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This study aims to explore the key attributes of robot chef restaurants and their influencing factors from the perspective of customers and analyzes how these key attributes affect customer perceived value.

A mixed-methods research design was used in this study. Using 473 online reviews and ratings (Study 1), the research summarized customers’ evaluations on three types of attributes (environment, service and food) and identified the key attributes along with their influencing factors. Subsequently, through field questionnaires (Study 2) involving 269 actual customers, structural equation modeling was used to analyze how the identified key attributes and their influencing factors impact customer perceived value.

This study reveals that customers in robot chef restaurants prioritize food attributes, particularly valuing food authenticity alongside food quality. In contrast to traditional restaurants, customers’ evaluations of food attributes in robot chef restaurants are significantly influenced by the competence of robot chefs. Notably, customers’ negative attitudes toward robots diminish the positive effects on both food quality and food authenticity.

To enhance customer perceived value, robot chef restaurants should concentrate on food attributes. They can achieve this by fostering a high-quality, authentic food experience through the elevation of robot chefs’ competence and by providing customer education.

This study expands research on the customer experience in robotic restaurants by proposing an integrated model determining factors that affect the perceived customer value.

Product discounts have been widely applied in digital commerce as a method to attract and retain customers to purchase in China. Given that digital channels differ in their attributes, customers may behave differently when they respond to the same discount across channels. However, little attention has been paid to explore the heterogeneity of customer responses to discounts across channels. This study aims to fill in the gap by exploring how customers’ purchase responses to price discounts differ across digital channels.

This study applies a Poisson regression to an unbalanced data set of purchasing history from Chinese footwear brands with 3,510 customers in a two-year time window across the three digital channels (i.e. personal computer [PC], app and mobile website), with a correction for endogeneity by using the Gaussian copula method.

This paper finds that price discounts have the strongest positive effect on consumers’ purchase volumes on the PC channel, followed by the app channel, while discounts show the weakest impact in the mobile website channel. By so, this paper demonstrates that customers respond differently to online and mobile channels, and they also respond differently within mobile channels when they purchase products with price discounts.

This study is original in analyzing the difference in customers’ discount responses across digital channels, offering valuable contributions to existing research on multichannel marketing as well as mobile marketing and providing helpful insights for multichannel merchants to design digital discount strategies.

We attempt to analyze the impact of retailer’s rebate strategy on consumer reviews and retailer’s profits.

Retailers' rebates have a chance to affect sales and their profits by encouraging customers to submit product reviews. To investigate the impact of retailer’s rebate strategy on consumer reviews and retailer’s profits, we describe the consumer’s utility function and the number of consumer-written reviews by introducing the concepts of product demand mismatch and consumer review effort, then develop a two-stage model of the retailer’s rebate strategy and examine how the retailer’s rebate affects online reviews, the consumer’s perceived utility and the retailer’s profit. Finally, a number case verifies the validity and rationality of the proposed model.

The results show that the rebate strategy can effectively reduce consumer dissatisfaction caused by excessive product demand mismatch, improve the consumer utility, prompt more positive comments, and thus increase product sales.

In this paper, we focus on the impact of retailers' rebate strategy on consumer purchase decisions. The research can accurately reflect the influence of online reviews on consumers and retailers, assisting merchants in making the best selections. The analysis indicates that the retailer’s rebate strategy can have a direct impact on consumers' evaluation choices and product sales.

Customer misbehavior has a negative impact on frontline employees. However, the underlying mechanisms from customer misbehavior to employees’ negative outcomes need to be further unfolded and examined. This study aims to propose that employees’ affective rumination and problem-solving pondering could be the explanatory processes of customer misbehavior influencing employee attitudes in which coworker support could be a moderator.

A mixed-method approach was designed to test this study’s predictions. Study 1 conducted a scenario-based experiment among 215 full-time hospitality employees, and Study 2 used a two-wave, longitudinal survey of 305 participants.

The results demonstrate the impact of customer misbehavior on work–family conflict and withdrawal behaviors. The mediating role of affective rumination is supported and coworker support moderates the processes.

