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In the practice of live streaming e-commerce, the consumer demand is usually uncertain, and the inventory and prices can be decided by brand owners or streamers. To this end, this study examines the inventory and pricing decisions of the brand owner and streamer in a live streaming e-commerce supply chain under demand uncertainty.

In this study, four scenarios are considered, i.e. the brand owner determines the inventory and price (Scenario BB), the brand owner determines the inventory and the streamer determines the price (Scenario BS), the streamer determines the inventory and the brand owner determines the price (Scenario SB), and the streamer determines the inventory and price (Scenario SS).

The results show that the inventory and prices, as well as the profits of the brand owner and streamer increase with the consumer sensitivity to streamer’s sales effort level under the four scenarios. The inventory (price) is the highest under Scenario SS (SB), while that is the lowest under Scenario BB (BS). In addition, when the sensitivity is low, the brand owner’s profit is the highest under Scenario BB, otherwise, the profit is the highest under Scenario SS. Regardless of the sensitivity, the streamer’s profit is always the highest under Scenario SS.

Few studies focused on the inventory and pricing decisions of brand owners and streamers in live streaming e-commerce supply chains under demand uncertainty, while this work bridges the research gap. This study can provide theoretical basis and decision support for brand owners and streamers.

This chapter examines which coping mechanisms citizens used during the pandemic and how these mechanisms related to overall well-being. Using the Transaction Theory of Stress and Coping to frame the analysis, the chapter investigates predictive factors for various coping strategies and identifies which groups were more likely to use adaptive as opposed to maladaptive strategies. I examine how coping strategies used in April 2020 predict change in well-being, measured by life satisfaction, in November 2020. Americans reported greater use of maladaptive coping and less use of the adaptive coping strategies compared to their Finnish counterparts. Americans reported more frequent use of religious coping strategies. Interestingly, worrying about COVID-19 did not increase the use of maladaptive coping for Finns or Americans. Regarding the effect of the coping strategies on life satisfaction, the analyses revealed that those who reported using maladaptive strategies in April 2020 showed a significant decrease in life satisfaction in November 2020. However, this finding was only significant for Finnish residents. Unexpectedly, Finnish and US residents who reported using Active/Expressive and Planning coping reported a decrease in life satisfaction from April to November 2020. Finally, Finnish and US residents who were married, had higher self-esteem, or had higher social capital were more likely to report an increase in life satisfaction from April 2020 to November 2020. These findings raise questions for future research. The context of the pandemic may have created a unique situation that rendered coping mechanisms to behave in unusual ways.

The purpose of this study is to develop a new hybrid method that combines interpretative structural modeling (ISM) and matrix cross-impact multiplication applied to classification (MICMAC) to investigate the influencing factors of sustainable infrastructure vulnerability (SIV).

(1) Literature review and case study were used to identify the possible influencing factors; (2) a semi-structured interview was conducted to identify representative factors and the interrelationships among influencing factors; (3) ISM was adopted to identify the hierarchical structure of factors; (4) MICMAC was used to analyze the driving power (DRP) and dependence power (DEP) of each factor and (5) Semi-structured interview was used to propose strategies for overcoming SIV.

Results indicate that (1) 18 representative factors related to SIV were identified; (2) the relationship between these factors was divided into a five-layer hierarchical structure. The 18 representative factors were divided into driving factors, dependent factors, linkage factors and independent factors and (3) 12 strategies were presented to address the negative effects of these factors.

The findings illustrate the factors influencing SIV and their hierarchical structures, which can benefit the stakeholders and practitioners of an infrastructure project by encouraging them to take effective countermeasures to deal with related SIVs.

The bridge expansion joint (BEJ) is a key device for accommodating spatial displacement at the beam end, and for providing vertical support for running trains passing over the gap between the main bridge and the approach bridge. For long-span railway bridges, it must also be coordinated with rail expansion joint (REJ), which is necessary to accommodate the expansion and contraction of, and reducing longitudinal stress in, the rails. The main aim of this study is to present analysis of recent developments in the research and application of BEJs in high-speed railway (HSR) long-span bridges in China, and to propose a performance-based integral design method for BEJs used with REJs, from both theoretical and engineering perspectives.

