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The purpose of this paper is to explore the relationship between transformational leadership and employees’ work engagement based on fit theory. The paper reports an investigation into the way in which employees’ perceptions of transformational leadership and person-job fit affect their work engagement.

To test the authors’ hypotheses, the authors performed structure equation modeling with maximum likelihood estimation on Mplus with bootstrapping proposed by Hayes (2009) with data from 691 full-time employees in China.

The results indicate that transformational leadership has as significant influence on employees’ work engagement as person-job fit in China. Moreover, employees’ perception of person-job fit is found to partially mediate the relationship between transformational leadership and employees’ work engagement.

There is a possible bias arising from the use of cross-sectional data. However, certain methods were implemented to minimize it, including survey design and data analysis.

The paper proposes a number of practical implications for policy makers, HR managers and transformational leaders relating to issues associated with improving levels of employee engagement.

The study contributes to developing leadership and engagement theory by examining a previously unexplored mediator – person-job fit – in a neglected cultural setting. This study promises to open new research avenues in this area.

This paper aims to analyze if and to what extent mechanical artificial intelligence (AI)-embedded in hotel service robots-influences customers’ evaluation of AI-enabled hotel service interactions. This study deploys online reviews (ORs) analytics to understand if the presence of mechanical AI-related text in ORs influences customers’ OR valence across 19 leading international hotels that have integrated mechanical AI – in the guise of service robots – into their operations.

First, the authors identified the 19 leading hotels across three continents that have pioneered the adoption of service robots. Second, by deploying big data techniques, the authors gathered the entire population of ORs hosted on TripAdvisor (almost 50,000 ORs) and generated OR analytics. Subsequently, the authors used ordered logistic regressions analyses to understand if and to what extent AI-enabled hospitality service interactions are evaluated by service customers.

The presence of mechanical AI-related text (text related to service robots) in ORs influences positively electronic word-of-mouth (e-WOM) valence. Hotel guests writing ORs explicitly mentioning their interactions with the service robots are more prone to associate high online ratings to their ORs. The presence of the robot’s proper name (e.g., Alina, Wally) in the OR moderates positively the positive effect of mechanical AI-related text on ORs ratings.

Hospitality practitioners should evaluate the possibility to introduce service robots into their operations and develop tailored strategies to name their robots (such as using human-like and short names). Moreover, hotel managers should communicate more explicitly their initiatives and investments in AI, monitor AI-related e-WOM and invest in educating their non-tech-savvy customers to understand and appreciate AI technology. Platform developers might create a robotic tag to be attached to ORs mentioning service robots to signal the presence of this specific element and might design and develop an additional service attribute that might be tentatively named “service robots.”

The current study represents the first attempt to understand if and to what extent mechanical AI in the guise of hotel service robots influences customers’ evaluation of AI-enabled hospitality service interactions.

Couriers are in an unequal relationship with on-demand logistic platforms with regards to order assignment and delivery-related information acquisition, which leads to high courier turnover rates. Based on social cognitive theory and justice theory, this research investigates the impact of order assignment and delivery-related information disclosure strategy on couriers' perceived justice and continuous participation intention and presents managerial suggestions to on-demand logistic platforms to lower the courier turnover rate.

Taking Chinese couriers as experimental subjects, this study conducts experiments by constructing an order receiving scene of order assignment strategy (performance-priority vs distance-priority) and delivery-related information disclosure strategy (detailed-information vs brief-information) and analyzes the results of 452 valid respondents.

The results indicate that the interaction between order assignment and delivery-related information disclosure strategy in on-demand logistics significantly affects couriers’ continuous participation intention, specifically under performance-priority order assignment and detailed-information (vs brief-information) disclosure strategy. Informational justice and distribution justice play mediating roles, and work experience and proactive personality moderate the relationship interactions.

The research helps us to understand the order-receiving justice demand and delivery-related information demand of couriers in on-demand logistics platforms and sheds light on cutting down turnover rates through different strategies designs and justice environment construction.

