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This study investigated a new attributional phenomenon in a brand scandal setting in which consumers tend to blame the top management of a brand, even though it was the frontline parties that caused the scandal. The authors termed this phenomenon upward blame attribution (UBA), shedding light on whether consumers in a host country indicate a higher UBA for a multinational (vs domestic) brand scandal, which in turn reinforces their revenge and impairs their reconciliation reactions, and whether these effects are contingent on consumer animosity.

Two experimental studies were conducted with real and fictitious brand/product and country stimuli with 1,399 Chinese participants.

Both studies verified UBA and found that Chinese consumers' UBA is higher for multinational (vs domestic) brand scandals, which drives their stronger desire for revenge and weaker desire for reconciliation. Moreover, consumers with high (vs low) animosity toward a multinational brand's home country reported a higher UBA for the multinational (vs domestic) brand scandal, which in turn reinforces their desire for revenge and impairs their desire for reconciliation.

The study provides new insights into host-country consumers' more severe UBA and responses toward multinational versus domestic brand scandals and the amplifying role of consumer animosity in these processes. It also has implications for mitigating host-country consumers' UBA and negative responses to multinational brand scandals.

This study contributes to the blame attribution literature by verifying consumers' UBA and the country-of-origin (COO) literature by revealing host-country consumers' higher UBA, stronger revenge desire and weaker reconcile desire toward multinational (vs domestic) brand scandals. It extends the knowledge regarding consumers' blame attributions toward the top management of a multinational (vs domestic) brand in scandals and the impact of such attributions.

This study aims to explore the double-edged sword effect of work connectivity behavior after-hours (WCBA) on employees’ occupational mental health. Drawing on job demand-resource theory, the authors examined the double mediating mechanism of work autonomy and work-family conflict on the relationship of WCBA, work engagement and work burnout. At the same time, the authors examined the moderating role of responsiveness from superiors, hoping to clarify how WCBA brings employees positive experiences (engagement) or negative experiences (burnout).

Under the mediating mechanism of work autonomy and work-family conflict, the authors built a dual-path model and moderated mediation model to examine the effect of WCBA on work engagement and burnout. Two-stage paired data were collected from various industries in China by distributing questionnaires to employees. The hypotheses were tested using the structural equation model and the bootstrap test method.

The results showed that WCBA positively affects work engagement and burnout. Work autonomy plays a mediating role both in the relationship between WCBA and work engagement and in the relationship between WCBA and work burnout. In addition, work-family conflict plays a mediating role both in the relationship between WCBA and work burnout and in the relationship between WCBA and work engagement. Responsiveness from superiors not only moderated the relationship between WCBA and work autonomy and between WCBA and work-family conflict but also moderated the mediating effects of work autonomy and work-family conflict.

This study examined the double-edged sword effect of WCBA on employees’ occupational mental health, the dual mediation of work autonomy and work-family conflict and the moderating effect of responsiveness from superiors. This study can enrich the understanding of the effects of WCBA as well as the influential factors and boundary conditions related to employees’ occupational mental health. Organizations (represented by superiors) and individuals were integrated into one model, providing a new perspective for studying WCBA. The research will help managers and individuals gain a comprehensive understanding of WCBA, and how to enhance its positive effects and circumvent its negative effects.

This study investigated the potential negative effects of a sponsored team's losing performance on audiences' trust and purchase intention toward the sponsoring brand. Shedding light on the moderating role of sponsoring brand familiarity among audiences and audience team identification regarding such negative effects, the study establishes when sports sponsorship may incur risk to a sponsoring brand.

Three experimental designs (audience as stimulus of a team's losing vs control condition) were used to indicate whether and when losing performance influences participants' trust and purchase intention toward the sponsoring brand.

The participants in the losing condition report lower brand trust and purchase intention. Brand trust mediates the relationship between losing results and decreased purchase intention. The negative effects of losing on brand trust and purchase intention only appear when the sponsoring brand has low familiarity among audiences and only for audiences with low identification.

The strategy of a brand with low familiarity sponsoring a team that frequently loses has risks and is not worth advocating. However, if an unknown brand has already sponsored a team that often loses, the efforts to cultivate audiences' identification with the team can reduce the potential risks.

The affirmed negative effects of losing performance on brand trust and purchase intention have value for firm sponsorship decisions. This study contributes to the sponsorship literature by revealing two boundary conditions (sponsoring brand familiarity and audiences' team identification) for those negative effects.

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

This study aims to benchmark Chinese TEFL academics’ research productivities, as a way to identify and, subsequently, address research productivity issues. This study investigated 182 Chinese TEFL academics’ research outputs and perceptions about research across three Chinese higher education institutions using a literature‐based survey. ANOVA, t‐tests and descriptive statistics were used to analyse data from and between the three institutions. Findings indicated that more than 70 per cent of the TEFL academics had produced no research in 10 of the 12 research output fields during 2004‐2008. The English Language and Literature Department in the national university outperformed all other departments at the three institutes for most of the research output categories. While a majority of the participants seemed to hold positive perceptions about research, t‐tests and ANOVA indicated that their research perceptions were significantly different across institutes and departments. Developing TEFL research capacity requires tertiary institutions to provide research‐learning opportunities.

Sustainable development requires businesses to improve their positive and reduce their negative impacts. This chapter discusses how the impact of business on sustainable development can be measured and managed using the sustainable development goals (SDGs). First, it introduces two complementary approaches for measuring impact: a top-down approach that departs from the economic activities that companies undertake; and a bottom-up approach that defines the impacts of individual companies. Second, it argues that companies can manage their impacts on the SDGs through a nexus approach. Instead of treating SDGs as isolated silos, a nexus approach aims to advance multiple SDGs simultaneously (creating co-benefits) while reducing the risk that contributions to one SDG undermine progress on another (avoiding trade-offs).

The purpose of this paper is to present the landscape of the cash-per-publication reward policy in China and reveal its trend since the late 1990s.

This study is based on the analysis of 168 university documents regarding the cash-per-publication reward policy at 100 Chinese universities.

Chinese universities offer cash rewards from USD30 to USD165,000 for papers published in journals indexed by Web of Science, and the average reward amount has been increasing for the past ten years.

The cash-per-publication reward policy in China has never been systematically studied and investigated before except for in some case studies. This is the first paper that reveals the landscape of the cash-per-publication reward policy in China.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.

This paper presents a review concerning the analytical and inverse methods of small punch creep test (SPCT) in order to evaluate the mechanical property of component material at elevated temperature.

In this work, the effects of temperature, specimen size and shape on material properties are mainly discussed using the finite element (FE) method. The analytical approaches including membrane stretching, empirical or semi-empirical solutions that are currently used for data interpretation have been presented.

The state-of-the-art research progress on the inverse method, such as non-linear optimization program and neutral network, is critically reviewed. The capabilities of the inverse technique, the uniqueness of the solution and future development are discussed.

The state-of-the-art research progress on the inverse method such as non-linear optimization program and neutral network is critically reviewed. The capabilities of the inverse technique, the uniqueness of the solution and future development are discussed.