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Repeat customers play an important role in the restaurant sector. Previous studies have confirmed the positive effect of managerial responses on customer relationship management. However, the practice of managerial response strategies toward repeat customers in the restaurant sector remains unclear. This study aims to explore how social influence and the revisit intention of customers affect the responding behavior of restaurant managers.

This study collects information of 251,944 customer reviews and managerial responses from 1,272 restaurants on Yelp (a leading restaurant review website around the world) and builds four econometric models (with restaurant and month fixed effects) to test the hypotheses empirically.

The empirical results show that restaurant managers are less likely to respond to reviews posted by repeat customers (10% lower than that of new customers). This effect is moderated by customer social influence, which entails that repeat customers with great social influence are more likely to receive managerial responses. Moreover, reviews from repeat customers who have had a longer time since their last consumption are also more likely to receive managerial responses.

The results present implications for restaurant managers in business practice regarding managerial response. Managers should take advantage of platform designs and tools (i.e. customer relationship management programs to keep track of repeat customers) to locate repeat customers and avoid the potential negative effects caused by their selected response strategies.

To the best of the authors’ knowledge, this study is among the first attempts to examine empirically how restaurant managers respond to reviews generated by repeat customers in real business practice and reveals what drives such activities from the perspectives of social influence and revisit intention.

The purpose of this paper is to improve the hydraulic efficiency without changing the overall dimension. The blade profile optimization design of the aero-centrifugal pump based on the biharmonic equation surrogate model has been studied.

First of all, Bezier curves and linear function are used to control the annular angle distribution and the stacking angle of blade profile under the MATLAB platform. Grid independence analysis has been studied to find the finest mesh scheme. After the precision comparison of test data and computation fluid dynamics 15 sets of design parameters are carried out as the boundary condition of the biharmonic equation. The efficiency surrogate model of the biharmonic equation is constructed via iteratively solving of a discrete difference equation. The other two surrogate models of response surface model (RSM) and radial basis function neural network surrogate model (RBFNNSM) are compared with the biharmonic equation surrogate model by the standard of modified complex correlation coefficient R² and root mean square deviation (RSME). Finally, the artificial fish swarm algorithm has been used to find the global optimal design parameters with the objective function of highest efficiency.

The results show that the design parameters code conversion method can reduce the number of optimization parameters from five to three, makes the design space become a cube, and compared with RSM and RBFNNSM, the biharmonic equation surrogate model has higher precision with R² is 0.8958, RSME is 0.1382. The final optimum result of AFSA is at the point of [1 −1 −1]. The internal flow field analysis shows that after optimization the outlet relative velocity becomes more uniform and the wake effect has been significantly decreased. The hydraulic efficiency of the optimized pump is about 59.45 per cent increasing 5.4 per cent compared with a prototype pump.

This study developed a new method to optimize the design parameters of aero-centrifugal pump impeller based on biharmonic equation surrogate model, which had a good agreement with experimental values within just 15 sets of the original design. The optimization results shows that the method can improve the hydraulic efficiency significantly.

This paper aims to report the conductivity measurement of ten different surfactant-free microemulsions (SFMEs)

The variations of electrical conductivity as a function of water volume fraction are examined at one constant alcohol (or DMF, ethyl lactate, γ-valerolactone)/water, alcohol (or DMF, ethyl lactate, γ-valerolactone)/oil volume ratios for each sample.

Most of the results are consistent with percolation character. The conductive mechanism of these SFMEs is discussed by the percolation model, and it is found that it might be described with the static percolation model below the percolation threshold.

Our report gives a systematic research on the percolation mechanism of as many species of SFMEs as possible by the theoretical models

This study aims to provide a critical reflection of the application of image recognition techniques in visual information mining in hospitality and tourism.

This study begins by reviewing the progress of image recognition and advantages of convolutional neural network-based image recognition models. Next, this study explains and exemplifies the mechanisms and functions of two relevant image recognition applications: object recognition and facial recognition. This study concludes by providing theoretical and practical implications and potential directions for future research.

