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This paper points out new directions for the deepening and broadening of the institution-based view, by drawing on three streams of research with which I have been involved recently: (1) outward foreign direct investment from emerging economies, (2) bankruptcy laws and entrepreneurship development, and (3) institution-based research focusing on Africa. Such deepening has been accomplished by enhancing our institution-based understanding of foreign direct investment with a focus on emerging multinationals, while broadening has been done both substantively by probing into the impact of bankruptcy laws on entrepreneurship development around the world and geographically by calling for enhanced research attention on Africa via an institution-based lens.

This paper aims to introduce the history and major achievement of the Chinese private enterprise survey (CPES), which is one of the most enduring large-scale nationwide sample surveys in China, providing important micro firm-level data for understanding and studying the development of Chinese enterprises and entrepreneurs over the past 26 years.

The main body of this paper is based on a bibliometric analysis of all literature using CPES until 2017.

This paper discusses problems that users may encounter during data mining. By doing so, it can assist other researchers to get a better understanding of what has been done (e.g. journals, topics, scholars and institutions) and do their research in a more targeted way.

As members of the survey project team, the authors also take a prospect of the future data design and use, as well as offer some suggestions about how to use the CPES data to improve high-quality development and business environment evaluation in China.

This paper is the first to provide an overall picture of academic papers in China and abroad that have used the CPES data.

The purpose of this study is to propose a new coordinated dynamic demand lot-size and delivery planning problem (CDLSDP), in which the delivery policy is integrated into the coordinated dynamic demand lot-size problem (CDLSP).

As a non-deterministic polynomial complete (NP-complete) problem, this CDLSDP seems difficult to be solved by a polynomial-time method. To handle this problem effectively and efficiently, a four-phase heuristic that balances the setup and inventory costs in the coordinating and delivery stages is designed to find near-optimal solutions.

Numerous computational experiments show that the proposed four-phase heuristic is effective and efficient. For 1,800 experiments with different scales, and different joint setup costs, solutions by the proposed heuristic have an average gap no more than 1.34% from the optimal solution.

To decrease total system cost, the CDLSDP optimizes the time-phased replenishment and delivery schedule, which includes joint setup cost, item setup, delivery and inventory cost, for each period. An effective and efficient four-phase heuristic is designed to solve the CDLSDP.

Compared with the traditional CDLSP, the delivery policy is considered by the new CDLSDP. Moreover, the proposed four-phase heuristic is a good candidate for solving the CDLSDP.

Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios.

A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale.

The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases.

A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

The purpose of this paper is to identify the factors that influence people to play socially interactive games on mobile devices. Based on network externalities and theory of uses and gratifications (U&G), it seeks to provide direction for further academic research on this timely topic.

Based on 237 valid responses collected from online questionnaires, structural equation modeling technology was employed to examine the research model.

The results reveal that both network externalities and individual gratifications significantly influence the intention to play social games on mobile devices. Time flexibility, however, which is one of the mobile device features, appears to contribute relatively little to the intention to play mobile social games.

This research successfully applies a combination of network externalities theory and U&G theory to investigate the antecedents of players’ intentions to play mobile social games. This study is able to provide a better understanding of how two dimensions – perceived number of users/peers and individual gratification – influence mobile game playing, an insight that has not been examined previously in the mobile apps literature.

This research paper aims to empirically analyse the impact of digital technologies and government support on the resilience of small and medium-sized enterprises (SMEs) during the COVID-19 pandemic; in other words, how SMEs survive and manage the negative impact of the health situation with the support of digital technologies and government policy. A questionnaire survey was employed based on a sample of 96 SMEs and was divided into three parts, which comprised 28 questions. The SPSS software was used to analyse the results. The significant findings indicate that digital technologies positively affect SMEs' resilience during the COVID-19 pandemic, combined with public support. This implies that digital technologies help SMEs be resilient and ensure their survival in a unique and challenging environment. This study has practical implications for different stakeholders to evaluate risks in health emergencies, filling a significant research gap in the literature. Furthermore, this research paper can provide empirical results on the potential impact of digital technologies used by SMEs and the availability of government support to survive during the COVID-19 crisis.

The COVID-19 pandemic had a huge negative impact on the world’s hotel industry from the beginning of 2020. As a result of the pandemic, the majority of hotels around the world have decided to close temporarily. It examines the challenges faced by hotel managers and the strategies used to survive.