Customer misbehavior leads to negative outcomes among frontline employees both at work and family domains. Hotel managers should help frontline employees to cope with customer misbehavior by avoiding negative affective spillover and providing support properly.

The studies have unfolded the processes of affective rumination and problem-solving pondering through which customer misbehavior influences work–family conflict and withdrawal behaviors among frontline employees. The surprising findings that coworker support magnified the negative effects have also been discussed.

This research aims to investigate the relationship between environmental, social and governance (ESG) factors and the performance of real estate companies before and after the COVID-19 pandemic. By conducting a comprehensive case study analysis, we will explore how real estate companies' adoption of ESG practices has influenced their financial performance, market value and resilience during these uncertain times. The findings of this study will contribute to the existing body of knowledge on the relationship between ESG factors and company performance, specifically within the real estate sector. Moreover, the research outcomes will offer practical implications for real estate companies, investors, policymakers and other stakeholders, aiding them in making informed decisions regarding ESG integration and its potential benefits in uncertain times. Overall, this research aims to shed light on whether ESG factors truly enhance the performance of real estate companies, considering the unique challenges posed by the COVID-19 pandemic and sanctions. By examining the case study before and during uncertain times including COVID-19 pandemic and sanctions, we provide valuable insights into the role of ESG practices in shaping the future of the real estate industry.

The study focuses on the selection process and main model used to investigate the relationship between ESG factors and firm performance. The data is divided into four groups based on ESG quartiles to analyze differences between firms with high and low ESG scores. The Difference-in-Differences (DID) model is employed to assess anomalous returns and stock volatility across different ESG quartiles before and after the COVID-19 pandemic. Panel data models are utilized to study the association between ESG and firm performance, with random effects and fixed effects estimators considered. The study builds a model to analyze the impact of ESG on financial performance indicators, incorporating various factors and control variables. Additionally, the Average Treatment Effect on the Treated (ATET) analysis and DID model are explored to evaluate the causal impact of ESG on firm performance. The study emphasizes the importance of testing for parallel trends to ensure the validity of the ATET analysis and it presents a generalized DID model to examine the relationship between ESG scores and company performance outcomes.

Our study's main conclusions show that, in a world with some degree of stability, ESG not only does not improve but, in some situations, also hurts firms' success. On the other hand, at times of notable worldwide unrest, like the COVID-19 pandemic, firms with better ESG ratings demonstrate exceptional stock market success and a noteworthy ability to rebound from a crisis. Moreover, we note that investors truly prioritize sustainable investments as a risk mitigation strategy in addition to their environmental and social duties only when companies face sufficiently significant risks. The results will highlight the significance of sustainable and responsible investment for investors and provide management with more knowledge to create effective ESG strategies for their companies.

By incorporating sustainability and responsibility into their operations, businesses may reduce risk, perform better over the long run and benefit society and the environment. As investors come to understand the importance of ESG issues in their decision-making, the global landscape is experiencing a transformation. Therefore, in the era when stakeholders, such as consumers, workers and shareholders, want more responsibility and transparency when it comes to ESG practises, it is crucial that companies should devote their priority to their ESG performance in order to reduce the danger of slipping behind, especially in light of the increasing importance of sustainability issues and changing laws. However, in the case of small-sized firms, investment policies to improve companies’ governance need to be controlled in moderation during the period of stability because it will create financial pressure and leave them without enough resources to cope with negative impacts during uncertain period. In sum, sustainable and ethical investment is not only a fad; rather, it is a vital and unavoidable route for companies looking to prosper in an unpredictable and complicated global environment.

This research study significantly enhances the existing academic discourse surrounding the relationship between ESG factors and firm performance, particularly, in periods of uncertainty. The findings underscore the critical importance for real estate companies to place a greater emphasis on ESG practices in order to not only benefit themselves but also to improve their overall performance and sustainability in the long term. By shedding light on the positive outcomes associated with prioritizing ESG considerations, this study offers valuable insights for real estate firms seeking to enhance their competitive advantage and stakeholder value in today's dynamic business landscape.

