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Online reviews serve as valuable sources of information, reflecting tourists’ attentions, preferences and sentiments. However, although the existing research has demonstrated that incorporating online review data can enhance the performance of tourism demand forecasting models, the reliability of online review data and consumers’ decision-making process have not been given adequate attention. To address the aforementioned problem, the purpose of this study is to forecast tourism demand using online review data derived from the analysis of review helpfulness.

The authors propose a novel “identification-first, forecasting-second” framework. This framework prioritizes the identification of helpful reviews through a comprehensive analysis of review helpfulness, followed by the integration of helpful online review data into the forecasting system. Using the SARIMAX model with helpful online review data sourced from TripAdvisor, this study forecasts tourist arrivals in Hong Kong during the period from August 2012 to June 2019. The SNAÏVE/SARIMA model was used as the benchmark model. Additionally, artificial intelligence models including long short-term memory, back propagation neural network, extreme learning machine and random forest models were used to assess the robustness of the results.

The results demonstrate that online review data are subject to noise and bias, which can adversely affect the accuracy of predictions when used directly. However, by identifying helpful online reviews beforehand and incorporating them into the forecasting process, a notable enhancement in predictive performance can be realized.

First, to the best of the authors’ knowledge, this study is one of the first to focus on the data issue of online reviews on tourism arrivals forecasting. Second, this study pioneers the integration of the consumer decision-making process into the domain of tourism demand forecasting, marking one of the earliest endeavors in this area. Third, this study makes a novel attempt to identify helpful online reviews based on reviews helpfulness analysis.

Multicasting is a necessity for a broadband metro‐area‐network. Discusses the security problems with current multicast protocols. To make the multicast delivery infrastructure more secure and reliable, a stateful multicast access control mechanism, based on MAPE, is proposed. This mechanism expands the current forwarding procedure of a layer 2 switch so that stateful multicast access control can be carried out at the very edge of the metro area network. The architecture of MAPE is discussed in detail, as well as the states maintained and messages exchanged. Further explains that the scheme is flexible and scalable.

This paper aims to study the influence of the Cu-Al₂O₃ film-coated Cu substrate as a thermal interface material (TIM) on the thermal and optical behaviour of the light-emitting diode (LED) package and the annealing effect on the thermal and optical properties of the films.

A layer-stacking technique has been used to deposit the Cu-Al₂O₃ films by means of magnetron sputtering, and the annealing process was conducted on the synthesized films.

In this paper, it was found that the un-annealed Cu-Al₂O₃–coated Cu substrate exhibited low value of thermal resistance compared to the bare Cu substrate and to the results of previous works. Also the annealing effect does not have a significant impact on the changes of properties of the films.

It is deduced that the increase of the Cu layer thickness can further improve the thermal properties of the deposited film, which can reduce the thermal resistance of the package in system-level analysis.

The paper suggested that the Cu-Al₂O₃–coated Cu substrate can be used as alternative TIM for the thermal management of the application of LEDs.

In this paper, the Cu substrate has been used as the substrate for the Cu-Al₂O₃ films, as the Cu substrate has higher thermal conductivity compared to the Al substrate as shown in previous work.

This study is the first that aims to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

Multiple spatial weight matrices can capture the contiguity of spatial units from various dimensions, which could be exploited to improve the precision of inference as well as prediction accuracy. To the best of the authors’ knowledge, this is the first study to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

With network structure analysis, this study finds that they contain different information content from the perspective of graphical display, node strength and correlation. Developed and emerging countries all play major roles in trade connection, while only developed countries play major roles in financial linkage. Second, by applying the multidimensional SAR model, only the spatial autocorrelation coefficients for trade and financial linkages are significant during the full sample period, which is in sharp contrast to published studies using the SAR model with a single matrix. Third, the spillover channels that play major roles in various periods are different. Only trade channel plays a role during crisis periods and it is the most important. Fourth, the spatial correlation among countries greatly amplifies the shock’s impacts on one market. And spatial effect for developed countries is larger than those for emerging countries, while the mean spatial effect of a unit shock in the USA on emerging countries is slightly greater than that on developed countries.

