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The literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.

This study searches four databases for relevant literature on on-demand service platform operations management and selects 72 papers for this review. According to the research context, the literature can be divided into research on “a single platform” and research on “multiple platforms”. According to the research methods, the literature can be classified into “Mathematical Models”, “Empirical Studies”, “Multiple Methods” and “Literature Review”. Through comparative analysis, we identify research gaps and propose five future research agendas.

This paper proposes five research agendas for future research on on-demand service platform operations management. First, research can be done to combine classic research problems in the field of operations management with platform characteristics. Second, both the dynamic and steady-state issues of on-demand service platforms can be further explored. Third, research employing mathematical models and empirical analysis simultaneously can be more fruitful. Fourth, more research efforts on the various interactions among two or more platforms can be pursued. Last but not least, it is worthwhile to examine new models and paths that have emerged during the latest development of the platform economy.

Through categorizing the literature into two research contexts as well as classifying it according to four research methods, this article clearly shows the research progresses made so far in on-demand service platform operations management and provides future research directions.

This study proposes a model that influences customer citizenship behavior during COVID-19, and empirically tests the effects of fast-food restaurant customers' perceptions of justice (price and procedural justice) on trust; trust on satisfaction and loyalty; and trust, satisfaction and loyalty on customer citizenship behavior. Furthermore, it was questioned whether there was a disparity between customer expectations based on the restaurant's image and consumption experience.

The data were gathered from customers of fast-food restaurants in the shopping centers in Turkey. The data set, which included 437 valid questionnaires, was subjected to CFA for validity and reliability, SEM analysis for hypothesis and paired sample t-Tests for the research questions.

The findings of the study indicate that perceived justice affects customer trust, which, consequently, affects customer loyalty and satisfaction during the COVID-19 period. Findings also demonstrate that, while customer loyalty and trust increase customer citizenship behavior, customer satisfaction alone is insufficient to increase customer citizenship behavior. The study also shows that during the COVID-19 period, fast-food restaurants should have raised awareness of employees’ fair behaviors toward the customers and provided additional services to differentiate themselves in the market. Also, it indicates that customer expectations related to price, cleanliness and professional appearance of staff are not met after taking service.

No research has been found in the literature focusing on the expectations, justice, trust, satisfaction, loyalty and citizenship behaviors of fast-food restaurant customers in the COVID-19 pandemic process. Therefore, the results can fill the gap in relevant literature by testing the relationships between justice, trust, satisfaction, loyalty and citizenship during the pandemic and provide inferences for fast-food business owners.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

In this study, the authors provide a systematic literature review of articles in the emerging areas of green finance and discuss the status and challenges in sustainability disclosure, which is crucial for the efficiency of green financial instruments. The authors then review the literature on the economic implications of green finance and outline future research directions.

The authors use the analytical framework – Search, Appraisal, Synthesis, and Analysis (SALSA) to conduct the systematic review of the literature.

Increasing public attention to the environment motivates the use of green finance to fund environmentally sustainable projects, and the rise of green finance intensifies the demand for environmental disclosure. Literature has documented tremendous growth in sustainability reporting over time and around the globe, as well as raised concerns about how such reporting lack consistency, comparability, and assurance. Despite these challenges, the authors find that in general, the literature agrees that a firm’s green practice is positively associated with its financial performance and negatively related to a firm’s cost of capital. Green finance is also found to bring about enhanced risk management and economic development.

The authors provide one of the first reviews of green finance, sustainability disclosure and the impact of green finance on financial performance, capital market and economic development.

Recently, the discussion on the impact of the Internet of Things (IoT) in theory and in practice is increasing. While some proponent envisage that the IoT will bring about positive radical change in the modern society, others argue that the IoT will introduce more disadvantages in the long run (mainly in terms of job losses) than advantages. The purpose of this paper is to arbitrate this controversy by examining the impact of IoT on the Japanese society.

While previous studies have largely been qualitative in nature, in this study, a quantitative approach was used. A multi-dimensional analysis was carried out and the statistical method known as the one-way analysis of variance was used to process the data obtained during this study.

The results show that indeed the IoT has a positive impact on the daily lives of the Japanese people, however the change it brings are mainly incremental change and not radical. Furthermore, rather than reducing job opportunities, it has created more opportunities and simplified operation processes.

However, a limitation of this study is in its narrow scope. It is important to note that further studies on an international level or perhaps multi-national level is needed. Furthermore, there may be other underlining factors, such as culture, social, economic, geographical location, technology capacity, that may contribute to the impact of the IoT on daily life. Therefore, future research needs to verify if indeed this is the case.

This research successful arbitrates the argument about the impact of the IoT on the society by specifically showing that the advantages brought by the IoT out-ways its disadvantages. Furthermore, the uncertainty (fear of job losses) expressed by some experts was addressed in this study. The results obtained showed that the diffusion of the IoT has no correlation with job loss but rather supports improved working environment and creation of jobs.