The purpose of this study is to investigate the behavior of a silicon solar cell when subjected to a magnetic field. Specifically, the study aims to understand how the presence of the magnetic field influences the distribution of excess minority carriers within the base region of the solar cell. By solving the one-dimensional continuity equation under these conditions, the study seeks to elucidate the transient dynamics of carrier generation, recombination and transport processes. This research contributes to the broader understanding of how external magnetic fields can impact the performance and efficiency of silicon solar cells, potentially informing future optimizations or applications in photovoltaic technology.

The solar cell is assumed to be uniformly illuminated, which simplifies the analysis of carrier generation to a function of depth (x). The emitter and space charge region contributions are considered while neglecting the diffusion region. The injection level remains constant throughout the analysis, focusing specifically on the base thickness region, H = 200 µm.

The findings of this study reveal significant insights into the behavior of a silicon solar cell under the influence of a magnetic field. Key findings include Impact on carrier distribution: the magnetic field affects the distribution of excess minority carriers within the base region of the solar cell. This distribution is crucial for understanding the efficiency of carrier collection and overall cell performance. Transient dynamics: the transient behavior of carrier generation, recombination and transport processes in the base region is influenced by the magnetic field. This understanding helps in predicting the response time and effectiveness of the solar cell under varying magnetic field strengths. Optimization potential: insights gained from this study suggest potential strategies for optimizing the design and operation of silicon solar cells to enhance their performance in environments where magnetic fields are present. Theoretical framework: the study provides a theoretical framework based on the one-dimensional continuity equation, offering a systematic approach to analyzing and predicting the behavior of solar cells under magnetic field conditions. These findings contribute to advancing the understanding of how external factors such as magnetic fields can impact the operation and efficiency of silicon solar cells, thereby guiding future research and development efforts in photovoltaic technology.

The originality and value of this study lie in its contribution to advancing the understanding of how magnetic fields influence silicon solar cell performance, providing both theoretical insights and potential practical applications in diverse technological contexts.

This study is of great significance in revealing the interactive and coordinated relationship between tourism development and the ecological environment, improving the level of environmental governance in the process of tourism economic development and realising the dual-carbon goal and sustainable development of the tourism industry.

This paper performs slack-based measure (SBM)-data envelopment analysis (DEA) analysis, benchmark regression and threshold effect measurement on a sample of 277 cities in China from 2011 to 2019, to estimate the impact of the digital economy on tourism eco-efficiency and to identify the moderating role of environmental regulation.

China’s tourism eco-efficiency shows a spatio-temporal characteristic of steady growth amid fluctuations. The digital economy has a positive facilitating effect on tourism eco-efficiency, which is non-linear with a single threshold effect (0.631), and when the level of the digital economy exceeds the threshold value, its facilitating effect increases from 0.696 to 0.927. Environmental regulation does not play the role of “the icing on the cake” during the digital economy’s impact on tourism eco-efficiency.

This study for the first time includes the digital economy, eco-efficiency and environmental regulation in the research perspective, and analysed the mechanism of action between the three, expanding the depth of research on the digital economy and environmental regulation in the field of tourism. Meanwhile, based on the development needs of policy specialisation and industrial refinement, this study has strong practical significance when conducted at the city level.

This study seeks to explore the intricate relationship among supply chain transparency, digitalization and idiosyncratic risk, with a specific focus on newly public firms. The objective is to determine whether supply chain transparency effectively mitigates idiosyncratic risk within this context and to understand the potential impact of digitalization on this dynamic interplay.

The study utilizes data from Initial Public Offerings (IPOs) on China’s Growth Enterprise Board (ChiNext) over the last five years, sourced from the CSMAR database and firms’ annual reports. The research covers the period from 2009 to 2021, observing each firm for five years post-IPO. The final sample comprises 2,645 observations from 529 firms. The analysis employs the Hausman test, considering the panel-data structure of the sample and favoring fixed effects over random effects. Additionally, it applies the high-dimensional fixed effects (HDFE) estimator to address unobserved heterogeneity.

