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Digital technology plays a vital role in empowering omnichannel integration. Research on digital technology has recently attracted attention and rapidly developed. However, a comprehensive assessment of the research status and potential gaps is yet to be conducted. Thus, this study investigated the current research status of digital technology-empowered omnichannel integration, and future research directions are proposed.

A three-stage bibliometric analysis was conducted on 764 articles published from 2000 to 2023, cited in the Web of Science database. Furthermore, performance and thematic analyses were performed.

The most productive contributors and influential articles in this field were identified, and four themes of focus were discovered: service quality, o2o commerce, omnichannel retailing, and digital transformation.

To the best of our knowledge, this work is the first attempt to enable researchers to understand the vast body of published scholarship on digital technology-empowered omnichannel integration.

In the dynamic landscape of the digital economy, companies are increasingly adopting omnichannel integration strategies to enhance customer experiences. However, the interplay between this strategy and digitalisation in fostering brand trust remains uncharted. Drawing on the social exchange and psychological reactance theories, this study ventures into unexplored territory by examining the impact of omnichannel integration and digital value on brand trust building. It also delves into the boundary roles of customers’ psychological perceptions, both positive (customer empowerment) and negative (privacy concerns and perceived deception), in this process.

This study conducted an online survey of 595 omnichannel users in China and validated the model using partial least squares structural equation modelling (PLS-SEM).

This study’s results have significant implications for businesses. They show that customer perception of omnichannel integration and perceived digital value are critical drivers of omnichannel brand trust, with customer empowerment playing a mediating role. Notably, the study also reveals that customers’ negative psychological perceptions can have different moderating effects, highlighting the need for businesses to address these concerns in their omnichannel strategies.

This study breaks new ground in marketing research by highlighting the benefits of omnichannel integration and incorporating digital perspectives. It demonstrates the positive impact of blending customer perception of omnichannel integration and perceived digital value on brand trust formation. Furthermore, it explores the boundary roles of customers’ psychological perceptions in this process, offering a unique and comprehensive perspective.

Graphene is a two-dimensional material. Its use has many advantages in gas sensing, but its long desorption process is problematic. The aim of this paper is to design a graphene-based gas sensor, study the response to NO₂ gas concentrations and find ways to accelerate the desorption process.

In one group, the sensor was placed in air to measure its initial resistance. Then, it was exposed to the NO₂ gas at a certain concentration. Finally, the sensor was exposed to light immediately after NO₂ gas exposure was ended. In another group, the sensor was heated using a heating plate at a stable temperature, before taking the measurements. Then the adsorption and desorption experiments were carried on.

Illumination and heating at a suitable temperature can expedite desorption of NO₂ molecules on graphene.

In the paper, two main methods are introduced to accelerate the desorption process when the NO₂ gas is absorbed on graphene. Through a series of experiments and analysis, the authors found that the recovery time could be reduced observably and the recovery performance of the graphene-based NO₂ sensor could be improved effectively.

To improve the problems as the heavy burden of sewage treatment and environmental pollution caused by the traditional sodium hydrosulfite reduction dyeing of indigo, this study aims to carry out the direct electrochemical reduction dyeing for indigo with the eco-friendly Cu(II)/sodium borohydride reduction system under normal temperature and pressure conditions.

The electrochemical behavior of Cu(II)/sodium borohydride reduction system was investigated by cyclic voltammetry. And, the dyeing performance of the Cu(II)/sodium borohydride reduction system was developed by optimizing the concentration of copper sulfate in the anode electrolyte, applied voltage and reduction time via single-factor and orthogonal integrated analysis.

The dyeing performance of the Cu(II)/sodium borohydride reduction system is superior to that of the traditional reduction dyeing with sodium hydrosulfite. In the case of the optimized condition, the soaping fastness and dry/wet rubbing fastness of the dyed fabric in the two reduction dyeing processes were basically comparable, the K/S value of electrocatalytic reduction of indigo by Cu(II)/NaBH4 is 11.81, which is higher than that obtained by traditional sodium hydrosulfite reduction dyeing of indigo.

The innovative electrocatalytic reduction system applied herein uses sodium borohydride as the hydrogen source combined with Cu(II) complex as the catalyst, which can serve as a medium for electron transfer and active the dye molecule to make it easier to be reduced. The electrochemical dyeing strategy presented here provides a new idea to improve the reduction dyeing performance of indigo by sodium borohydride.

