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Mean absolute percentage error (MAPE) is the primary forecast evaluation metric in hospitality and tourism research; however its main shortcoming is that it is asymmetric. The asymmetry occurs due to over or under forecasts that introduce bias into forecast evaluation. This study aims to explore the nature of asymmetry and designs a new measure, one that reduces the asymmetric properties while maintaining MAPE’s scale-free and intuitive interpretation characteristics.

The study proposes and tests a new forecasting accuracy measure for hospitality revenue management (RM). A computer simulation is used to assess and demonstrate the problem of asymmetry when forecasting with MAPE, and the new measures’ (MSapeMER, that is, Mean of Selectively applied Absolute Percentage Error or Magnitude of Error Relative to the estimate) ability to reduce it. The MSapeMER’s effectiveness is empirically validated by using a large set of hotel forecasts.

The study demonstrates the ability of the MSapeMER to reduce the asymmetry bias generated by MAPE. Furthermore, this study demonstrates that MSapeMER is more effective than previous attempts to correct for asymmetry bias. The results show via simulation and empirical investigation that the error metric is more stable and less swayed by the presence of over and under forecasts.

It is recommended that hospitality RM researchers and professionals adopt MSapeMER when using MAPE to evaluate forecasting performance. The MSapeMER removes the potential bias that MAPE invites due to its calculation and presence of over and under forecasts. Therefore, forecasting evaluations may be less affected by the presence of over and under forecasts and their ability to bias forecasting results.

Hospitality RM should adopt this measure when MAPE is used, to reduce biased decisions driven by the “asymmetry of MAPE.”

The MAPE error metric exhibits an asymmetry problem, and this paper proposes a more effective solution to reduce biased results with two major methodological contributions. It is first to systematically study the characteristics of MAPE’s asymmetry, while proposing and testing a measure that considerably reduces the amount of asymmetry. This is a critical contribution because MAPE is the primary forecasting metric in hospitality and tourism studies. The second methodological contribution is a procedure developed to “quantify” the asymmetry. The approach is demonstrated and allows future research to compare asymmetric characteristics among various accuracy measures.

This study aims to clarify the impact of agriculture–tourism integration (ATI) on in situ urbanization (ISURB) of rural residents, to highlight the role of industrial integration in the process of China's ISURB and to provide industrial integration suggestions for promoting urbanization quality in Chinese counties.

By sorting out the panel data of China's 1868 counties, the evaluation index system of ISURB was constructed. Difference in difference (DID) and spatial Durbin-difference in difference (SDM-DID) model is used for estimate the relationship between ATI and ISURB.

First, ATI can improve ISURB by 11.4% higher than other regions. Second, theoretical analysis model of ATI on ISURB is constructed from four aspects of “drive–push–pull–block.” The results show that ATI can promote ISURB by increasing upgrading of rural industries, rural employment demand and income capacity, whereas ATI may inhibit ISURB by reducing farmland. Third, considering changes in institutional, hard and soft factors, rural collective economy, information infrastructure and digital finance all promote positive impact of ATI on ISURB. Fourth, ATI will produce spillover effects on ISURB in neighboring regions, which is more pronounced in the central and western regions.

This study lacks quantification of ATI, so future studies are encouraged to further quantify ATI at the county level.

This study has policy significance for constructing ATI demonstration counties and promoting ISURB in China's counties.

It is of great practical value to promote China's ISURB. By stimulating ATI, it can improve income and employment capacity of rural residents and stimulate ISURB of China.

This study enriches the theoretical and practical research on industrial integration behaviors during the process of ISURB.