After this study presents different potential applications and compares the use of image recognition with traditional manual methods, the main findings of this critical reflection revolve around the feasibility of the described techniques.

Knowledge on how to extract valuable visual information from large-scale user-generated photos to infer the online behavior of consumers and service providers and its influence on purchase decisions and firm performance is crucial to business practices in hospitality and tourism.

Visual information plays a crucial role in online travel agencies and peer-to-peer accommodation platforms from the side of sellers and buyers. However, extant studies relied heavily on traditional manual identification with small samples and subjective judgment. With the development of deep learning and computer vision techniques, current studies were able to extract various types of visual information from large-scale datasets with high accuracy and efficiency. To the best of the authors’ knowledge, this study is the first to offer an outlook of image recognition techniques for mining visual information in hospitality and tourism.

Flood season in our country is characterized by frequent heavy rains, and flood problems are becoming increasingly serious. The uneven distribution of water resources causes conflicts in the occurrence of floods and droughts. Implementing effective flood control planning and solving drought and flood disasters are the research highlights of relevant institutions both domestic and abroad. This study develops a multiscale method of urban flood control planning based on microcirculation. A microcirculation water ecosystem, which consists of six elements, namely, collecting, interacting, precipitating, reserving, storing, and purifying, is introduced. This study investigates precipitation; peak shaving; recycle mode of filtration at the macro level in different regions; “hierarchy” in rainwater ecosystems in rain parks, heavy rain garden parks, and wetland parks at the meso level; and the concept of zero-emission rain in residential areas and roads at the micro level. Finally, this study analyzes a rain garden and its domestic application. A conclusion is drawn that the flood control planning model based on microcirculation can effectively reduce rain runoff. Empirical measurement proves that the proposed multiscale model for city flood control planning based on microcirculation promotes flood control and effectively reduces the occurrence of droughts and floods.

The purpose of this paper is to numerically and experimentally evaluate the effect of the protection net icing on the inlet performance of helicopter engines.

The ice shapes of the protection net at different times are first simulated by a two-dimensional (2D) icing calculation, then the porous media parameters are calculated based on the 2D ice shapes. Afterward, three-dimensional flow fields of the engine inlet with the iced net are simulated using the porous media model instead of the real protection net. The transient pressure losses of the iced protection net are calculated and tested through an icing wind tunnel test rig under different icing conditions.

Overall, the numerical results and experimental data show a good agreement. The effects of several control parameters, such as liquid water contents (LWC), water droplet diameters and airflow velocities on the pressure loss of the protection net during the icing process are analyzed in a systematic manner. The results indicate that the pressure loss increases with the increase of the LWC at the same icing time. The same trend occurs when the water droplet diameter and the airflow velocity increase.

A new method to predict the pressure loss of the iced protection net is proposed. A series of tests in an icing wind tunnel are performed to obtain the ice shapes and pressure loss of protection net during the icing process.

Innovation ecosystem research has highlighted complementors as the critical force to determining focal firm innovation’s success in addition to the traditional value chain or supply chain perspective. However, literature is relatively scarce in terms of innovation ecosystem governance, especially, on how to manage various types of complementors. The purpose of this paper is to fill this theoretical gap by developing a typology of managing complementors from multiple case studies.

This study conducted multiple case studies of three leading focal firms with ecosystem strategies to understand innovation ecosystem governance. Theoretical themes are inductively generated to reveal their success in managing complementors in their ecosystems.

The case analysis reveals four generic strategies to manage complementors. These strategies are contingent on the types of complementors and level of interdependence: focal firms tend to engage functional complementors and collaborate with infrastructural complementors when the level of interdependence is higher, and acquire functional complementors and nurture infrastructural complementors when the level of interdependence is lower.

For practitioners, this study can improve their understanding on the mechanisms of innovation ecosystem governance, particularly interdependence between participants in an innovation ecosystem, and developing appropriate strategies to manage different types of complementors in innovation ecosystems.

