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As some data to evaluate the efficiency of bank branches is qualitative or uncertain, only grey numbers should be used to calculate the efficiency interval. The combination of multi-stage models and grey data can lead to a more accurate and realistic evaluation to assess the performance of bank branches. This study aims to compute the efficiency of each branch of the bank as a grey number and to group all branches into four grey efficiency areas.

The key performance indicators are identified based on the balanced scorecard and previous research studies. They are included in the two-stage grey data envelopment analysis (DEA) model. The model is run using the GAMS program. The grey efficiencies are calculated and bank branches have been grouped based on efficiency kernel number and efficiency greyness degree.

As policies and management approaches for branches with less uncertainty in efficiency are different from branches with more uncertainty, considering the uncertainty of efficiency values of branches may be helpful for the policy-making of managers. The grey efficiency of branches of one bank is examined in this study using the two-stage grey DEA throughout one year. The branches are grouped based on kernel and greyness value of efficiency, and the findings show that considering the uncertainty of data makes the results more consistent with the real situation.

The performance of bank branches is modeled as a two-stage grey DEA, in which the efficiency value of each branch is obtained as a grey number. The main originality of this paper is to group the bank branches based on two grey indexes named “kernel number” and “greyness degree” of grey efficiency value.

This study aimed to explore the impact of Artificial Intelligence (AI) characteristics, namely Perceived Animacy (PAN), perceived intelligence (PIN), and perceived anthropomorphism (PAI), on user satisfaction (ESA) and continuous intentions (CIN) by integrating Expectation Confirmation Theory (ECT), with a particular focus on Generation Y and Z.

Using a quantitative method, the study collected 495 data from Gen Y (204) and Z (291) respondents who were users of digital banking apps through structured questionnaires that were analysed using PLS-SEM. The latter helped investigate the driving forces of AI characteristics and user behavioural intentions as well as reveal generation-specific features of digital banking engagement.

The study revealed that PAN and PIN have significant positive effects on the anthropomorphic perceptions of digital banking apps, which in turn increases perceived usefulness, satisfaction, and continuous intentions. In particular, the influence of these AI attributes varies across generations; Gen Y’s loyalty is mostly based on the benefits derived from AI features, whereas Gen Z places a greater value on the anthropomorphic factor of AI. This marked a generational shift in the demand for digital banking services.

The specificity of Indian Gen Y and Z users defines the scope of this study, suggesting that demographic and geographical boundaries can be broadened in future AI-related banking research.

The results have important implications for bank executive officers and policymakers in developing AI-supported digital banking interfaces that appeal to the unique tastes of millennial customers, thus emphasising the importance of personalising AI functionalities to enhance user participation and loyalty.

This study enriches the digital banking literature by combining AI attributes with ECT, offering a granular understanding of AI’s role in modulating young consumers' satisfaction and continuance intentions. It underscores the strategic imperative of AI in cultivating compelling and loyalty-inducing digital banking environments tailored to the evolving expectations of Generations Y and Z.

Prefabricated construction (PC) can benefit construction industry due to its high efficiency, energy saving, consumption reduction and safety. However, the high capital cost is a critical challenge hindering its development in China. The collaboration of PC stakeholders is conducive to improving cost management efficiency and optimizing resource allocation which has been ignored in previous studies. Therefore, this study aims to explore the collaboration paths of stakeholders in the process of solving critical cost influencing factors (CIFs) of PC to reduce costs.

Firstly, 25 CIFs and five main stakeholders that affect PC capital cost were identified through literature research and expert interviews. Then, questionnaires were used to investigate the relationship between stakeholders and CIFs from the perspectives of three stakeholder attributes of proximity, attitude and power, respectively. Finally, based on the survey data, three stakeholder-CIF networks from three attributes perspective and a comprehensive network were constructed and used for subsequent social network analysis.

(1) Stakeholders mainly show willingness and potential to collaborate on organization and management factors; (2) More stakeholders pay attention to incentive policies and the setting of prefabrication rates and assembly rates, while all stakeholders have the right to facilitate information and resource sharing in the PC supply chain; (3) The comprehensive network shows a core-periphery structure. As core stakeholders, contractor, designer and manufacturer are more likely to actively manage the 14 core CIFs.

This paper innovatively combined stakeholder and cost management in PC, and used two-mode network based on three stakeholder perspectives to reveal the collaboration potential and motivation of stakeholders in PC cost management. The findings not only provide guidance for stakeholders to find potential partners and optimize resource allocation in solving specific cost issues, but also facilitate stakeholders' sustainable collaboration to achieve PC's cost performance.