1. Use county data to measure in situ urbanization (ISURB)

2. Agriculture–tourism integration (ATI) can increase ISURB

3. Constructs a “drive-push-pull-block” model to explain the influence mechanism

4. Use spatial Durbin-difference in difference (SDM-DID) models

5. Consider collective economy, rural information infrastructure and digital finance

Use county data to measure in situ urbanization (ISURB)

Agriculture–tourism integration (ATI) can increase ISURB

Constructs a “drive-push-pull-block” model to explain the influence mechanism

Use spatial Durbin-difference in difference (SDM-DID) models

Consider collective economy, rural information infrastructure and digital finance

People often look to the opinions and actions of others to guide their food choices, especially when they are uncertain or unfamiliar with a particular food. This influence can be positive or negative depending on the context and can have an impact on food consumption and health outcomes.

The paper analysed data from 500 young adult consumers in China and employed a multi-study design to examine various aspects of social proof and herd behaviour in food choices. Experiment 1 examined the influence of testimonials from an influential person on buying decisions and eating behaviour. Experiment 2 explored whether herd behaviour drives food options. Experiment 3 assessed the influence of social proof on food choices. Chi-square tests of independence were conducted to examine the relationship between social proof and food choice, as well as herd behaviour and food decision-making. Several logit regression analyses were performed to identify the factors that drive consumers' susceptibility to social proof and herding.

The results indicated that the source of feedback, whether from an influential person or a family member, did not have a statistically significant effect on the likelihood of following the food guide recommendations. The preference for a healthier food option was stronger than following the herd. In contrast, social proof in the form of reviews and ratings influenced participants' choices. The paper highlights the usefulness for stakeholders and policymakers seeking to promote healthier eating habits.

The originality lies in its comprehensive approach, combining multiple experiments and analytical methods.

This paper breaks through the limitations of the research on bullwhip effect in the traditional supply chain, extends the research perspective to digital supply chain and discusses the weakening effect of digital supply chain on bullwhip effect by comparing the overall performance of the two.

This paper starts with the weakening mechanism of supply chain digitization on bullwhip effect, builds bullwhip effect models of traditional supply chain and digital supply chain, respectively, simulates the influence of supply chain digitization transformation on bullwhip effect by using Matlab software and analyzes the causes of bullwhip effect in supply chain led by T company and the digitization process.

Firstly, digitization can reduce bullwhip effect in multi-level supply chain by reducing information feedback deviation. Second, digital transformation is conducive to improving the overall performance of the supply chain. Third, government incentives can promote the digital transformation of supply chain and inhibit bullwhip effect.

Although the study considers the heterogeneous subject -- the government's incentive effect on digital transformation and information sharing – it does not include the influence of the end node in the supply chain, that is the consumer. In addition, this paper only analyzes and discusses the bullwhip effect on the amplification of demand, without considering the situation that the market contraction will lead to the reduction of demand.

This paper considers the distortion degree and delay degree of information feedback, carries out quantitative analysis of bullwhip effect, builds the bullwhip effect model of traditional supply chain and digital supply chain, uses Matlab software to analyze the difference of the influence of supply chain digital transformation on bullwhip effect suppression and puts forward the corresponding control strategy.

The research shows that digital transformation can reduce the bullwhip effect in multi-layer supply chain by reducing the information feedback deviation, which is conducive to improving the overall supply chain performance, and government support can accelerate the digital transformation of supply chain to a certain extent.

First, break through the limitations of traditional supply chain research, expand the research perspective to digital supply chain and discuss the weakening effect of digital supply chain on bullwhip effect by comparing the overall performance of the two. Second, quantify the bullwhip effect through information feedback bias and provide an analysis method for the weakening of the bullwhip effect. Third, the driving role of the government in the digital transformation of the supply chain is considered in the study, so that the model is more close to the actual situation of enterprise operation.

The paper aims to solve the problem of personnel intrusion identification within the limits of high-speed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy of object recognition in dark and harsh weather conditions.

This paper adopts the fusion strategy of radar and camera linkage to achieve focus amplification of long-distance targets and solves the problem of low illumination by laser light filling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm for multi-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposes a linkage and tracking fusion strategy to output the correct alarm results.

Simulated intrusion tests show that the proposed method can effectively detect human intrusion within 0–200 m during the day and night in sunny weather and can achieve more than 80% recognition accuracy for extreme severe weather conditions.

