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In a complex, ever-changing, and turbulent business world, encouraging employees to express their improvement-oriented novel ideas through voice behavior is crucial for organizations to survive and thrive. Understanding how to foster employee promotive voice at work is a significant issue for both researchers and managers. This study explores how to foster employee promotive voice through specific HRM practices and positive employee attitudes. It also examines the effect of employee promotive voice on perceived organizational performance.

This study employed a time-lagged multisource survey design. Data were collected from 215 executives, 790 supervisors, and 1,004 employees in 113 firms, and analyzed utilizing a multilevel moderated serial mediation model.

The findings of this study revealed that promotive voice was significantly related to perceived organizational performance. Innovation-enhancing HRM was positively associated with employee promotive voice. The HRM-voice relationship was partially mediated by employee job satisfaction. Power distance orientation was found to significantly moderate the relationship between innovation-enhancing HRM and employee job satisfaction at the firm level. Our findings showed that innovation-enhancing HRM policies may fail to foster promotive voice if they do not enhance employee job satisfaction.

This study challenges some taken-for-granted assumptions in the literature such as any high performance HRM bundles (e.g. HPWS) can foster employee promotive voice, and the effects of HRM are direct and even unconditional on organizational outcomes. It emphasizes the need to avoid potential unintended effects of HRM on employee voice and the importance of contextualizing voice research.

This paper investigates the buy online and pick up in-store cooperation (BOPSC) of online and offline retailers. Specifically, this study solves the following questions: (1) What is the impact of BOPSC on their optimal price and sales volume of products? (2) When should an online retailer and an offline retailer conduct the BOPSC strategy with each other?

The paper first establishes two game models to explore the equilibriums of online and offline retailers in non-BOPSC and BOPSC. Then the condition for online and offline retailers to implement BOPSC strategy are determined. Furthermore, the applicability of the BOPSC strategy is enhanced by incorporating numerical analysis.

The study’s findings reveal that BOPSC strategy will not always beneficial to online and offline retailers, which depends on the total cost of online shopping and the product valuation of consumers. BOPSC strategy leads to the increase of prices and online orders, and the demand of offline retailer is eroded. Moreover, BOPS cooperation between different retailers is easier to achieve than omni-channel integration strategy. When the convenience difference between offline shopping and BOPSC pick-up is moderate, the effectiveness of BOPSC strategy can be improved.

This study has the following two main contributions: Firstly, the authors investigate the effects of BOPSC strategy on the prices of online and offline retailers. The study results show that the BOPSC strategy alleviates price competition and promotes a win–win situation between online retailers and offline retailers. Secondly, this paper mainly studies the cooperative behavior between online and offline retailers and reveals the optimal conditions for online and offline retailers to adopt BOPSC strategy. It can help small- and medium-sized online and offline retailers to choose suitable products for BOPSC strategy, so as to achieve the purpose of increasing profit.

Single-shot multi-category clothing recognition and retrieval play a crucial role in online searching and offline settlement scenarios. Existing clothing recognition methods based on RGBD clothing images often suffer from high-dimensional feature representations, leading to compromised performance and efficiency.

To address this issue, this paper proposes a novel method called Manifold Embedded Discriminative Feature Selection (MEDFS) to select global and local features, thereby reducing the dimensionality of the feature representation and improving performance. Specifically, by combining three global features and three local features, a low-dimensional embedding is constructed to capture the correlations between features and categories. The MEDFS method designs an optimization framework utilizing manifold mapping and sparse regularization to achieve feature selection. The optimization objective is solved using an alternating iterative strategy, ensuring convergence.

Empirical studies conducted on a publicly available RGBD clothing image dataset demonstrate that the proposed MEDFS method achieves highly competitive clothing classification performance while maintaining efficiency in clothing recognition and retrieval.

This paper introduces a novel approach for multi-category clothing recognition and retrieval, incorporating the selection of global and local features. The proposed method holds potential for practical applications in real-world clothing scenarios.

