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The authors investigated the factors influencing consumer evaluations of advertisements for ethical luxury products that incorporate animal rights and protection concerns. The authors empirically examined how ethical messages influence advertisement persuasiveness through ethical consumer guilt and positively impact consumer evaluations of ethical luxury products. Furthermore, the authors explored the moderating role of consumers’ independent versus interdependent self-construals.

The authors conducted four experimental studies on the interplay among ethicality, luxury brand positioning and self-construal. Moderated mediation analyses revealed that moral emotions were responsible for the effect of ethical luxury advertisements that address animal welfare on brand attitude.

Advertisement messages signaling a luxury brand’s ethical efforts increase empathy through ethical consumer guilt, thereby generating favorable attitudes toward luxury products. However, this effect is limited to consumers with independent self-construal in South Korea and the United States of America.

The authors offer novel insights into the roles of ethical consumer guilt and empathy in the positive effects of ethical messages from luxury brands. Furthermore, the authors identified brand type and self-construal as boundary conditions for the effects observed across different consumer groups and markets.

While COVID-19 mitigation measures (CMMs) aided in steady recovery during the pandemic, they also impeded movement across economies/borders, affecting quality assurance (QA) of Cross-border Construction Logistics and Supply Chain (Cb-CLSC). However, prior studies on the pandemic in the construction project industry have not revealed how CMMs have impacted QA. Thus, this study aims to evaluate the impact of the CMMs on the QA of Cb-CLSC.

This is achieved by adopting an embedded mixed-method approach involving a desk literature review and engaging 150 experts from different economies across the globe using expert surveys, and results verified via semi-structured expert interviews. Structural equation modelling-based multiple regression analysis (SEM-MRA) was integrated to examine the impact of the CMMs on the QA, along with descriptive and content analysis.

The study confirmed that CMMs have not only impacted the QA negatively but also influenced the positioning of the QA for the post-pandemic era and probably to survive the risks of future pandemics. Among all the identified CMMs, the top three critical measures include “lockdown (CMM2)”, “use of personal protective equipment, such as nose masks, disinfects, etc. (CMM5)”, and “electronic/virtual meetings (CMM7)”. However, CMM5 possesses the highest contributory power to form CMM in impacting the QA, and this can be regarded as largely positive by strengthening health and safety management systems. Its negative impact lies with the project cost increment and the inconveniences of using nose and face masks.

This study provides a better understanding to construction practitioners and policy makers on how the pandemic policies, i.e. CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics.

The study contributes to knowledge in that it provides a better understanding of how the pandemic policies, such as CMMs, have impacted QA and can aid in formulating planning and operational decisions to adequately position the QA for the post-pandemic era and to endure the risks of future pandemics. This area of study has been given limited attention among prior studies during the pandemic.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.

To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.

The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.

The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.

We explore the driving forces behind the channel choices of the manufacturer and the platform by considering asymmetric selling cost and demand information.

This paper develops game-theoretical models to study different channel strategies for an E-commerce supply chain, in which a manufacturer distributes products through a platform that may operate in either the marketplace channel or the reseller channel.

Three primary models are built and analyzed. The comparison results show that the platform would share demand information in the reseller channel only if the service cost performance is relatively high. Besides, with an increasing selling cost, the equilibrium channel might shift from the marketplace to the reseller. With increasing information accuracy, the manufacturer tends to select the marketplace channel, while the platform tends to select the reseller channel if the service cost performance is low and tends to select the marketplace channel otherwise.

All these results have been numerically verified in the experiments. At last, we also resort to numerical study and find that as the service cost performance increases, the equilibrium channel may shift from the reseller channel to the marketplace channel. These results provide managerial guidance to online platforms and manufacturers regarding strategic decisions on channel management.

Although prior research has paid extensive attention to the driving forces behind the online channel choice between marketplace and reseller, there is at present few study considering the case where a manufacturer selling through an online platform faces a demand information disadvantage in the reseller channel and sales inefficiency in the marketplace channel. To fill this research gap, our work illustrates the interaction between demand information asymmetry and selling cost asymmetry to identify the equilibrium channel strategy and provides useful managerial guidelines for both online platforms and manufacturers.

In the era of digitalization, digital technology has transformed businesses and created enormous opportunities for organizations worldwide. Unsurprisingly, research on digital transformation has garnered significant interest among academics in recent decades. However, this study aims to recognize the key and holistic antecedents influencing digital transformation in manufacturing firms. This study also investigates the indirect relationships of antecedents with firm performance.

The hypothesis was investigated using the partial least squares structural equation modeling (PLS-SEM) approach. The data was collected from 279 employees through a self-administered survey of manufacturing firms.

The results described a significant and positive impact of competitive pressure, leadership role, organization culture, organization mindfulness, government regulation, and IT readiness on digital transformation and firm performance. Furthermore, digital transformation partially mediates the relationship between antecedents and firm performance.

The study finds a holistic perspective of the critical antecedents of digital transformation using the mediation role of digital transformation and moderating effects of firm agility. Additionally, all antecedents have a significant association with Firm Performance.

Drawing on the knowledge-based view, this study investigates how IT–business alignment influences business model design via organizational learning and examines the moderating role of data-driven culture in the relationship between IT–business alignment and business model design via organizational learning.

Using multi-respondent survey data collected from 597 Chinese firms, mediation and moderated mediation analyses were used to examine this study's hypotheses.

The mediation test results revealed organizational learning served as a mediator between IT–business alignment and two types of business model design (i.e. novelty- and efficiency-centered). In addition, data-driven culture strengthened the indirect effects of IT–business alignment on these two types of business model design via organizational learning.

This study extends current understandings of the relationship between IT–business alignment and business model design by revealing the mediating role of organizational learning and investigating its indirect effects under various degrees of data-driven culture. As such, it contributes to the literature on the business model and IT–business alignment and provides insights for managers seeking to achieve the expected business model design.

The purpose of this paper is to investigate the effects of electric current stressing on damping properties of Sn5Sb solder.

Uniformly shaped Sn5Sb solders were prepared as samples. The length, width and thickness of the samples were 60.0, 5.0 and 0.5 mm, respectively. The damping properties of the samples were tested by dynamic mechanical analyzer with a cooling system to control the test temperature in the range of −100 to 100°C. Simultaneously, electric current was imposed to the tested samples using a direct current supply. After tests, the samples were characterized using scanning electron microscope, electron backscatter diffraction and transmission electron microscope, which was aimed to figure out the damping mechanism in terms of electric current stressing induced microstructure evolution.

It is confirmed experimentally that the increase in damping properties is due to Joule heating and athermal effects of current stressing, in which Joule heating should make a higher contribution. G–L theory can be used to explain the damping properties of strain amplitude under current stressing by quantitative description of geometrically necessary dislocation density. While the critical strain amplitude and high temperature activation energy decrease with increasing electric current.

These results provide a new method for vibration reliability evaluation of high-temperature lead-free solders in serving electronics. Notably, this method should be also inspiring for the mechanical performance evaluation and reliability assessment of conductive materials and structures serving under electric current stressing.

By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).

The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.

By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.