This research aims to explore the mechanisms by which green marketing practices (GMP) influence customer loyalty (CL) and how green self-identity (GSI) moderates the relationship between green corporate image (GCI) and customer loyalty in the new energy vehicle (NEV) market.

The study surveyed individuals who had purchased new energy vehicle products through an online platform, resulting in 321 valid questionnaires obtained through a non-probability sampling method. The data were analyzed using the PLS-SEM method to test the proposed hypotheses.

The research found that green advertisement, green product quality, green product price, external green supply chain management and the salesperson’s green expertise are GMP by the company, and they had positive effects on GCI. Furthermore, GCI had a positive mediating effect between GMP and CL, while green self-identity served as a positive moderator between GMP and CL.

This paper addresses the research gap in the literature on green image and consumer markets, providing a deeper understanding of the mechanisms underpinning GMP and consumer behaviors. These insights can assist companies in shaping a GCI and enhancing CL in the NEV market.

Digitally driven virtual streamers are increasingly utilized in live-streaming commerce, possessing distinct advantages compared to human streamers. However, the applicable scenarios of virtual streamers are still unclear. Focusing on product attribute variances, this paper compares the livestreaming effects of virtual and human streamers to clarify the applicable scenarios for each and assist companies in strategically choosing suitable streamers.

We conducted four experiments utilizing both images and video as stimulus materials, and each experiment employed different products. To test the proposed model, a total of 1,068 valid participants were recruited, encompassing a diverse group of individuals, including undergraduates and employed workers.

The results indicate no significant difference between virtual and human streamers in increasing consumers’ purchase intention for utilitarian products. In contrast, human streamers are more effective in enhancing consumer purchase intention for hedonic products, with a mediating role of mental imagery quality. Consumers’ implicit personality variances also influence their willingness to accept virtual streamers.

This paper is the first to compare the effects of virtual and human streamers in promoting different products to enhance our comprehension of virtual streamers. Given the potential risks associated with human streamers, a comprehensive understanding of the role of virtual streamers is imperative for brands when deploying live-streaming commerce activities.

This study aims to build on social comparison theory to develop a theoretical model of leader–member exchange (LMX) relationship to workplace ostracism through perceived organizational status by coworkers and envy. This study further proposes that warmth and competence may potentially moderate these two indirect effects.

This study tested the hypotheses in a battery manufacturing company located in South China by a survey of 216 employees organized in 55 work teams, using different sources. Additionally, the authors conduct two online vignette experiments to test this study’s mediation, proving the causality.

The authors found that high-level LMX leads to both envy and perceived organizational status by coworkers, which results in a mixed blessing on workplace ostracism toward the employee with high-level LMX. The focal employee’s warmth and competence moderate these indirect relationships.

The authors use LMX to explore antecedents of workplace ostracism and explain how and when these focal employees suffer workplace ostracism from their coworkers. The authors extend the research on LMX by examining the interpersonal risk of being a focal employee. The authors discover two critical boundary conditions – warmth and competence.

This study suggests that it is important to balance the level of the differential LMX; appropriately endorsing other members is a good way to avoid eliciting envy and opposition. Meanwhile, person-oriented citizenship behaviors such as demonstrations of concern or help may shortly build up an employee’s warm impression on their coworkers.

By discovering the bright and dark sides of LMX, this paper has the potential to advance theories on LMX and workplace ostracism. Therefore, the authors believe the current research will have an important impact on relevant research in the future.

The purpose of this paper is to improve the mechanical and tribological properties of Si₃N₄ ceramics and to make the application of Si₃N₄ ceramics as tribological materials more extensive.

Si₃N₄-based composite ceramics (SN-2L) containing nitrogen-doped graphene quantum dots (N-GQDs) were prepared by hot press sintering process through adding 2 Wt.% nanolignin as precursor to the Si₃N₄ matrix, and the dry friction and wear behaviors of Si₃N₄-based composite against TC4 disc were performed at the different loads by using pin-on-disc tester.

