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Hydroelectric power is widely used because it is environmental friendly, renewable and green. The cavitation is an inevitable phenomenon during the operation of hydro turbine, which is related to the efficiency and service life of the unit. This paper aims to discriminate the phenomenon of the incipient cavitation, prevent the early destruction and avoid the irreversible damage to hydro turbine.

The paper tries to find out the characteristics of cavitation entirely through a variety of features. The method comprises collection of the signals using a hydrophone, acceleration sensor and acoustic emission sensor; analyzing cavitation signal by using the way of wavelet time-frequency, peak factor and power spectral density; and comparing the different wavelet basis for analyzing signals and find the most suitable one.

The analyzed results show that the wavelet basis of morlet is more suitable for the cavitation signals. The hydrophone can distinguish the different operating conditions and discriminate the difference between the phenomenon of incipient cavitation and the other state of cavitation. The results show that when the hydrophone and acceleration sensors are used, the accuracy rate goes up to 75 per cent, which meets the requirements for the detection for incipient cavitation.

This paper focuses on finding the best sensor to discriminate the operating state of incipient cavitation to prevent early destruction.

The effective prediction of crude oil futures prices can provide a reference for relevant enterprises to make production plans and investment decisions. To the nonlinearity, high volatility and uncertainty of the crude oil futures price, a matrixed nonlinear exponential grey Bernoulli model combined with an exponential accumulation generating operator (MNEGBM(1,1)) is proposed in this paper.

First, the original sequence is processed by the exponential accumulation generating operator to weaken its volatility. The nonlinear grey Bernoulli and exponential function models are combined to fit the preprocessed sequence. Then, the parameters in MNEGBM(1,1) are matrixed, so the ternary interval number sequence can be modeled directly. Marine Predators Algorithm (MPA) is chosen to optimize the nonlinear parameters. Finally, the Cramer rule is used to derive the time recursive formula.

The predictive effectiveness of the proposed model is verified by comparing it with five comparison models. Crude oil futures prices in Cushing, OK are predicted and analyzed from 2023/07 to 2023/12. The prediction results show it will gradually decrease over the next six months.

Crude oil futures prices are highly volatile in the short term. The use of grey model for short-term prediction is valuable for research. For the data characteristics of crude oil futures price, this study first proposes an improved model for interval number prediction of crude oil futures prices.

Tourism demand forecasting is vital for the airline industry and tourism sector. Combination forecasting has the advantage of fusing several forecasts to reduce the risk of inappropriate model selection for analyzing decisions. This paper investigated the effects of a time-varying weighting strategy on the performance of linear and nonlinear forecast combinations in the context of tourism.

This study used grey prediction models, which did not require that the available data satisfy statistical assumptions, to generate forecasts. A quality-control technique was applied to determine when to change the combination weights to generate combined forecasts by using linear and nonlinear methods.

The empirical results showed that except for when the Choquet fuzzy integral was used, forecast combination with time-varying weights did not significantly outperform that with fixed weights. The Choquet integral with time-varying weights significantly outperformed that with fixed weights for all model combinations, and had a superior forecasting accuracy to those of other combination methods.

The tourism sector can benefit from the use of the Choquet integral with time-varying weights, by using it to formulate suitable strategies for tourist destinations.

Combining forecasts with time-varying weights may improve the accuracy of the predictions. This study investigated incorporating a time-varying weighting strategy into combination forecasting by using CUSUM. The results verified the effectiveness of the time-varying Choquet integral for tourism forecast combination.

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

E-entrepreneurship is developed based on digital platforms, having specific technical opportunities, such as the interactive ecosystem, fast payment method and online store function, without strict requirements for online entrepreneurs. Considering China’s e-entrepreneurship environment and cultural background, this paper aims to analyse individuals’ e-entrepreneurship motivation based on the capability–opportunity–motivation–behaviour (COM-B) behaviour changing theory.

Through testing 602 samples based on the partial least squares path modelling and variance-based structural equation modelling, the factors from the opportunity and capability units positively affect individuals’ e-entrepreneurship motivation. Meanwhile, because of the economic and social environmental differences between China’s urban and rural regions, this study promotes the multi-group analysis based on individuals’ regional backgrounds.

First, as opportunity factors, technical and policy opportunities have significantly positive relationships with individuals’ e-entrepreneurship motivation. Second, entrepreneurial and cultural capabilities are essential for Chinese entrepreneurs while making an entrepreneurial decision. Third, because of the e-entrepreneurial environment difference and educational system gap, entrepreneurial capability exerts a greater influence on the e-entrepreneurship motivation for Chinese individuals from urban regions, and cultural capability exerts a higher impact on the e-entrepreneurship motivation for Chinese individuals from rural regions.

Whilst the phenomenon of e-entrepreneurship is emerging as a popular entrepreneurship area of study, little research has systematically explored individuals’ e-entrepreneurial motivation and analysed influencing factors from macro and minor aspects. According to the COM-B behaviour changing theory, this paper discovers influencing factors from environmental opportunity and personal capability units, and it is helpful to present individuals’ attitudes to the platform-based business model.