Nowadays, the construction of lifelong education system has become the common trend of educational development in many countries. In China, credit accumulation and transfer as one of the effective measures to promote the lifelong education system was proposed in the National Medium and Long-term Educational Reform and Development Plan (2010 – 2020). It certainly poses a new opportunity and challenge to open universities in China, most of which are in transition from TV and radio universities and expected to play more important roles in the construction of lifelong education system in China. The paper presents the initial research and practice of Shanghai Academic Credit Transfer and Accumulation Bank for Lifelong Education (SHCB), which is led by Shanghai Municipal Education Commission and operated by Shanghai Open University as one of the initiatives of open universities in China since 2010. Focusing on continuing education for Shanghai citizens and cooperating with other universities and related institutions, SHCB has been established with the organisational structure, accreditation criteria for credits, credit accumulation and transfer system, learners' learning portfolios, technology service platform, and the detailed operating mode. By now, accreditation criteria of learner's credits of 166 courses and 139 non-degree certificates, and recognition of 541 non-degree certificates and 1549 leisure courses have been completed. SHCB has been open to the public from 24 July, 2002 to promote the exchange and transfer among the academic education, even between academic education and non-academic education, and ultimately promote the construction of the lifelong education system in Shanghai.

Based on a dyadic perspective, the purpose of this paper is to include the contributions of employee and customer in a service process and to examine the underlying mechanism of customer organization socialization on service performance.

The authors used a unique survey data pertaining to the service industry. The authors collected their data from multiple sources (customers, front-line employees and these employees' managers) in the divisions of a large service organization – Ping An Insurance (Group) Company of China. The authors adopted hierarchical regression moderated path analysis approach to examine our moderated mediation model.

The authors find that both the quality of customer service and the quality of employee service play as moderators in the relationship between customer organization socialization and service performance. And quality of customer service moderates the relationship between customer organization socialization and quality of employee service.

The literature has focused primarily on service performance improvement based on the dyadic perspective of customer and employee. The research develops a moderated mediation model and contributes to the literature by empirically examining customer organization socialization.

At present, the scale of China's floating population has reached 376 million people. Compared with the local inhabitants, the poverty problem of the floating population is more complex, and this problem should also attract the attention of all sectors of society. This paper aims to measure and analyze the multidimensional poverty of the floating population in China.

The data used in this paper are the data of the China Migrants Dynamic Survey (CMDS) in China. This survey is a large-scale national migratory population sampling survey organized by the China National Health Commission, covering 31 provinces (autonomous regions and cities) and other autonomous regions. This paper uses the dynamic monitoring and Alkire and Foster (A-F) method to study the multidimensional poverty problem of the floating population.

This study finds that income poverty is no longer the main type of poverty faced by the floating population. The multidimensional poverty of the floating population mainly occurs in the social security and education dimensions, of which social security has become the most severe poverty dimension of the floating population. From the perspective of group differences, compared with the floating population in urban areas, the multidimensional poverty of migrant workers is more serious. However, the poverty of migrant workers is mainly concentrated in one-dimensional poverty and two-dimensional poverty.

In the future, the authors should focus on the social security of the floating population in the place of influx and the education of the floating population.

Through the review of the existing literature, the authors find that the current research on the multidimensional poverty of the floating population is mainly concentrated on the migrant worker groups that move from rural areas to urban areas. However, insufficient attention is paid to the urban floating population groups moving between cities.

To the best of the authors’ knowledge, this study is the first to investigate the intricate relationship between crude oil spot and futures prices, focusing on both cointegration and market efficiency during the COVID-19 pandemic, and the beginning of the Russia–Ukraine conflict. Using daily West Texas Intermediate data from January 2020 to March 2024, like Cunado and Pérez de Gracia (2003), the authors use advanced statistical methods to identify structural breaks and assess cointegration levels. Linear and nonlinear Granger causality tests are used to reveal underlying dynamics.

This paper uses the Lagrange Multiplier test by Arai and Kurozumi (2007) to check for cointegration with various shifts in crude oil spot and futures markets. The two-step procedure by Kejriwal and Perron (2010) and Kejriwal et al. (2022) is then applied to assess partial parameter stability in cointegration models. Efficiency is examined using both bivariate and trivariate models based on non-arbitrage and expectations hypotheses. Finally, causality is analyzed with the vector error correction model for linear Granger causality, and the tests by Bai et al. (2018) and Diks and Panchenko (2006) for nonlinear causality.

The analysis reveals that futures prices generally lead spot prices through both linear and nonlinear causality during certain periods, while only linear causality is present in others. This inconsistency suggests fluctuating market efficiency and potential arbitrage opportunities. Structural breaks indicate that the equilibrium between spot and futures prices adjusts in response to significant events like the COVID-19 pandemic and the Russia–Ukraine war. The study identifies specific periods, particularly between January 2020 and March 2024, where both linear and nonlinear forecasting between futures and spot oil prices are effective, highlighting the dynamic nature of their relationship.

