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The purpose of this paper is to report the investigations on the potential of a new evolutionary algorithm based on probabilistic models – the quantum-inspired evolutionary algorithm (QEA) in solving inverse problems.

An improved QEA.

The proposed algorithm is an efficient and robust global optimizer for solving inverse problems.

To enhance the convergence speed without compromising the diversity performances of the populations, a new definition of global information sharing is introduced and implemented. To guarantee the balance between exploration and exploitation searches, a different migration strategy and formula, as well as a novel formulation for adaptively updating the rotation angle, are developed.

This paper delves into cross-border E-business, unraveling its intricate dynamics and forecasting its future trajectory.

This paper projects the prospective market size of cross-border E-business in China for the year 2023 using the GM (1,1) gray forecasting model. Furthermore, to enhance the analysis, the paper attempts to simulate and forecast the size of China’s cross-border E-business sector using the GM (1,3) gray model. This extended model considers not only the historical trends of cross-border E-business but also the growth patterns of GDP and the digital economy.

The forecast indicates a market size of 18,760 to 18,934 billion RMB in 2023, aligning with the consistent growth observed in previous years. This suggests a sustained positive trajectory for cross-border E-business.

Cross-border e-commerce critically shapes China’s global integration and traditional industry development. The research in this paper provides insights beyond statistical trends, contributing to a nuanced understanding of the pivotal role played by cross-border e-commerce in shaping China’s economic future.

This study aims to examine whether indirect customer-to-customer interactions (CCI) affect consumers’ behavioral intentions and how that effect is generated. It also explores the effect of dining experience on customer behavioral intentions and how that effect varies by party type.

The research consists of an experimental survey-based study of n = 491 real-world consumers from a marketing research panel. Structural equation models are analyzed to examine hypothesized relationships.

Indirect CCIs significantly affect all five dimensions of experiential value. Food and beverage (F&B) excellence, aesthetics and service excellence positively affect customer revisit intentions and word-of-mouth intentions via restaurant image. Furthermore, party type moderates the effect of aesthetics on behavioral intentions so that the effect is significant for the social diner group only. Customer return on investment and playfulness show non-significant impacts on behavioral intentions.

Managers should be aware that indirect CCIs influence all aspects of the restaurant experience. Since F&B excellence, aesthetics and service excellence affect restaurant image and behavioral intentions, management can operationalize these elements of service. The impact of aesthetics differs by consumers’ party type, enabling management to create unique servicescapes based on their target customer segment.

The study pioneers an investigation of how indirect CCI is associated with behavioral intentions through the mediating effects of experiential value and restaurant image. It contributes to the literature by examining how the impact of diners’ experiences differs by party type.

The purpose of this paper is to analyze the results of recording electrophysiological signals by nanosensors during tests on volunteers using neutral questions and questions that cause excitement.

The nanosensor-based hardware and software complex (HSC) was used for simultaneous recording of electrocardiogram, electroencephalogram and galvanic skin response during tests on volunteers using neutral questions and questions that cause excitement. The recording was carried out in real time without averaging and filtering in the extended frequency range from 0 to 10,000 Hz, level of more than 1 µV and sampling frequency equal to 64 kHz.

For the first time, the following signals were recorded by nanosensors without filtering and averaging in the measuring channels: real-time micropotentials on an electrocardiogram with a duration of 0.2 ms and a level of 1 µV or more. Also, for the first time, changes in the shape and amplitude of the P wave, slow waves on the electroencephalography (EEG), high impulse activity of the EEG and impulse activity of short duration on the GSR were recorded in response to questions that cause excitement.

The obtained results will be used for high-resolution equipment to develop additional measuring channels in existing types of equipment for psychophysiological studies.

For the first time, new data undistorted by filters was obtained on the amplitude and time parameters of electrophysiological signals in the frequency range from 0 to 10,000 Hz in response to questions that cause excitement, which was due to high sensitivity and noise immunity of nanosensors in comparison with existing electrodes for biopotential recording.

This study systematically reviewed pricing research published in leading marketing and hospitality and tourism (H&T) journals between 2010 and 2019. It attempts to concretize the understanding of the evolving patterns of pricing research in both fields and suggests an agenda for future research in H&T.

This study performed keyword co-occurrence analyses and co-citation analyses on the bibliographic data of 575 articles from marketing and H&T journals. Content analysis was applied to investigate the emerged topics in H&T.

