Negotiation versus consultation in the development of a regulation

Under negotiated regulation, stakeholders are invited to reach an agreement on a regulatory innovation. This approach might be harmful, because potential improvements might be blocked. However, negotiation can also be beneficial—eliciting information about how to improve regulations. Three reasons are identified. First, a participant might hesitate to provide information, unless she can prevent that information being used against her interests. Second, negotiation provides stronger incentives than consultation does, to suggest innovations that primarily benefit parties other than oneself. Third, if uninformed stakeholders can reduce the no-information payoff of informed parties, those parties lose the incentive to strategically withhold information.      

Too similar to combine? On negative weights in forecast combination

This paper provides the first thorough investigation of the negative weights that can emerge when combining forecasts. The usual practice in the literature is to consider only convex combinations and ignore or trim negative weights, i.e., set them to zero. This default strategy has its merits, but it is not optimal. We study the problem from various angles, and the main conclusion is that negative weights emerge when highly correlated forecasts with similar variances are combined. In this situation, the estimated weights have large variances, and trimming reduces the variance of the weights and improves the combined forecast. The threshold of zero is arbitrary and can be improved. We propose an optimal trimming threshold, i.e., an additional tuning parameter to improve forecasting performance. The effects of optimal trimming are demonstrated in simulations. In the empirical example using the European Central Bank Survey of Professional Forecasters, we find that the new strategy performs exceptionally well and can deliver improvements of more than 10% for inflation, up to 20% for GDP growth, and more than 20% for unemployment forecasts relative to the equal-weight benchmark.     

The impact of knowledge hiding on targets’ knowledge sharing with perpetrators

Using a sequential mixed-methods approach, this study explored how knowledge hiding (KH) targets react to perpetrators in the hospitality industry. Study 1 entailed in-depth interviews of 20 employees from 13 hotels. Findings indicate that KH influences knowledge transfer behavior through negative emotions. Moreover, individual personality and motivation, team and interpersonal factors, job characteristics, and KH characteristics can moderate this effect. In Studies 2 (n = 54) and 3 (n = 118), two scenario-based experiments reveal that KH negatively affects targets’ knowledge sharing (KS) with perpetrators directly and indirectly through negative emotions. In Study 4, the results of a survey from 475 employees indicate that when the need for affiliation of employees and task interdependence is high, the negative effect of negative emotions on KS with perpetrators is weaker. This study advances the literature on KH by offering a sound theoretical treatment of emotional concerns and the interaction between knowledge seekers and knowledge hiders.     

The role of explanations and metadiscourse in management responses to anger-reviews versus anxiety-reviews: The mediation of sense-making

Management response (MR) has become a popular intervention for hotels to manage customer reviews on social media platforms. This article introduces two important linguistic features of MR content—metadiscourse and explanation—and investigates their effectiveness in addressing negative reviews. It also examines how hotels customize MRs using different linguistic features according to different emotions in reviews. Based on a field investigation of large-scale TripAdvisor data and an experimental study, we demonstrate that explanations outperform metadiscourse for anxiety-reviews, whereas metadiscourse is more effective than explanations for anger-reviews. Moreover, their relative effectiveness is mediated by consumers’ sense-making process. Using explanations for anxiety-reviews and metadiscourse for anger-reviews facilitates sense-making, whereas using explanations for anger-reviews and metadiscourse for anxiety-reviews impedes it. This research enriches current understanding of MR effects and provides the hospitality industry with important guidelines for formulating effective MRs and social media marketing practices.     

Does customer incivility undermine employees’ service performance?

This study extends the growing body of research on customer incivility by examining its impact on employees’ in-role and extra-role service performance in the hospitality industry. Using a sample of 307 employee–supervisor dyads in nine hotels in Zhuhai City, China, this research examined the impact of customer incivility along with negative affectivity and hostile attribution bias on in-role performance and extra-role performance, particularly proactive customer service performance (PCSP). The results demonstrate that, while customer incivility negatively influenced PCSP, it did not impact in-role performance. Furthermore, the effect of customer incivility on PCSP was mediated by negative affectivity. Additionally, hostile attribution bias significantly moderated the relationship between customer incivility and negative affectivity, as well as the indirect relationship between customer incivility and PCSP through negative affectivity.     

寿险公司高退保现状及其对策探析

近年来我国寿险保单的退保居高不下。高退保严重影响了寿险公司的正常经营和寿险业的健康发展,因此寿险公司应认真冷静分析原因,着力从提升自身经营管理水平出发,积极探索应对高退保的策略。     

How virtual reality moderates daily negative mood spillover among hotel frontline employees: A within-person field experiment

This study explores how virtual reality (VR) interventions mitigate daily negative mood spillover among hotel frontline employees through a daily dairy study. A within-subject field experiment was conducted to collect data from 87 hotel employees over ten consecutive workdays (846 daily responses). The multilevel analysis supports daily negative mood spillover by revealing positive relationships between negative moods before work and midday negative moods, and between midday negative moods and turnover intentions. Exposure to virtual natural scenes alleviates these daily positive relationships. Employees with high (vs. low) levels of trait mindfulness are less likely to be influenced by their negative moods before work when exposed to the VR intervention. This study advances our knowledge by integrating spillover theory, stress recovery theory, and mindfulness through a multilevel framework of employees’ daily emotional fluctuations moderated by VR interventions. The study findings provide hotel professionals with meaningful information regarding workplace stress management.     

Jump detection with wavelets for high-frequency financial time series

This paper introduces a new nonparametric test to identify jump arrival times in high frequency financial time series data. The asymptotic distribution of the test is derived. We demonstrate that the test is robust for different specifications of price processes and the presence of the microstructure noise. A Monte Carlo simulation is conducted which shows that the test has good size and power. Further, we examine the multi-scale jump dynamics in US equity markets. The main findings are as follows. First, the jump dynamics of equities are sensitive to data sampling frequency with significant underestimation of jump intensities at lower frequencies. Second, although arrival densities of positive jumps and negative jumps are symmetric across different time scales, the magnitude of jumps is distributed asymmetrically at high frequencies. Third, only 20% of jumps occur in the trading session from 9:30 AM to 4:00 PM, suggesting that illiquidity during after-hours trading is a strong determinant of jumps.     

A white-boxed ISSM approach to estimate uncertainty distributions of Walmart sales

We present our solution for the M5 Uncertainty competition. Our solution ranked sixth out of 909 submissions across all hierarchical levels and ranked first for prediction at the finest level of granularity (product-store sales, i.e. SKUs). The model combines a multi-stage state-space model and Monte Carlo simulations to generate the forecasting scenarios (trajectories). Observed sales are modelled with negative binomial distributions to represent discrete over-dispersed sales. Seasonal factors are handcrafted and modelled with linear coefficients that are calculated at the store-department level.     

Effects of education externalities on schooling

In some developed countries, such as Japan and Sweden, the number of years of education does not predict wage differences as opposed to in some countries such as the United States and Germany. To explain such seemingly contradictory observations, this study develops a simple model utilizing the ‘keeping up with Joneses’ effect regarding schooling decisions. The main result of this study is that the model can have multiple equilibria, which can explain the difference between the two groups of countries. Moreover, efficiency analysis reveals that changes in the strength of education reference and psychological cost parameters can alter the welfare ranking of multiple equilibria.