Despite extensive efforts, pinpointing the exact break date for COVID-19 remains challenging due to limitations in the data set and methodology. Additionally, the analysis of the Russia–Ukraine conflict is still ongoing. These challenges highlight the complexity of addressing structural breaks linked to unprecedented events.

The findings offer valuable insights for both academia and industry practitioners. The study reveals potential arbitrage opportunities stemming from inconsistent market efficiency and fluctuating causality between futures and spot prices, allowing traders to optimize their trades and timing. It also enhances risk management by identifying when linear and nonlinear causality is most effective. Policymakers can use these insights to evaluate market stability, especially during major disruptions such as the COVID-19 pandemic and geopolitical conflicts, guiding regulatory decisions. Furthermore, the study highlights the importance for investors to adjust their strategies in response to structural breaks and evolving market conditions.

This study’s social implications are diverse, extending beyond finance and academia. It influences economic stability by revealing inefficiencies and arbitrage opportunities in crude oil markets, aiding better resource allocation. Enhanced transparency benefits stakeholders, promoting fair market practices and consumer protection. Policymakers can refine regulations based on identified structural breaks, ensuring market stability. The study indirectly impacts environmental discussions by examining crude oil’s link to global energy consumption. Financially, it guides investment strategies, influencing resource distribution and the broader economy. Additionally, its educational contribution stimulates academic discourse, fostering growth in energy economics and financial market knowledge, shaping future research.

The originality and value of this paper lie in its comprehensive examination of the dynamic relationship between futures and spot oil prices, particularly through both linear and nonlinear causality across different periods. By identifying and analyzing periods of both linear and nonlinear causality, the study uncovers fluctuating market efficiency and potential arbitrage opportunities that are not typically addressed in conventional analyses. Additionally, the paper’s focus on the impact of significant global events, such as the COVID-19 pandemic and the Russia–Ukraine war, on the equilibrium between spot and futures prices offers a novel perspective on how structural breaks influence market dynamics. This nuanced understanding enhances both theoretical and practical knowledge, offering valuable insights for traders, investors and policymakers to navigate and respond to evolving market conditions.

This paper proposes an intelligent fault diagnosis method, which aims to obtain the outstanding fault diagnosis results of the gearbox.

An intelligent fault diagnosis method based on energy entropy-weighted complementary ensemble empirical mode decomposition (EWCEEMD) and support vector machine (SVM) optimized by whale optimization algorithm (WOA) is proposed. The raw signal is first denoised by the wavelet noise reduction method. Then, complementary ensemble empirical mode decomposition (CEEMD) is used to generate several intrinsic mode functions (IMFs). Next, energy entropy is used as an indicator to measure the sensibility of the IMF and converted into a weight coefficient by function. After that, IMFs are linearly weighted to form the reconstruction signal, and several features are extracted from the new signal. Finally, the support vector machine optimized by the whale optimization algorithm (WOA-SVM) model is used for gearbox fault classification using feature vectors.

The fault features extracted by this method have a better clustering effect and clear boundaries under each fault mode than the unimproved method. At the same time, the accuracy of fault diagnosis is greatly improved.

In most studies of fault diagnosis, the sensitivity of IMF has not been appreciated. In this paper, energy entropy is chosen to quantify sensitivity. In addition, high classification accuracy can be achieved by applying WOA-SVM as the final classification model, improving the efficiency of fault diagnosis as well.

The purpose of this paper is to explore the impact of product information on impulse purchases in a cross-border electronic commerce (CBEC) setting from the perspective of cue stimulation.

This study proposes a research model of impulse purchases in CBEC based on the cue utilization theory and Stimulus-Organism-Response (S-O-R) model. The research model was tested using covariance-based structural equation modelling. Data were collected from the consumers of a popular CBEC platform in China.

A high-quality product description has a significant positive effect on concentration but not on curiosity and autotelic experience. A high-quality product display has a significant positive effect on concentration, curiosity and autotelic experience. High-quality product content has a significant positive effect on curiosity and autotelic experience but not on concentration. Curiosity and autotelic experience both have a significant positive effect on impulse purchases; however, concentration has no such effect on an impulse purchase. Curiosity and autotelic experience have a full mediation effect between product display and impulse purchases and between product content and impulse purchases, respectively.

This study integrates the S-O-R model and cue utilization theory to construct a theoretical model of product information-flow experience-impulse purchases. According to the model, we can understand how product information influences consumers' impulse purchases in CBEC.