(1) The authors propose a personnel intrusion monitoring scheme based on the fusion of millimeter wave radar and camera, achieving all-weather intrusion monitoring; (2) The authors propose a new multi-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring under adverse weather conditions; (3) The authors have conducted a large number of innovative simulation experiments to verify the effectiveness of the method proposed in this article.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

Drawing upon the theory of communication visibility, this research intends to investigate the direct effect of enterprise social media (ESM) usage on team members’ knowledge creation capability (KCC) and the mediating effects of psychological safety and team identification. In addition, it aims to untangle how the efficacy of ESM usage varies between pre- and post-COVID-19 periods.

Using two-wave survey data from 240 members nested within 60 teams, this study utilizes a multilevel approach to test the proposed hypotheses.

We discover that ESM usage enhances team members’ KCC. More importantly, the results show that psychological safety and team identification mediate the ESM–KCC linkage. Interestingly, we further find that the impacts of ESM usage on team members’ KCC, psychological safety, and team identification are stronger in the pre-COVID-19 period than those in the post-COVID-19 period.

This research sheds light on the ESM literature by unraveling the mechanisms of psychological safety and team identification underlying the linkage between ESM usage and team members’ KCC. Moreover, it advances our understanding of the differential efficacy of ESM usage in pre- and post-COVID-19 periods.

Showrooming presents a complex and evolving challenge to retail managers, as it signifies the emergence of new forms of exchange rules. The purpose of this research is to investigate how factors responsible for information search and evaluation affect showrooming and also consider the consumer mindset as a moderator.

This research undertakes three experimental designs to investigate how the push (i.e. assortment size), pull (i.e. price discount), and mooring (i.e. sunk cost) factors influence consumers' showrooming intention. Specifically, consumers' maximizing tendency plays the role of moderator.

The results reveal that push, pull, and mooring factors are significantly related to consumers' showrooming intention. Furthermore, the findings show that maximizers have higher showrooming intention than satisficers in the context of the push, pull, and mooring factors.

By integrating the push-pull-mooring framework and the maximizing mindset theory, this research proposes a novel research model and the empirical testing results support six hypotheses. The findings add to the body of knowledge in showrooming behavior by taking consumer mindset into account. The results also provide implications for practitioners to develop their retail strategies.

This research explores the key factors that contribute to the success of Black students in a predominantly White institution (PWI). Two measures of success are examined: cumulative grade point average (GPA) and graduation status.

Using student-level data from a southeastern university, this research estimates education production functions using ordinary least squares regression.

While the negative effect of being Black is significant for both cumulative GPA and graduation status, the effect becomes overshadowed when peer effects are added. The authors also found the critical effect of institutional support on student success.

The student-level data are restricted to a single institution over a relatively short period of time, which limits the authors' ability to analyze institution-level factors.

This research provides a broad view of many significant factors for student success with particular highlights on the importance of encouraging Black students to utilize institutional support.

This study is an extension of the education production function model in the field of student success. The study identified peer effects and institutional support as more powerful determinants of student success than race.

Different information sharing mechanisms and online platform information sharing to different charging models are compared and analyzed.

This paper uses the Stackelberg game model to study the demand information sharing and pricing decisions.

The results show that: (1) the retailer's pricing strategy is the highest when both of them obtain information, while the manufacturer's pricing strategy is affected by the related attributes of different products, such as the sensitivity of consumers to product prices; (2) in the online platform sales model, the demand information data sharing owned by the online platform can bring more expected profits to the whole supply chain and the members of the supply chain, and the higher the accuracy of the information, the higher the expected profit; (3) when the cost of obtaining demand information is zero, that is, the online platform shares the information data about market demand free of charge, the retailer and manufacturer tend to obtain information; (4) for the online platform, charging a certain fee can achieve higher expected profits than free sharing.

Based on the single platform online sales model, this paper uses the Stackelberg game model to study the demand information sharing and pricing decision of a manufacturer and a retailer selling products through the same online platform.