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This study aims to examine the ability of Generative Pre-trained Transformer 4 (GPT-4), one of the most powerful large language models, to generate a literature review for peer-reviewed journal publications. The objective is to determine whether business scholars can rely on GPT-4’s assistance with literature reviews and how the nature of human–artificial intelligence (AI) interaction may affect the quality of the reviews generated by GPT-4.

A survey of 30 experienced researchers was conducted to assess the quality of the literature reviews generated by GPT-4 in comparison with a human-authored literature review published in a Social Science Citation Index (SSCI) journal. The data collected were then analyzed with analysis of variance to ascertain whether we may trust GPT-4’s assistance in writing literature reviews.

The statistical analysis reveals that when a highly structured approach being used, GPT-4 can generate a high-quality review comparable to that found in an SSCI journal publication. However, when a less structured approach is used, the generated review lacks comprehensive understating and critical analysis, and is unable to identify literature gaps for future research, although it performed well in adequate synthesis and quality writing. The findings suggest that we may trust GPT-4 to generate literature reviews that align with the publication standards of a peer-reviewed journal when using a structured approach to human–AI interaction.

The findings suggest that we may trust GPT-4 to generate literature reviews that align with the publication standards of a peer-reviewed journal when using a structured approach to human–AI interaction. Nonetheless, cautions should be taken due to the limitations of this study discussed in the text.

By breaking down the specific tasks of a literature review and using a quantitative rather than qualitative assessment method, this study provides robust and more objective findings about the ability of GPT-4 to assist us with a very important research task. The findings of this study should enhance our understanding of how GPT-4 may change our research endeavor and how we may take a full advantage of the advancement in AI technology in the future research.

The paper aims to accurately measure the key motion parameters, such as velocity, azimuth and pitch angle, of the small flying object with a non-uniform curve trajectory. It proposes a measurement method and its calculation model of non-uniform curve trajectory using a photoelectric sensor array.

First, the basic composition of the measurement system and mechanism of photoelectric sensor array are described, respectively. Second, a non-uniform curve mathematical measurement model is constructed differently from the traditional linear trajectory, taking into account the influence of gravity and air resistance. Third, the measurement error of the system is analyzed through numerical simulation. Finally, the accuracy and feasibility of the approach are verified by live-ammunition experiments.

The results show that the systematic error of the hitting point coordinates can be reduced by 9% compared to the traditional linear measurement model. Consequently, this method can meet the higher measurement requirement for the key motion parameters of the small flying object under the non-uniform curve trajectory. Research limitations/implications (if applicable)- although the approach itself is generalizable, the method is unable to detect the motion parameters of multiple small flying objects.

Although the approach itself is generalizable, the method is unable to detect the motion parameters of the multiple small flying objects.

It is evident that the proposed non-uniform curve measurement model is more precise in quantifying the essential characteristics of the small flying object, particularly in consideration of the environmental conditions.

The precise measurement of the key motion parameters of the small flying object can facilitate the enhancement of the protective performance of protective materials.

A novel approach to measurement is proposed, which differs from the conventional uniform trajectory model. To this end, the space construction of the photoelectric sensor array is optimized. The number of the sensors is revised.

Aiming at the problem of insufficient adaptability of robot motion planners under the diversity of end-effector constraints, this paper proposes Transformation Cross-sampling Framework (TC-Framework) that enables the planner to adapt to different end-effector constraints.

This work presents a standard constraint methodology for representing end-effector constraints as a collection of constraint primitives. The constraint primitives are merged sequentially into the planner, and a unified constraint input interface and constraint module are added to the standard sampling-based planner framework. This approach enables the realization of a generic planner framework that avoids the need to build separate planners for different end-effector constraints.

Simulation tests have demonstrated that the planner based on TC-framework can adapt to various end-effector constraints. Physical experiments have also confirmed that the framework can be used in real robotic systems to perform autonomous operational tasks. The framework’s strong compatibility with constraints allows for generalization to other tasks without modifying the scheduler, significantly reducing the difficulty of robot deployment in task-diverse scenarios.

This paper proposes a unified constraint method based on constraint primitives to enhance the sampling-based planner. The planner can now adapt to different end effector constraints by opening up the input interface for constraints. A series of simulation tests were conducted to evaluate the TC-Framework-based planner, which demonstrated its ability to adapt to various end-effector constraints. Tests on a physical experimental system show that the framework allows the robot to perform various operational tasks without requiring modifications to the planner. This enhances the value of robots for applications in fields with diverse tasks.

The purpose of this paper is to investigate cutting-edge coagulant materials and procedures for the removal of harmful microplastics from the water.

Traditional methods of removing microplastics from water bodies, like filtration, face limitations due to the small sizes involved. Hence, coagulation and flocculation emerge as essential strategies to enhance filtration efficacy. This paper summarizes recent research on coagulant materials, including novel hybrids, for water purification. It also looks at the most recent improvements in coagulation and flocculation processes, as well as the factors that influence their efficiency.

This paper highlights recent research on coagulant materials, including novel hybrids, used in water purification. It also examines the most recent advancements in coagulation and flocculation procedures, as well as the elements influencing their effectiveness.

The environmental threat posed by plastics, especially in their non-naturally degradable forms, such as microplastics, has reached alarming proportions. These minute particles pervade our air, soil and water bodies, driven by various factors and sources. Their diminutive size, whether in micro or nano form, renders them ingestible by marine and freshwater organisms, as well as humans, posing significant health risks. Traditional methods of water cleaning are not effective in dealing with very small-sized plastics and hence this paper summarizes recent research on coagulant materials, including various novel hybrids, for water purification from tiny microplastics in detail.

Merchant guild culture derives from business practices associated with medieval and early modern merchant guilds. This study aims to investigate the nexus between merchant guild culture and firm internationalization as well as the factors that moderate this nexus.

Based on the distribution of the ten merchant guilds in China and data on Chinese listed companies, this study uses the geographical proximity-based method to measure the intensity of merchant guild culture, which is the nearest distance between the ten merchant guilds’ origins and each firm’s registered address.

This study provides robust evidence that merchant guild culture positively relates to the degree of firm internationalization. It also documents that this nexus is stronger for firms with overseas background executives and those situated in highly marketized regions.

The findings of this study have valuable implications for both governments and firms. Governments can leverage local cultures to promote the internationalization of domestic firms, particularly in emerging economies with rich cultural heritage. Firms can further enhance their internationalization efforts by hiring more executives with overseas backgrounds.

This study advances the imprinting literature, provides a novel perspective on the antecedents of firm internationalization and expands research on the contemporary value of historical business culture.