There is a wealth of value hidden in regional cultural heritage, but its preservation status is not optimistic. This study introduces a method that focuses on the inherent cultural value of regional cultural heritage to preserve it by value construction and release.

Based on the great value of regional cultural heritage due to spatial adjacency and temporal continuity, this paper focuses on its inherent cultural value to explore the preservation path and chooses Shichahai cultural heritage digital resources for a case study. This paper draws lessons from the narrative method of ancient Chinese historiography, constructs a cultural space and tells cultural stories. A linked data organization model for digital resources is created to construct a conceptual cultural space. Then, the space is materialized by linked dataset creation. The authors tell cultural stories discovered from the space, which are presented by various user interfaces using visualization technologies.

A cultural space promotes the development of a fine-grained description of regional cultural heritage and aids in relationship discovery to enhance the value construction ability. Additionally, storytelling via interactive user interfaces is helpful in the utilization and dissemination of knowledge extracted from a cultural space and enhances the value release of regional cultural heritage. In this way, a path with the inherent cultural value of regional cultural heritage as the core is established, and preservation is achieved.

This study focuses on the inherent cultural value of regional cultural heritage and proposes a new path to preserve these resources. This approach will enrich research on the preservation of regional cultural heritage and contribute to the construction and release of its cultural value.

This study used an integrated framework that incorporates the technology acceptance model (TAM) (Davis, 1989), the theory of planned behavior (TPB) (Ajzen, 1991) and trust to examine factors that mainly influence consumers' intention towards the use of smart technologies in tourism and hospitality (T&H) industry. The Internet of things (IoT), artificial intelligence (AI), virtual reality systems, augmented reality systems, etc. are the Smart 4.0 technologies generally used in T&H industry these days.

Convenience sampling approach was employed in this study. Data were collected over the Internet using a survey instrument by posting the questionnaire link on social network web pages of travel agencies from November 10, 2021, to December 30, 2021. In the opening statement of the questionnaire, we have explained about the Smart 4.0 technologies so that every respondent could understand what we mean by Smart 4.0 technologies.

The findings show that conjoining the TAM and the TPB with trust resulted in a robust model for explaining customers' intention toward using smart technologies in the T&H industry.

Smart technologies have become one of the most profitable e-commerce applications. This study examines and integrates the various advantages of smart technologies for the consumers in T&H industry, as well as providing insight into the intentions of Indian consumers. Hence, this study gives significant information to IT companies, online travel agencies, tour operators, travel agents, T&H planners and other stakeholders on Indian consumers' behavioral intentions (BIs).

This study tested the utility of the extended model in predicting consumers' intention towards the use of smart technologies in T&H industry. As far as the authors' knowledge is concerned, this is the first study that predicted intention of Indian consumers towards the use of smart technologies in T&H industry by integrating TAM, TPB and trust.

The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.

The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.

Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.

The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.

The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.

This paper aims to characterize the surface film formed on Alloys 800 and 690 in chloride and thiosulfate-containing solution at 300°C.

Alloy 800 and 690 were immersed in chloride and thiosulfate-containing solution at 300°C up to five days, and then the surface film was analyzed by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM) and energy dispersive X-ray spectrometers (EDX).

Through static immersion experiments in a high-temperature and high-pressure water environment, the alloy samples covered by surface film after five days of immersion were obtained. The morphology of the surface film was characterized at both horizontal and cross-sectional scales using SEM and focused ion beam-TEM techniques. It was observed that due to the influence of the quartz lining, the surface film primarily exhibited a bilayered structure. The first layer contained a significant amount of SiO₂, with a higher content of metal hydroxides compared to metal oxides. The second layer was predominantly composed of Fe, Ni and Cr, with a higher content of metal oxides compared to metal hydroxides.

The results showed that the materials of the lining of the autoclave could significantly influence the film composition of the tested material, which should be paid attention when analyzing the corrosion mechanism at high temperature.