The study first presents a summary on the application and maintenance of BEJs in HSR long-span bridges in China representing an overview of their state of development. Results of a survey of typical BEJ faults were analyzed, and field testing was conducted on a railway cable-stayed bridge in order to obtain information on the major mechanical characteristics of its BEJ under train load. Based on the above, a performance-based integral design method for BEJs with maximum expansion range 1600 mm (±800 mm), was proposed, covering all stages from overall conceptual design to consideration of detailed structural design issues. The performance of the novel BEJ design thus derived was then verified via theoretical analysis under different scenarios, full-scale model testing, and field testing and commissioning.

Two major types of BEJs, deck-type and through-type, are used in HSR long-span bridges in China. Typical BEJ faults were found to mainly include skewness of steel sleepers at the bridge gap, abnormally large longitudinal frictional resistance, and flexural deformation of the scissor mechanisms. These faults influence BEJ functioning, and thus adversely affect track quality and train running performance at the beam end. Due to their simple and integral structure, deck-type BEJs with expansion range 1200 mm (± 600 mm) or less have been favored as a solution offering improved operational conditions, and have emerged as a standard design. However, when the expansion range exceeds the above-mentioned value, special design work becomes necessary. Therefore, based on engineering practice, a performance-based integral design method for BEJs used with REJs was proposed, taking into account four major categories of performance requirements, i.e., mechanical characteristics, train running quality, durability and insulation performance. Overall BEJ design must mainly consider component strength and the overall stiffness of BEJ; the latter factor in particular has a decisive influence on train running performance at the beam end. Detailed BEJ structural design must stress minimization of the frictional resistance of its sliding surface. The static and dynamic performance of the newly-designed BEJ with expansion range 1600 mm have been confirmed to be satisfactory, via numerical simulation, full-scale model testing, and field testing and commissioning.

This research provides a broad overview of the status of BEJs with large expansion range in HSR long-span bridges in China, along with novel insights into their design.

This paper aims to explore augmented reality (AR) applications in construction safety academic literature and propose possible improvements for future scholarly works. The paper explicitly focuses on AR integration with Construction 4.0 technologies as an effective solution to safety concerns in the construction industry.

This study applied a systematic review approach. In total, 387 potentially relevant articles from databases were identified. Once filtering criteria were applied, 29 eligible papers where selected. The inclusion criteria were being directly associated with construction safety focused on an AR application and AR interactions associated with the Construction 4.0 technologies.

This study investigated the structure of AR applications in construction safety. To this end, the authors studied the safety purposes of AR applications in construction safety: pre-event (intelligent operation, training, safety inspection and hazard alerting), during-event (pinpointing hazard) and post-event (safety estimation) applications. Then, the integration of AR with Construction 4.0 technologies was elaborated. The systematic review also revealed that the AR integration has contributed to developing several technical aspects of AR technology: display, tracking and human–computer interaction. The study results indicate that AR integration with construction is effective in mitigating safety concerns; however, further research studies are required to support this statement.

This study contributes to exploring applications and integrations of AR into construction safety in order to facilitate the leverage of this technology. This review can help encourage practitioners and researchers to conduct further academic investigations into AR application in construction safety.

National spirit, as a powerful legitimacy trait, shapes the consistency of a firm’s financial decisions, employee engagement and sustainability strategies. Combining this with resource-based view (RBV) theory, the study empirically examines the dual impact of national spirit on corporate environmental, social and governance (ESG) performance.

This paper utilizes data from Chinese A-share listed companies from 2009 to 2022 and employs machine learning methods to construct enterprise-level indicators of national spirit. In addition, the paper scrapes nearly 3 million ESG-related online news articles from the Baidu news website and uses machine learning methods to measure media ESG attention and sentiment.

