Tourists’ hotel event experience and satisfaction: an integrative approach

ABSTRACT

Tourists’ hotel event experiences have received little attention in tourism research. By proposing an integrated model of expectation–confirmation theory (ECT) and the experience economy concept, this research explores the relationship between tourists’ event experience and their satisfaction regarding the hotel event setting. The hypothesized model was empirically validated using a sample of 663 tourists who experienced a holiday event at a resort hotel. Results confirmed that the integration of the experience economy and ECT provided a better understanding of tourists’ post-satisfaction in a pleasure-driven setting. This affective–cognitive approach advances the knowledge of tourists’ experiences and satisfaction at hotel events.     

Determinants of materiality disclosure quality in integrated reporting: Empirical evidence from an international setting

This study examines determinants of materiality disclosure quality (MDQ) in integrated reporting (IR) in an international setting. To this purpose, we constructed a novel, hand‐collected MDQ score in line with the <IR> guiding principles introduced by the International Integrated Reporting Council. On the basis of a cross‐national sample consisting of 359 firm‐year observations between 2013 and 2016, we find that MDQ is positively associated with learning effects, gender diversity, and the assurance of nonfinancial information in the integrated report. On the other hand, we find that IR readability, listing in the Dow Jones Sustainability Index, and earnings management do not affect MDQ. Our results are robust to different statistical models. We expand on earlier empirical findings on IR disclosure quality and provide valuable insights for research, practice, and standard setting.     

我国林业扶贫工作的主要问题及优化措施研究

林业扶贫是当前我国扶贫工作的重要内容。通过介绍开展林业扶贫工作的政策背景、理论背景以及经济背景,分析林业扶贫工作开展过程中存在的基础设施落后、针对性差等问题,提出了因地制宜,互联网+林业扶贫,鼓励社会资本进入扶贫工作、志智双扶等应对措施。     

Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis

This paper investigates the portfolio optimization under investor’s sentiment states of Hidden Markov model and over a different time horizon during the period 2004–2016. To compare the efficient portfolios of the Islamic and the conventional stock indexes, we have employed two approaches: the Bayesian and Markowitz mean-variance. Our findings reveal that the Bayesian efficient frontier of Islamic and conventional stock portfolios is affected by the investor’s sentiment state and the time horizon. Our findings also indicate that the investor’s sentiment regimes change the Islamic and the conventional optimal diversified portfolios.Moreover, the results show that the potential diversification benefits seem to be more important when using the Bayesian approach than when applying the Markowitz approach. This finding is valid for the bearish, depressed, bullish and calm states in Islamic stock markets. However, the diversification of potential portfolios is significant only for the bullish and the bubble states in the conventional financial markets.The findings of the study provided additional evidence for investors to exploit googling investor sentiment states to evaluate the portfolio performance and make an optimal portfolio allocation.     

Forecast of realized covariance matrix based on asymptotic distribution of the LU decomposition with an application for balancing minimum variance portfolio

We derive the asymptotic distribution for the LU decomposition, that is, the Cholesky decomposition, of realized covariance matrix. Distributional properties are combined with an existing generalized heterogeneous autoregressive (GHAR) method for forecasting realized covariance matrix, which will be referred to as a generalized HARQ (GHARQ) method. An out-of-sample forecast comparison of a real data set shows that the proposed GHARQ method outperforms other existing methods in terms of optimizing the variances of portfolios.     

Tweaking public sector reporting with integrated reporting (IR) concepts

ABSTRACT

This paper examines the annual departmental reports prepared by Maltese government departments and highlights the gap between current practices and integrated reporting (IR). The authors suggest that principles and elements of IR could be gradually introduced in an effort to enhance transparency and accountability. The internalization of integrated thinking could also lead to enhanced value creation, and overcome the silo mentality that characterizes the Maltese public sector. Detailed guidelines for preparing ADRs urgently need to be developed in Malta—preparers should not expect to find them in the IIRC Framework, because they are not there.     

机器类设备基于不同时延需求分组的随机接入方法

针对大规模机器类通信中拥塞导致的时延敏感设备时延高和接入成功率低的问题，提出将小区中设备按时延要求分组，对不同组设备引入不同的退避模型，分析时延敏感设备的时延和吞吐量，按照不同组中设备的时延需求动态分配前导数目，同时通过调整接入类限制因子实现吞吐量的优化。仿真结果表明，在给定时延敏感设备的时延限制条件时，与统一退避的机制对比，所提分组机制的时延敏感设备能够满足时延要求，并且提高了接入效率。     

Pareto efficient allocation of an in-motion wireless charging infrastructure for electric vehicles in a multipath network

Electric vehicles (EV) use an eco-friendly technology that limits the greenhouse gas emissions of the transport sector, but the limited battery capacity and the density of the battery are the major barriers to the widespread adoption of EV. To mitigate this, a good method seems to be the innovative wireless charging technology called ‘On-Line EV (OLEV)’, which is a contactless electric power transfer technology. This EV technology has the potential to charge the vehicle’s battery dynamically while the vehicle is in motion. This system helps to reduce not only the size of the battery but also its cost, and it also contributes to extending the driving range before the EV has to stop. The high cost of this technology requires an optimal location of the infrastructure along the route. For this reason, the objective of this paper is to study the problem of the location of the wireless charging infrastructure in a transport network composed of multiple routes between the origin and the destination. To find a strategic solution to this problem, we first and foremost propose a nonlinear integer programming solution to reach a compromise between the cost of the battery, which is related to its capacity, and the cost of installing the power transmitters, while maintaining the quality of the vehicle’s routing. Second, we adapt the multi-objective particle swarm optimization (MPSO) approach to our problem, as the particles were robust in solving nonlinear optimization problems. Since we have a multi-objective problem with two binary variables, we combine the binary and discrete versions of the particle swarm optimization approach with the multi-objective one. The port of Le Havre is presented as a case study to illustrate the proposed methodology. The results are analyzed and discussed in order to point out the efficiency of our resolution method.     

Optimal granularity for portfolio choice

Many optimization-based portfolio rules fail to beat the simple 1/N rule out-of-sample because of parameter uncertainty. In this paper we suggest a grouping strategy in which we first form groups of equally weighted stocks and then optimize over the resulting groups only. This strategy aims at balancing the trade-off between the benefits from optimization and the losses from estimation risk. We rely on Monte-Carlo simulations to illustrate the performance of the strategy, and we derive the optimal group size for a simplified setup. Furthermore, we show that estimation risk also has an impact via the criterion by which the assets are sorted into groups (like the expected excess returns or betas), but does not negate the grouping approach. We relate our work to linear asset pricing models, and we conduct out of sample back-tests in order to confirm the validity of our grouping strategy empirically.     

基于运行规划的能源综合服务系统能效管理研究

以浙江电网企业转型现代能源综合服务的具体战略与发展规划为研究背景，针对能源综合服务系统的运行规划目标，开展基于运行规划的能源综合服务系统能效管理研究。从系统工程的视角出发，以能源流为纽带，基于多尺度能源系统建模方法，构建了能源综合服务系统模型，并结合系统综合能效，采用粒子群优化算法来优化系统各设备单元的运行策略，以实现基于运行规划的最优能效管理。通过能源综合服务系统模型计算表明，大规模清洁能源和可再生能源的接入，可以明显提高系统综合能效；随着区域用户总冷量和/或总热量需求占总电力需求的比值增大，系统最优综合能效逐渐增大；与使用内燃机、燃气轮机及汽轮机为原动机的热电联产系统相比，使用燃料电池为原动机的热电联产系统可以使能源综合服务系统综合能效更优。