The analysis initially uncovered an inverted U-shaped relationship between supply chain transparency and idiosyncratic risk, indicating a delicate equilibrium where detrimental effects diminish and beneficial effects accelerate with increased transparency. Moreover, this inverted U-shaped relationship was notably more pronounced in newly public firms with a heightened level of firm digitalization. This observation implies that firm digitalization amplifies the impact of transparency on a firm’s idiosyncratic risk.

This study distinguishes itself by providing distinctive insights into supply chain transparency and idiosyncratic risk. Initially, we introduce and substantiate an inverted U-shaped correlation between supply chain transparency and idiosyncratic risk, challenging the conventional linear perspective. Secondly, we pioneer the connection between supply chain transparency and idiosyncratic risk, especially for newly public firms, thereby enhancing comprehension of financial implications. Lastly, we pinpoint crucial digital conditions that influence the relationship between supply chain transparency and idiosyncratic risk management, offering a nuanced perspective on the role of technology in risk management.

We aim to examine two issues. First, we intend to identify the best performing expected return proxies. Second, we investigate whether the expected return proxies for individual stocks can track the corresponding realized returns during extremely good or extremely bad times of the economic environment related to business conditions, stock market valuation and broad market performance.

We construct four sets of expected return proxies, including: (1) characteristic-based proxies; (2) standard risk-factor-based proxies; (3) risk-factor-based proxies that allow betas to vary with firm characteristics and (4) macroeconomic-variable-based proxies. First, we estimate expected returns for individual stocks using newly developed methods and evaluate the performance of these expected return proxies based on the minimum variance criterion of Lee et al. (2020). Second, we regress expected return proxies and realized returns on indicator variables that capture the extreme phases of the economic environment. Then we compare the estimated coefficients from these two sets of regressions and see if they are similar in magnitude via formal hypothesis testing.

We find that characteristic-based proxies and risk-factor-based proxies that allow betas to vary with firm characteristics are the two best performing proxies. Therefore, it is important to allow betas to vary with firm characteristics in constructing expected return proxies. We also find that model-based expected return proxies do a reasonably good job capturing actual returns during extremely bad and extremely good phases of business cycles measured by leading economic indicators, consumer confidence and business confidence. However, there is a large gap between the adjustment of model-based expected returns and realized returns during extreme episodes of stock market valuation or broad market performance.

We examine four types of expected return proxies and use the newly developed methodology as in Lee et al. (2020) to see which one is the best. In addition, we document whether model-based expected returns from individual stocks adjust partially or fully to keep pace with actual returns in response to changing economic conditions. No prior studies have examined these two issues.

Educational accountability and student achievement polarization, which result in high dropout rates, pose significant challenges and pressures on teachers' pedagogical leadership. Whether pedagogical leadership, which originates in the Western educational environment, can significantly improve student achievement in Chinese high schools remains unclear. This concept has not yet been fully explored in the Chinese educational environment, and its direct impact on student achievement and the mediating role of English teaching methods remain to be investigated. However, existing research has concentrated on the effectiveness of principals' pedagogical leadership, with variations in teachers' pedagogical leadership practices. Many reform measures have been implemented in China to improve student achievement, but past educational practices have analyzed the impact on student achievement from a single instructional leadership, school capital or teaching method perspective. Furthermore, there is a lack of multidimensional and systematic assessments of the direct effects of teacher pedagogical leadership on student achievement and the mediating effects of English teaching methods.

To address this gap, this study analyzed the impact of teachers' pedagogical leadership on student achievement and the mediating effect of English teaching methods with the support of the theory of action for teacher leadership, specifically using pedagogical leadership and English teaching methods models.This study conducted a questionnaire survey of 968 participants in Taian City, China, and quantitatively analyzed the data using SmartPLS structural equation modeling (SEM).

This study revealed that pedagogical leadership has a positive direct effect on student achievement. Meanwhile, among the four mediating factors, the Direct Method, Audio-Lingual Method and Communicative Language Teaching had significant mediating effects.

This study shows that the effective use of academic and professional capital allocation in pedagogical leadership, combined with effective measures of using multiple effective English teaching methods, helps achieve high-quality student achievement.