This study contributes to innovation ecosystem literature by enriching the conceptualization of interdependence in innovation ecosystems and unpacking innovation ecosystem governance with the inductively developed holistic typology of strategies to manage complementors. Meanwhile, this study also suggests underlying mechanisms for how innovation ecosystem governance and, therefore, contributes to a systematic theory on understanding innovation ecosystem governance.

Food SMEs is the backbone of local and world economy. Even while food SMEs are aware of the potential advantages of implementing supply chain analytics (SCA), only a small number of companies use data-based decision-making. This is because of technophobia. In light of this, the purpose of this study is to investigate the factors that have an impact on SCA adoption which in turn influence the sustainable performance of firms.

The data were collected from 221 managers working in food-related SMEs in China by using a questionnaire-based survey. The framework of this study was validated using a rigorous statistical procedure using the technique, namely, partial least squares structural equation modelling.

The findings of this study suggest that all modified UTAUT components (i.e. performance expectancy, effort expectancy, social influence, facilitating conditions and technophobia) significantly influence SCA adoption. Moreover, the existing study highlights and confirms the significance of adopting SCA to improve sustainable performance.

This research is novel, as it extends and investigates the theoretical framework based on UTAUT theory in SCA context and its impact on sustainable organizational performance. In addition, the factor of technophobia is tested in SCA context. This study has several contributory managerial implications for food SMEs.

Studies have documented the distinctive advantage of innovation ecosystems in integrating and recombining heterogeneous knowledge resources across firms' boundaries. However, hierarchical governance in the form of vertical integration is still preferred in many industries for organizing innovation, and the current literature touches little on the relative performance of different organizational structures (integrated firms vs innovation ecosystem) and the factors that lead firms to choose one over the other. The authors conjecture that structure of technological interdependence is one of such important factors. Using a computational experiment, the authors compare the innovation performance of ecosystems with integrated firms under different interdependency structures.

Using the NKC model, the authors incorporate non-generic complementarities and modularity into the technological interdependence between different components. The authors compare four different types of technological interdependence (modular, hierarchical, nearly modular, and random).

The results show that integrated firms with centralized search demonstrate stable and consistent performance that is robust to the structure of technological interdependencies, but an ecosystem significantly outperforms integrated firms with centralized or decentralized when the products exhibit modular or nearly-modular structures.

This study sheds light on why an ecosystem often exhibits modular structures while vertical integration is prevalent in industries with complex technological interdependence. In addition, it shows the evolutionary nature of ecosystems and indicates how the cooperation and competition between actors shape the interdependence structure of ecosystems.

Debates regarding climate change risk perception (CCRP), particularly its scale and impact on social and environmental sustainability, have continued for decades. CCRP is experiencing a renaissance with an increased focus on environmentally relevant behaviors to mitigate the effects of climate change. However, CCRP lacks investigation from the employee perspective. Supported by the social exchange and value–belief–norm theories, this study aims to address the impact of employees’ CCRP on their proenvironmental behavior (PEB) via the moderating roles of environmental values and psychological contract breach.

The nonprobability convenience sampling technique was used to collect survey data from a sample of 299 employees across 138 manufacturing firms in Pakistan.

The results show that employees’ CCRP positively impacts their PEB and that this relationship is moderated by their environmental values and psychological contract breach. Specifically, environmental values strengthen the CCRP–PEB relationship, while psychological contract breach weakens it.

The findings of the study emphasize useful guidance for managers and practitioners as a future avenue to restructure the climate change framework by emphasizing the conditions (i.e. environmental values and psychological contract breach). In doing so, the study is beneficial for managers and practitioners in helping to increase employees’ PEB through the development of climate change action plans.

To the best of the authors’ knowledge, this study is one of the first investigations into CCRP–employees’ PEB nexus in the developing country context. The study incorporates social exchange and value–belief–norm theory, which serve as the CCRP’s theoretical underpinnings. The findings advance the new knowledge about a firm’s social responsibility to achieve the sustainable development goals outlined in the UN’s 2030 Agenda.