This research can motivate hotel companies around the world to better understand pandemic situations and develop effective anti-pandemic policies. Based on online in-depth interviews with 25 hotel managers, the findings shed light on the various challenges to hotels.

Findings have shown that the hotel industry has been able to adapt their business for the short term with post-COVID-19 strategies still having limitations. To survive the duration of the pandemic hotels have adopted strategies: reducing employees, promotions and discounts and changing the market segment, as well as levels of maintenance of hygiene and cleanliness. The hotel industry can implement opportunities toward change through government support, crisis management, cooperation with travel agencies and technology.

The current research is to determine the impact of COVID-19 and the adaptive strategies on the hotel sector in the Siem Reap province by the following objectives: (1) To analyse the impacts of COVID-19 in the hotel sector, (2) To identify adaptive strategies in dealing with COVID-19 in the hotel sector and (3) To explore post-COVID-19 strategies of the hotel sector after the COVID-19 pandemic. A qualitative method was employed in the research online and in-depth interviews were conducted with the owner and general manager.

The study suggests that hotels focus more on survival strategies for the short term, so the topic for future research could be to investigate details of strategies after the COVID-19 pandemic in order to research what the hotels' strategic solutions will be and how they will manage the operation after the COVID-19 pandemic for long-term strategies.

This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.

Firstly, a single-train trajectory optimization (STTO) model is constructed based on train dynamics and operating conditions. The train kinematics parameters, including acceleration, speed and time at each position, are calculated to predict the arrival times in the train timetable. A STTO algorithm is developed to optimize a single-train time-efficient driving strategy. Then, a TTR approach based on multi-train tracking optimization (TTR-MTTO) is proposed with mutual information. The constraints of temporary speed restriction (TSR) and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train. The multi-train trajectories at each position are optimized to generate a time-efficient train timetable.

The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF. The STTO algorithm predicts the train’s planned arrival time to calculate the total train delay (TTD). As for the TSR scenario, the proposed TTR-MTTO can reduce TTD by 60.60% compared with the traditional TTR approach with dispatchers’ experience. Moreover, TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.

With the cooperative relationship and mutual information between train rescheduling and control, the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

From the atom economy and environmentally friendly point of views, the development of clean and green approaches using ionic liquids (ILs) as recyclable catalysts has attracted increasing attention. The purpose of this study is to investigate the effect of task-specific ILs content on the one-pot three-component Biginelli reaction.

A series of halogen-free quaternary ammonium ILs functionalized with –SO₃H group were prepared and characterized by ¹H nuclear magnetic resonance (NMR), ¹³C NMR and electrospray ionization mass spectrometry. The ILs were used as catalysts for Biginelli reaction among aromatic aldehydes, urea or thiourea and β-dicarbonyl compounds. Anions and cations of ILs were varied to observe their effects on and contributions to the catalysts. The influencing factors, such as the amount of catalyst, solvent, reaction time and reaction temperature, were investigated.

The effect and contribution of cations of ILs were observed. Results showed that 3-(N, N-dimethylhexadecylammonium) propanesulfonic acid toluene sulfate ([DHPA][Tos]) showed comparable catalytic activity. Good adaptability to the reaction substrate and maximum product yield was observed when [DHPA][Tos] was used as catalyst. It was found that Biginelli reaction catalyzed by 10 mol% [DHPA][Tos] for 3 h under solvent-free conditions at 80 °C gave the best yield of 94%. Post-processing steps were simple, and the catalyst could be reused easily.

This paper demonstrates that ILs containing a long carbon chain and a bulky Tos anion efficiently promoted the reaction, in which the long carbon chains facilitate mass transfer in the reaction system.

Research suggests that context matters for MNEs’ international business strategy. MNEs’ strategies vary when different intertwined contexts interact with each other. While International Business scholars understand well the influence of the institutional environments on firms’ international strategies and operations, some contextual differences are less understood as is the case involving African countries and firms. In this study we investigate how different institutional contexts and legitimacy challenges combine to impact ownership strategic choices of African firms in their cross-border acquisitions (CBAs). Specifically, we study the influence of the host country institutional development and two institutional dimension distances: administrative distance and knowledge distance. Methodologically, we use a sample of 314 CBAs made by acquirers from 24 African countries in 71 host countries worldwide to test a number of theoretically driven hypotheses. This study contributes to our understanding of how foreign investors from less institutionally developed countries that are more likely to face higher legitimacy barriers use ownership strategies to achieve legitimacy abroad.