Prior investigations concerning misalignment resulting from journal deformation typically relied on predefined misaligned angles. Nevertheless, scant attention has been devoted to the determination of these misaligned angles. Furthermore, existing studies commonly treat the journal as rigid under such circumstances. Therefore, the present study aims to introduce a framework for determining misaligned angles and to compare outcomes between rigid and flexible journal configurations.

The bearing forces are considered as an external load leading to journal deformation. This deformation is calculated using the finite element method. The pressure distribution producing the bearing force is solved using the finite difference method. The mesh grids in the finite element and finite difference methods are matched for coupling calculation. By iteration, the pressure distribution of the lubricant film at the equilibrium position is determined.

Results show that the deformation-induced misalignment has a significant influence on the performance of the bearing when the journal flexibility is taken into account. The parametric study reveals that the misalignment relies on system parameters such as bearing length-diameter ratio and static load.

The investigation of this work provides a quantification method of misalignment of hydrodynamic bearings considering the elastic deformation of the journal, which assists in the design of bearing in a rotor-bearing system.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0337/

In today’s digital economy, it is very important to cultivate digital professionals with advanced interdisciplinary skills. The purpose of this paper is that universities play a vital role in this effort, and research teams need to use the synergistic effect of various educational methods to improve the quality and efficiency of personnel training. For these teams, a powerful evaluation mechanism is very important to improve their innovation ability and the overall level of talents they cultivate. The policy of “selecting the best through public bidding” not only meets the multi-dimensional evaluation needs of contemporary research, but also conforms to the current atmosphere of evaluating scientific and technological talents.

Nonetheless, since its adoption, several challenges have emerged, including flawed project management systems, a mismatch between listed needs and actual core technological needs and a low rate of conversion of scientific achievements into practical outcomes. These issues are often traced back to overly simplistic evaluation methods for research teams. This paper reviews the literature on the “Open Bidding for Selecting the Best Candidates” policy and related evaluation mechanisms for research teams, identifying methodological shortcomings, a gap in exploring team collaboration and an oversight in team selection criteria.

It proposes a theoretical framework for the evaluation and selection mechanisms of research teams under the “Open Bidding for Selecting the Best Candidates” model, offering a solid foundation for further in-depth studies in this area.

Research progress on the Evaluation Mechanism of Scientific Research Teams in the Digital Economy Era from the Perspective of “Open Bidding for Selecting the Best Candidates.”

This paper presents a generic simulation model to determine the equipment mix (quay, yard and intra-terminal transfer) for a Container Terminal Logistics Operations System (CTLOS). The simulation model for the CTLOS, a typical type of discrete event dynamic system (DEDS), consists of three sub-models: ship queue, loading-unloading operations and yard-gate operations. The simulation model is empirically applied to phase 1 of the Yangshan Deep Water Port in Shanghai. This study considers different scenarios in terms of container throughput levels, equipment utilization rates, and operational bottlenecks, and presents a sensitivity analysis to evaluate and choose reasonable equipment ratio ranges under different operational conditions.

Milk is one of the most produced, consumed and protected agricultural commodities worldwide. The purpose of this paper is to assess how trade-opening policies can foster food security in the Chinese milk sector.

The empirical evidence proposed in our paper is based on time series data from the National Bureau of Statistics of China (2019) and FAOSTAT (2020). Differences in income elasticity between urban and rural areas are estimated by OLS regressions. The data also provide empirical evidence to assess to what extent and to which countries China is resorting to meet its growing demand.

Per-capita milk consumption of Chinese is rising. The authors’ estimates show that milk income elasticity is higher in rural areas. China is also progressively increasing its dependence on imports. Producers who benefit the most are those from countries implementing trade-opening policies.

Other methods could be applied, by way of example, the gravitational model.

Trade agreements and the removal of barriers could be effective responses to protectionist pressures and to food security concerns.

The case examined is of particular interest as it intervenes on food security and safety.

The paper adds value and evidence to the effects of trade on food security in a country with limited and exploited natural resources addressing a health emergency and environmental concerns.

Unlike conventional aircraft, birds can glide without a vertical tail. The purpose of this paper is to analyse the influence of dihedral angle spanwise distribution on lateral-directional dynamic stability by the simulation, calculation in the development of the bird-inspired aircraft and the flight testing.

The gliding magnificent frigatebird (Fregata magnificens) was selected as the study object. The geometric and mass model of the study object were developed. Stability derivatives and moments of inertia were obtained. The lateral-directional stability was assessed under different spanwise distributions of dihedral angle. A bird-inspired aircraft was developed, and a flight test was carried out to verify the analysed results.

The results show that spanwise distribution changing of dihedral angle has influence on the lateral-directional mode stability. All of the analysed configurations have convergent Dutch roll mode and rolling mode. The key role of dihedral angle changing is to achieve a convergent spiral mode. Flight test results show that the bird-inspired aircraft has a well-convergent Dutch roll mode.

The theory that birds can achieve its lateral-directional stability by changing its dihedral angle spanwise distribution may explain the stability mechanism of gliding birds.

This paper helps to improve the understanding of bird gliding stability mechanism and provides bio-inspired solutions in aircraft designing.