The marketing discipline showed a persistent focus on research themes including price promotion, reference price, price fairness and pricing strategy. The H&T domain experienced a significant content enrichment of preexistent research topics. H&T scholars showed a growing interest in studying pricing for sharing economy accommodations and the interplay between pricing and electronic word-of-mouth. While marketing research applied theories from multiple disciplines as the theoretical foundations, H&T studies adopted the hedonic pricing model as an overarching theory.

Future pricing research in H&T may incorporate theories from other disciplines such as psychology, sociology and anthropology to broaden the scope of the study. Besides, innovative study designs and complex data analysis techniques should be encouraged. Topicwise, H&T scholars can dive deeper into price promotion and distribution channel price management.

This is the first study consolidating the pricing literature in H&T and marketing. It also suggests the potential research directions for researchers.

The purpose of this paper is twofold. First, the study examines the prolonged effect of policy-related economic uncertainty on hotel operating performance, particularly the room demand (occupancy). Second, the study attempts to explain why occupancy drops when the perceived economic uncertainty is high by studying the mediating effect of consumer sentiment in the relationship between economic policy uncertainty and hotel demand.

This quantitative study uses secondary data – US economic policy uncertainty (EPU) index, University of Michigan's index of consumer sentiment (ICS), and property-level hotel operating data from three states of the US – California, Florida and New York. Data were analyzed using random effect regression and structural equation modeling. Robustness tests were conducted to enhance the reliability of the research findings.

Random-effects regression analysis reveals that policy-related economic uncertainty has a negative and lead-lag effect on hotel occupancy, average daily rate and revenue per available room (RevPAR). Structural equation modeling results show that the relationship between economic policy uncertainty and hotel occupancy is significantly mediated by consumer sentiment. Robustness test results support the findings from the main analysis.

This study offers valuable implications for the hotel professionals in regard to anticipating the economic impact of policy-related uncertainty on hotel industry and understanding how consumer sentiment affects demand at such crises times. Moreover, the study suggests potential course of actions to deal with declining room demand at times of uncertainty.

This empirical study explores how economic policy uncertainty affects hotel performance at the property level and explains the mediating effect of consumer sentiment on hotel room demand. The study provides a first-hand evidence of how consumer sentiment relates to the perception of economic uncertainty and leads to decline in consumer demand. In that regard, findings of the study have valuable implications for hospitality industry practitioners and relevant policymakers.

The purpose of this paper is to propose an approach for conceptualizing science based on collaboration and competences of researchers.

The research is conducted by exploratory analysis of collaboration and competences using case studies from humanistic, engineering, natural sciences and a general topic.

The findings show that by applying the proposed approach on bibliographic data that readily exist for many national sciences as well as for international scientific communities, one can obtain useful new insights into the research. The approach is demonstrated with the following exploratory findings: identification of important connections and individual researchers that connect the community of anthropologists; collaboration of technical scientists in the community of anthropologists caused by an interdisciplinary research project; connectivity, interdisciplinary and structure of artificial intelligence, nanotechnology and a community based on a general topic; and identifying research interest shift described with concretization and topic-shift.

As demonstrated with the practical implementation (http://scienceatlas.ijs.si/), users can obtain information of the most relevant competences of a researcher and his most important collaborators. It is possible to obtaining researchers, community structure and competences of an arbitrary research topic.

The map for collaboration and competences of a complete science can be a crucial tool for policy-making. Social scientists can use the results of the proposed approach to better understand and direct the development of science.

Originality and value of the paper is in combining text (competences) and network (research collaboration and co-authoring) approaches for exploring science. Additional values give the results of analysis that demonstrate the approach.

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature. Furthermore, this research aims to identify research gaps and propose future research opportunities.

The bibliometric analysis was performed. Scopus database was used as the source of the literature. This study selected and analyzed 297 AV acceptance papers. The performance and science mapping analysis were performed.

The developed countries tended to dominate the topic. The publication outlet tended to be in transportation or technology journals. There were four research themes in existing literature. Technology acceptance model (TAM) and UTAUT2 tended to be used for explaining AV acceptance. AV acceptance studies tended to use two types of psychological concepts for understanding AV acceptance, namely risk related concepts and functional utilitarian benefit related concepts. In the context of research design, quantitative approach tended to be used. Self-driving feature was the most exploited feature of AV in the existing literature. Three research gaps were mapped and future research opportunities were proposed.

This paper provided a comprehensive information that allowed scientists to develop future research on AV acceptance.

There is lack of paper that discussed the bibliometric characteristics of AV acceptance literature. This paper fulfilled the gap.