The friction coefficients and wear rates of SN-2L composite against TC4 were significantly lower than those of the single-phase Si₃N₄ against TC4 at the load range from 15 to 45 N. At higher load of 45 N, SN-2L/TC4 pair presented the lowest friction coefficient of 0.25, and the wear rates of the pins and discs were as low as 1.76 × 10⁻⁶ and 2.59 × 10⁻⁴mm³/N·m. The low friction and wear behavior could be attributed to the detachment of N-GQDs from the ceramic matrix to the worn surface at the load of 30 N or higher, and then an effective lubricating film containing N-GQDs, SiO₂, TiO₂ and Al₂SiO₅ formed in the worn surface. While, at the same test condition, the friction coefficient of the single-phase Si₃N₄ against TC4 was at a range from 0.45 to 0.58. The spalling and cracking morphology formed on the worn surface of single-phase Si3N4, and the wear mechanism was mainly dominated by adhesive and abrasive wear.

Overall, a high-performance green ceramic composite was prepared, and the composite had a good potential for application in engineering tribology fields (such as aerospace bearings).

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0161/

In today’s digital era, talent recruitment can help address the growing shortage of skilled labor in the construction industry and promote sustainable growth. While existing research has explored the association between talent acquisition and local labor productivity or economic progress, the impact on construction growth deserves further study. This study aims to (1) explore the influence of talent recruitment on the growth of the construction industry and (2) analyze whether different regional characteristics shape the differential impact of talent acquisition on construction growth.

This research employs a quantitative approach, focusing on 35 major cities in China. A panel data regression model is utilized to analyze annual data from 2013 to 2018, considering variables like the construction talent recruitment index, value added in construction, gross regional product per capita and others. The study also examines regional heterogeneity and conducts robustness tests to validate the findings.

The results reveal a positive and significant correlation between talent recruitment and construction industry growth. This correlation is more pronounced in economically advanced and infrastructure-rich regions. The study also finds that factors like capital investment, educational attainment and housing prices significantly contribute to industry growth. Talent recruitment not only transforms local labor market dynamics but also drives demand for construction services, promoting industry growth through economies of scale.

This research constructs a new measurement for talent recruitment and provides new insights into the pivotal role of talent recruitment in the sustainable growth of the construction industry. It underscores the need for construction firms to tailor talent acquisition policies to their specific circumstances and regional developmental conditions. The findings offer practical guidance for driving regional growth within the sector, emphasizing the importance of talent recruitment as a key yet previously underappreciated factor in industry development.

On the basis of labor economics theories, this study examines how adjustment in human capital accounts for labor cost stickiness.

This study makes use of employee education level as a measure of the quality of human capital and relies on data from Chinese public firms to conduct the empirical test. This study focuses on two important components of labor cost changes: one corresponding to the adjustment in the number of employees (capacity adjustment) and another corresponding to the adjustment in the mix of employee education levels (quality adjustment).

This study reveals that labor cost changes driven by the adjustment of employee education level are sticky. This stickiness cannot be explained by the standard adjustment cost theory. This further shows that firms that actively adjust their employee quality during downturns experience improved future performance. The findings are robust to alternative measures and specifications.

This study provides new evidence for and insights into the cost behavior literature. Previous studies treat input resources in a homogenous way and focus on the effect of capacity adjustment. This study considers the heterogeneity of resources and examines three dimensions of salary cost adjustment: capacity, structure, and unit cost. In line with the economic theory of sticky costs proposed by Banker et al. (2013a), the study’s evidence sheds light on the additional underlying economic mechanisms driving cost stickiness behavior. Specifically, managers asymmetrically adjust both employee structure and average salaries, in addition to employee number. This study also adds to the existing knowledge of the consequences of managers' actions regarding cost behavior.

Teaching wine tasting online is challenging, even given the curated digital tools of the Wine and Spirit Education Trust, a highly renowned online wine certification system is used. This paper aims to initially explore wine experts’ opinions about online wine education and subsequently examine the feasibility of customizing wine appreciation lexicons for Chinese learners.

A two-study multimethod approach was adopted. Study 1, a two-stage Delphi study, was conducted with 17 wine experts representing a number of countries, using a mix of closed/open-ended questions in an online survey. Data was collected in a market study in Study 2, conducted at agricultural markets in Thailand (pilot test) and China. Dialogues with market sellers were undertaken, evoking mental imagery of wine descriptors to explore the relevance of traditional versus local aromas and flavors in describing wine.

Findings concentrate on three main areas: general advantages/disadvantages of online wine education, reactions toward asynchronous/synchronous methods of wine tasting and, finally, the feasibility of customizing a wine appreciation lexicon for Chinese learners.

The study presents novel insights into the role of online wine education in China.