Multiple spatial weight matrices can capture the contiguity of spatial units from various dimensions, which could be exploited to improve the precision of inference as well as prediction accuracy. To the best of the authors’ knowledge, this is the first study to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

The rapid development of e-commerce has caused not only explosive growth of the express delivery industry, but also ever-greater operational pressures. Models from the sharing economy may provide new ideas for operational improvement. The purpose of this paper is to consider an optimization method that reduces costs and increases efficiency. The proposed method enables a shared distribution system based on revenue-sharing and cooperative investment contracts.

The authors design a two-echelon supply chain (SC) of the shared distribution system with one shared distribution company and N express companies. In this SC, the express companies provide only inter-city transportation, and they outsource internal-city transportation to a shared distribution company. This distribution system differs from that of the traditional express delivery industry. The traditional system of delivery requires large numbers of empty trips (with no load to deliver), because the operating mode of urban distribution has been the franchise. To offer greater efficiency and performance, the authors introduce the sharing economy mode of express delivery. The authors examine the potential of a joint optimal decision-making strategy that involves revenue-sharing and cooperative investment contracts based on an order flow proportion (OFP) and a revenue-sharing factor (RSF). In this shared distribution system, the most important innovation is that all of the express companies jointly invest in and establish a shared distribution company based on OFP or RSF principles.

The profitability of an SC with revenue-sharing contracts based on an OFP system is much higher than that of a decentralized SC, and it is very close to the profitability of a centralized SC. In SCs with revenue-sharing contracts that are based on RSFs, there are many possible combinations of RSFs that can increase the overall profitability. The analyses indicate that the OFP system offers the best solution in designing revenue-sharing contracts based on RSFs.

This study indicates that revenue-sharing contracts based on both OFP and RSF principles can increase overall SC returns by 0.21 to 0.44 percent. In sum total, this improvement could mean a 0.84 to 1.76bn Yuan increase in revenues for the 400+ bn-Yuan express delivery industry.

The authors find that a combination of equity investment and SC coordination contracts makes the cooperation between SC members much more stable. Through this kind of shared distribution system, the scale of economy can further reduce the costs and increase the efficiency of the express delivery industry.

Reviewing a dozen of fiscal stimulus packages in developed countries, this paper analyzes one common strategy that has found widespread support in these stimulus packages and its relevance for developing countries: investing in broadband and next‐generation networks, as a counter‐cyclical tool to create jobs and provide the foundation for economic recovery and long‐term sustained growth.

The paper looks at the various impacts broadband investment is expected to have: short‐term job creation and aggregate demand effects, and long‐term productive activities in other sectors of the economy. Moreover, broadband investment is more fiscally sound than other public spending stimulus options, in the sense of coming closer to, or in some cases actually being, self‐financing.

Several factors highlight the potential of broadband infrastructure as an important area of public investment during economic downturn, an option also open to policymakers in developing countries. Spending initiatives on next‐generation telecommunications networks at a time when labor market conditions are particularly weak can help preserve jobs and head off a potential burden on social safety nets. Bringing forward longer‐term aggregate spillover effects of broadband can improve the productivity of the entire economy and is consistent with enhancing longer‐run growth and development. Public support also “crowds in” private investment when access to private financing is decreasing and more expensive.

This is one of the few studies with a focus on the emerging broadband network, its impact on economy and the role of the public sector in rolling out next‐generation networks, during economic downturn and in general. A detailed summary of broadband initiatives in more than a dozen developed countries is provided in the paper.

The purpose of this paper is to present an intelligent data-driven framework which provides an effective group-buying aggregation service and thus offers a new opportunity for personalized services in recommendation and advertisement.

The work presented in the paper analyzes the aggregated group-buying data and creates a compact view of the data which eliminates the potential redundancy and noise. In doing this, the dependencies are discovered from the data in a reverse engineering way. A noise-tolerant method is appreciated, as noise and exception is inevitable in massive data.

The paper finds that, through the implementation of the intelligent framework, the aggregator will provide a compact view of the group-buying data to customers. According to the empirical study, a 38 percent average decrease of redundancy and noise in the searching results is achieved through the newly built views and corresponding data.