This research integrates social cognitive theory into on-demand logistics and combines with justice theory to fill platform strategies, couriers’ justice perception and characteristics, as well as behavior into “triadic reciprocal causation.” Meanwhile, it investigates different impacts and interactive relationships of order assignment and delivery-related information disclosure strategy, expands strategies from the impact of operational efficiency to the impact of couriers’ participation and extends the literature of justice perception and individual characteristics in on-demand logistics.

Resilience is a fundamental component of healthcare supply chains, as the quality and endurance of human life are dependent on them. However, there are numerous resilience-building measures, and there is a need for prioritization of those strategies. This research study aims to prioritize resilience strategies for healthcare supply chains while considering the risks that most severe, probable to occur and have the lengthiest periods of recovery.

This research study has used multi-criteria decision-making (MCDM) techniques for analysis. Initially, the criteria for prioritization of risks, i.e. severity, probability of occurrence and recovery time were assigned with importance weights through the fuzzy analytical hierarchy process (AHP). Then, these weights were used in the fuzzy technique for order preference by similarity to ideal solution (TOPIS) analysis for prioritization of risks. Subsequently, the identified risks were used for highlighting the appropriate resilience strategies through the fuzzy quality function deployment (QFD) technique.

Results indicate that Industry 4.0, multiple sourcing, risk awareness, agility and global diversification of suppliers, markets and operations are the most significant resilience strategies.

This study's limitation is that it is conducted in a general perspective, rather than reducing the context to a developing or developed country. Different areas have variable market factors, due to which potential risks occur in a different form. Moreover, resilience strategies work differently in different environments. Therefore, for future endeavors, the studies should be carried out in a limited context.

This research study proposes a novel MCDM-based approach for ranking resilience strategies, in light of the most probable, severe and long-lasting risks. In addition, this approach has been employed for the enhancement of resilience in healthcare supply chains.

The results indicate that land prices exert pressure on retail performance (RP) and that the enhancement of digital means has a positive effect on RP. Additionally, digital instruments (DI) play a significant moderating role in the relationship between land prices and RP.

This paper empirically examines the impact of land prices on RP using panel data from 239 Chinese cities between 2011 and 2022.

The use of lagged land prices as instrumental variables effectively alleviates endogeneity issues. Both two-stage least squares (2SLS) and generalized method of moments (GMM) regression results suggest that higher land prices are associated with improved RP. Further analysis reveals that the increase in land prices leads to scale effects, structural effects and technological effects, contributing to the enhancement of RP. The impact of land prices on RP becomes more pronounced in larger cities and economically developed regions experience the pressure from land prices earlier.

The findings of this study have practical implications for discussions on retail industry development, site selection for retail businesses and the establishment of sustainable mechanisms for expanding domestic demand.

The purpose of the study has been to fill the gap detected in the literature and to analyze whether the application of management of R&D in accordance with UNE 166002:2021 allows companies to obtain higher product innovation and better performance, specifically incremental and radical product innovations.

The population used in this study included Spanish manufacturing organizations that were active, had more than 50 employees according to the SABI. The information was collected through a structured questionnaire previously tested using a company specializing in the sector under the supervision of the authors. A total of 1,154 companies were randomly contacted in order to reach an acceptable number of 225 valid questionnaires. The data analysis has been carried out with structural equation methodology.

The results obtained with a sample of 225 companies show that the application of this standard for innovation management promotes the development of new products with incremental and radical changes, and improves business performance. It has also been found that incremental and radical product innovations mediate the relationship between this standard and performance.

Firstly, the survey is only addressed to the company's operations manager. Secondly, the sample used is cross-sectional, whereas innovation management implies a broad implementation process.

Managers must know that radical and incremental product innovation can improve the company's operational performance. And the most direct implication of this work is that, those companies that are committed to the development of innovations should seriously consider the application of the principles incorporated in Standard 166,002, as an instrument that improves the results of innovation in the organization. Since this SIMS promotes both types of innovations, it improves results directly and indirectly through these product innovations.

The existing literature indicates that no empirical study has focused on the benefits of this SIMSs for innovation and BP. This paper fills this gap detected in the literature and analyzes the results of the implementation of this standard on incremental and radical product innovations and business performance.