The purpose of this paper is to review the literature that measures the concept of firms' information environment (IE) with focus on the validity of proxies used to measure IE.

The paper reviews the IE literature using theoretically based categories and analyzes the contextual meaning and use of IE proxies. The review is based on a selection of 284 research articles from 51 journals between 2000 and 2018. A total of 37 different proxy measures of IE are found and analyzed with respect to causality based on categories and the use of IE variables as dependent, independent and control variables.

The study indicates that the IE measures are heterogeneous and there is a lack of consensus regarding their use. The different conditions used to study IE explain part, but far from all, of this heterogeneity. Furthermore, we find that the use of IE measures is only briefly discussed or motivated among the studies in the sample. These findings suggest a necessary discussion about causality in the use of IE as dependent, independent or control variables.

This study contains new and significant information on IE and IE proxy measures. It provides an extensive literature review and provides a novel typology to analyze IE.

The purpose of this paper is to investigate the agility of oil and gas value chains in the United Arab Emirates (UAE) and to understand the impact of implementing supply disruption (SD) strategies, outsourcing strategies (OS) and management strategies (MS) on oil and gas value chain agility (VCA). The results can support the oil and gas industry across the UAE to build resilience in the value chain.

The research design consists of a comprehensive literature review, followed by questionnaire-based survey responses of 106 participants and comprehensive statistical analysis, thus validate the developed theoretical framework and contribute to both practical and methodological approaches.

The findings indicate that oil and gas value chain in the UAE has moderate a significant degree of SD, when OS in place that are synchronized with the overall MS. Among the hypotheses developed, two were accepted thus warranting both SD strategies (r=+0.432) and MS (r= +0.457) found to have a positive moderate effect on VCA. The third hypothesis was rejected by revealing OS (r=+0.387) found to have a positive moderate relationship with VCA. Therefore, implementation of all three strategies has a positive moderate effect on the agility of the value chain and, therefore, supports to sustain competitive position.

Some of the limitations of this research include the geographic coverage of the study region and other methodological limitation.

The research provides guidance for oil and gas supply chain managers to better understand the critical factors that impact and determine VCA. The paper also describes relevant strategies that should be taken into consideration by these managers in order to build their agile value chains.

The research contributes to the social dimensions of supply chain sustainability of how resilient is the oil and gas value chain during uncertain conditions, so that it can respond to uncertain changes in order to contribute to corporate social responsibility.

This research is the first of its kind in the UAE region to assess the link between dimensions of agile value chain, OS, SD strategies and MS primarily from the Emirates of Abu Dhabi and Dubai.

The incentive cost of enterprises increases significantly with the rapid growth of the social commerce (SC) market. In this context, enterprises need to develop the optimal strategy to improve incentive effectiveness and reduce cost. Different types of consumers’ responses to incentives bring different values to enterprises. Hence, this paper proposes the social commerce value network (SCVN) to help enterprises study the contributions of different types of consumers to the network.

Based on the graphical evaluation and review technique (GERT), the authors construct the social commerce value GERT (i.e. SCV-GERT) network and design three progressive experiments for estimating the value contributions of “network stage”, “consumer type”, and “resource type” to the SCVN under the same incentives. The authors initialize the SCV-GERT model with consumer data in SC and distinguish the most valuable consumers by adjusting the incentive parameters.

The results show that the SCV-GERT model can well describe the value flow of SCVN. The incentive on forwarding consumers brings the greatest value gain to the SCVN, and social trust contributes the most to forwarding consumers.

Under the guidance of the results, platforms and enterprises in SC can select the optimal type of consumers who bring the maximum network value so as to improve the effectiveness of incentive strategy and reduce marketing costs. A four-level incentive system should be established according to the ranking of the corresponding value gains: forwarding consumers > agent consumers > commenting consumers > potential consumers. Enterprises also need to find ways to improve the social resource investments of consumers participating in SC.

This paper investigates the incentive problem in SC grounded in the SCVN and uses the GERT method to construct the SCV-GERT model, which is the first attempt to introduce GERT into the SC context. This study also makes up for the lack of comparative research on different types of consumers in SC and can provide support for enterprises’ customer relationship management and marketing decisions.

Forecasting tourism demand accurately can help private and public sector formulate strategic planning. Combining forecasting is feasible to improving the forecasting accuracy. This paper aims to apply multiple attribute decision-making (MADM) methods to develop new combination forecasting methods.

Grey relational analysis (GRA) is applied to assess weights for individual constituents, and the Choquet fuzzy integral is employed to nonlinearly synthesize individual forecasts from single grey models, which are not required to follow any statistical property, into a composite forecast.

The empirical results indicate that the proposed method shows the superiority in mean accuracy over the other combination methods considered.

For tourism practitioners who have no experience of using grey prediction, the proposed methods can help them avoid the risk of forecasting failure arising from wrong selection of one single grey model. The experimental results demonstrated the high applicability of the proposed nonadditive combination method for tourism demand forecasting.

By treating both weight assessment and forecast combination as MADM problems in the tourism context, this research investigates the incorporation of MADM methods into combination forecasting by developing weighting schemes with GRA and nonadditive forecast combination with the fuzzy integral.