The paper presents the innovative process of discovering the dependencies and creating views in a data-driven and noise-tolerant way. The proposed intelligent framework improves the aggregation performance and forms the basis of personalized services.

Despite the knowledge transfer between projects has received increasing attention from scholars, few scholars still conduct comprehensive research on inter-project knowledge transfer from both horizontal and vertical perspectives. Besides, knowledge transfer is affected by multiple antecedent conditions, and these factors should be combined for analysis. Therefore, this paper aims to explore the key factors influencing knowledge transfer between projects using the fuzzy-set qualitative comparative analysis (fsQCA) method from both horizontal and vertical perspectives and how these factors combine to improve the effectiveness of knowledge transfer (EKT) between projects.

First, nine factors affecting knowledge transfer between projects were identified, which were from the four dimensions of subject, relationship, channel, and context, namely temporary nature (TN), time urgency (TU), transmit willingness (TW), receive willingness (RW), trust (TR), project-project transfer channels (PPC), project-enterprise transfer channels (PEC), organizational atmosphere (OA), and motivation system (MS). Then, the source of the samples was determined and the data from the respondents was collected for analysis. Following the operation steps of the fsQCA method, variable calibration, single condition necessity analysis, and configuration analysis were carried out. After that, the configurations of influencing factors were obtained and the robustness test was conducted.

The results of the fsQCA method show that there are five configurations that can obtain better EKT between projects. Configuration 3 (∼TN * ∼TU * TW * RW * TR * ∼PPC * PEC * MS) has the highest consistency, indicating that it has the highest degree of the explanatory variable subset. Configuration 1 (∼TN * ∼TU * TW * RW * PEC * OA * MS) has the highest coverage, meaning that this configuration can explain most cases. Also, the five configurations were divided into three types: vertical transfer, horizontal-vertical transfer, and channel-free transfer category.

Firstly, this study explores the key factors influencing knowledge transfer between projects from four dimensions, which presents the logical chain of influencing factors more clearly. Then, this study divided the five configurations obtained into three categories according to the transfer direction: vertical, horizontal-vertical, and channel-free transfer, which gives implications to focus on both horizontal knowledge transfer (HKT) and (VKT) when studying knowledge transfer between projects. Lastly, this study helps to realize the exploration of combined improvement strategies for EKT, thereby providing meaningful recommendations for enterprises and project teams to facilitate knowledge transfer between projects.

A detailed analytical study of Leping bark liptobiolith in Jiangxi was conducted to determine its petrographic characteristics and depositional environment based on coal petrography and geochemistry. Results indicate that barkinite mainly occurs in the middle and lower coal sea4ms, whereas less barkinite and more vitrinite occur in the middle and upper coal seams. Coal facies analysis of bark liptobiolith was performed to determine its characteristics under various depositional conditions, such as the presence of a water table and gelification during coal formation. Results indicate that the environmental evolution of bark liptobiolith begins from brackish-marine swamp facies (barkinite-rich coal seam) and ends in back barrier swamp facies (barkinite-poor coal seam).

The purpose of this paper is to propose a framework for describing and evaluating the representativeness of a small set of search results extracted from the original results: this is deemed desirable in information retrieval in enterprise information systems.

The paper proposes a combined measure, namely RF_β, to evaluate the extracted small set in terms of the notions of coverage and redundancy. Data experiments were conducted on three different extraction strategies to evaluate the representativeness, i.e. coverage and redundancy.

Both from intuitive and experimental perspectives, the proposed coverage measure, redundancy measure and RF_β measure could effectively evaluate the representativeness.

The search results, e.g. in the form of documents and texts, are modeled using a vector space model and cosine similarity. Semantic models and linguistic models could be further introduced into this research to improve the proposed measures.

With the rapidly growing need for information retrieval in enterprise information systems, the representativeness of search results become more desirable and important for search engine users. The well‐designed representativeness measures will help them achieve satisfactory results.

The originality of the paper lies in the definition of representativeness of a small set of search results extracted from the original results. This focuses on the two aspects of coverage rate and redundancy rate both from intuitive and experimental perspectives.