The findings reveal that national spirit significantly enhances corporate ESG performance, operating through both internal and external channels: promoting social financing and boosting employee morale. Further analysis indicates that the positive influence of national spirit on corporate ESG performance is more pronounced in private enterprises, companies facing higher levels of credit constraints and firms in polluting industries. Additionally, managerial shortsightedness weakens the sustainable value of national spirit, while external media ESG attention and regional ESG governance efforts further strengthen this effect. Furthermore, different dimensions of national spirit exhibit varying impacts on corporate ESG performance.

This study provides new insights for promoting sustainable development systems in emerging economies and understanding the role of national spirit in corporate social responsibility investments.

This paper shifts the study of national spirit from macro-level cultural analyses to a micro-level perspective. It bridges gaps in the literature by providing empirical evidence on the role of national spirit as a soft resource that influences corporate financial behavior and employee morale. This study provides new insights into promoting sustainable development systems in emerging economies and understanding the role of national spirit in corporate social responsibility investments.

This study aims to investigate the effect of brand authenticity on consumer brand loyalty in the Pakistani frozen food industry sector in the light of the stimulus-organism-response (SOR) theory.

The quantitative approach utilized a survey questionnaire to acquire customers’ perceptions. A simple random technique was used to collect data. About 255 questionnaires were analysed, and the response rate was 72.86%. The measurement and structural model were constructed through Smart PLS-4 and fsQCA.

The findings indicated that brand authenticity positively affects brand loyalty in the Pakistani frozen food industry. Results further proved that brand involvement has a full mediation effect, fsQCA supports the same results, and customer satisfaction has a partial mediation effect. These findings offer valuable insights into the frozen food industry in Pakistan and other countries, allowing them to create successful tactics to engage customers and foster brand loyalty. The findings reveal the complexity and ever-changing nature of how consumers assess brand authenticity in the frozen food industry.

These findings also have implications for the frozen food business’s marketing and brand positioning strategies, particularly its utilization of brand authenticity to attract and retain consumers.

This is the first paper in the frozen food sector from the perspective of brand authenticity.

This study explores the potential of artificial intelligence (AI) in fostering sustainable entrepreneurship within the tourism industry. The rapid growth of the tourism sector has raised concerns regarding its environmental impact, social equity and economic sustainability. Sustainable entrepreneurship offers a promising approach to address these challenges by integrating environmental, social and economic considerations into business practices. AI technologies, with their ability to process vast amounts of data, analyse patterns and make predictions, have the potential to support sustainable entrepreneurship initiatives in the tourism industry. By analysing the current literature, this study provides insights into the effective utilisation of AI to promote sustainable entrepreneurship in the tourism industry, while acknowledging the need for responsible and ethical AI implementation. The findings contribute to the understanding of how AI can be harnessed as a tool for driving sustainable practices and innovation in the tourism sector, ultimately leading to a more sustainable and responsible tourism industry.

This study aims to investigate the differences in consumer reviews across multiple e-commerce platforms to better assist consumers in making informed decisions. By examining the specific content of these differentiated reviews, the study seeks to provide insights that can enhance e-commerce services and improve consumer satisfaction.

The research utilizes the latent Dirichlet allocation (LDA) method for text analysis to identify the varying concerns of consumers across different e-commerce platforms for the same product. Additionally, the study expands the sentiment dictionary to address polysemy issues, allowing for a more precise capture of sentiment differences among consumers. A non-parametric test is employed to compare reviews across multiple platforms, providing a comprehensive analysis of review disparities.

The findings reveal that consumer concerns and sentiments vary significantly across different e-commerce platforms, even for the same product. The combination of text analysis and non-parametric testing highlights the objectivity of the research, offering valuable evidence and recommendations for improving e-commerce services and enhancing the shopping experience.

This study is original in its approach to combining text analysis with non-parametric testing to examine multi-platform review differences. The research not only contributes to the understanding of consumer behavior in the context of e-commerce but also provides practical suggestions for platforms and consumers, aiming to optimize service quality and consumer satisfaction.