Sustainability issues are crucial in today’s competitive environment. The integration of technology plays a vital role in the attainment of sustainability objectives. The study aims to investigate the relationship between green intellectual capital (IC), green information systems (IS), green management initiatives (GMI) and green technology adoption in light of natural resource-orchestration theory (ROT). Moreover, digital technology adoption mediates between green IC, green IS, GMI and sustainable performance. Finally, digital transformation strategy is used as a moderator between green technology adoption and sustainable performance.

A sample of 484 managers from automobile manufacturing companies was used in this study to evaluate the proposed relationships using the Structural Equation Modeling (SEM) methodology.

Findings reveal that green IC, green IS and GMI significantly influence green technology adoption. Besides, green technology adoption plays a crucial role in improving sustainable performance. Moreover, green technology adoption significantly mediates between green IC, green IS, GMI and sustainable performance. Finally, a digital transformation strategy significantly strengthens the relationship between green technology adoption and sustainable performance.

The organizations need green technology adoption to address environmental concerns, respond to consumer demand, achieve cost savings and comply with government regulations. Besides, in decision-making, organizations must focus on green IC, green IS, GMI, green technology adoption and digital transformation strategy to boost sustainable performance.

The originality of this study lies in its use of the natural ROT as a framework to examine the impact of multiple green resources on green technology adoption, leading to sustainable performance. Digital transformation strategy is used as a moderator between green technology adoption and sustainable performance. This study provides a comprehensive and integrated perspective on the subject with empirical evidence and relevant insights, contributing to the advancement of the field.

We explore the driving forces behind the channel choices of the manufacturer and the platform by considering asymmetric selling cost and demand information.

This paper develops game-theoretical models to study different channel strategies for an E-commerce supply chain, in which a manufacturer distributes products through a platform that may operate in either the marketplace channel or the reseller channel.

Three primary models are built and analyzed. The comparison results show that the platform would share demand information in the reseller channel only if the service cost performance is relatively high. Besides, with an increasing selling cost, the equilibrium channel might shift from the marketplace to the reseller. With increasing information accuracy, the manufacturer tends to select the marketplace channel, while the platform tends to select the reseller channel if the service cost performance is low and tends to select the marketplace channel otherwise.

All these results have been numerically verified in the experiments. At last, we also resort to numerical study and find that as the service cost performance increases, the equilibrium channel may shift from the reseller channel to the marketplace channel. These results provide managerial guidance to online platforms and manufacturers regarding strategic decisions on channel management.

Although prior research has paid extensive attention to the driving forces behind the online channel choice between marketplace and reseller, there is at present few study considering the case where a manufacturer selling through an online platform faces a demand information disadvantage in the reseller channel and sales inefficiency in the marketplace channel. To fill this research gap, our work illustrates the interaction between demand information asymmetry and selling cost asymmetry to identify the equilibrium channel strategy and provides useful managerial guidelines for both online platforms and manufacturers.

Drawing upon work-home resources model, this study aims to investigate how and when humble leadership influences followers’ work–family enrichment. Specifically, this study focuses on the mediating role of thriving at work and moderating role of promotion focus.

Data were collected from 292 employees of science and technology enterprises in China through a three-wave questionnaire survey. Hierarchical regression analysis and bootstrapping approach were employed to test hypotheses.

This study found that thriving at work significantly mediated the relationship between humble leadership and work–family enrichment. Promotion focus strengthened the positive relationship between humble leadership and thriving at work and the indirect effect of humble leadership on work–family enrichment through thriving at work.

The findings of this study offer guidance for managers to enhance thriving at work and improve employees’ work–family experiences.

First, this study explores the work-to family spillover effects of humble leadership by examining the family outcomes of humble leadership. Second, this study further uncovers the underlying mechanism between humble leadership and work–family enrichment by demonstrating the mediating role of thriving at work. Third, by exploring the moderating role of promotion focus, this study provides insight into the boundary conditions of the impact of humble leadership.