmental damage coefficient is high for products; government should implement cap-and-trade regulation to optimize social welfare while reducing manufacturers’ carbon emissions.

This study offers theoretical and practical research support to assist manufacturers in optimizing production decisions for compliance with carbon emission limits, enhancing profits through the development of effective influencer marketing strategies, and providing strategies to mitigate carbon emissions and enhance social welfare while sustaining manufacturing activities.

This paper addresses the limitations of prior research by examining how the social influencer spillover effect influences manufacturers' business mode choices under government low-carbon policies and analyzing the social welfare of different carbon emission restrictions when such spillovers occur. Our findings provide valuable insights for manufacturers in selecting optimal marketing strategies and business modes and decision-makers in implementing effective regulations.