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In prior literature, online endorsement system allowing the users to “like” or “dislike” shared information is found very useful in information filtering and trust elicitation in most social networks. This paper shows that such systems could fail in the context of investment communities due to several psychological biases.

This study develops a series of regression analyses to model the “like”/“dislike” voting process and whether or not such endorsement distinguishes between valuable information and noise. Trading simulations are also used to validate the practical implications of the findings.

The main findings of this research are twofold: (1) in the context of investment communities, online endorsement system fails to signify value-relevant information and (2) bullish information and “wisdom over the past event” information receive more “likes” and fewer “dislikes” on average, but they underperform in stock market price discovery.

This study demonstrates that biased endorsement may lead to the failure of the online endorsement system as information gatekeeper in investment communities. Two underlying mechanisms are proposed and tested. This study opens up new research opportunities to investigate the causes of biased endorsement in online environment and motivates the development of alternative information filtering systems.

As a common form of failure in industry, corrosion causes huge economic losses. At present, with the development of computational techniques, artificial intelligence (AI) is playing a more and more important role in the field of scientific research. This paper aims to review the application of AI in corrosion protection research.

In this paper, the role of AI in corrosion protection is systematically described in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction.

With efficient and in-depth data processing methods, AI can rapidly advance the research process in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction and save on costs.

This paper summarizes the application of AI in corrosion protection research and provides the basis for corrosion engineers to quickly and comprehensively understand the role of AI and improve production processes.

This paper aims to contribute to the performance improvement and the broader application of hot-dip galvanized coating.

First, the ability to provide barrier protection, galvanic protection, and corrosion product protection provided by hot-dip galvanized coating is introduced. Then, according to the varying Fe content, the growth process of each sublayer within the hot-dip galvanized coating, as well as their respective microstructures and physical properties, is presented. Finally, the electrochemical corrosion behaviors of the different sublayers are analyzed.

The hot-dip galvanized coating is composed of η-Zn sublayer, ζ-FeZn13 sublayer, δ-FeZn10 sublayer, and Γ-Fe3Zn10 sublayer. Among these sublayers, with the increase in Fe content, the corrosion potential moves in a noble direction.

There is a lack of research on the corrosion behavior of each sublayer of hot-dip galvanized coating in different electrolytes.

It provides theoretical guidance for the microstructure control and performance improvement of hot-dip galvanized coatings.

The formation mechanism, coating properties, and corrosion behavior of different sublayers in hot-dip galvanized coating are expounded, which offers novel insights and directions for future research.

With the increase in population, the energy needs of countries are also increasing. These countries have difficulties in meeting these increasing needs. Countries that cannot meet this need have to import energy from abroad. This situation adversely affects the current account balance of countries. Nuclear energy investments allow countries to obtain their own energy, although there are some criticisms. In this framework, while some countries in the world increase their nuclear energy investments, some countries do not have any nuclear power plants (NPP). There are 32 such countries where nuclear energy projects are running till date. Therefore, it is very important to determine the socio-economic variables of countries that have nuclear energy investments. In this context, a detailed literature analysis will be made first to determine socio-economic criteria. Then, the importance weights of these factors will be calculated using the Decision Making Trial and Evaluation Laboratory (DEMATEL) method. The profiles of the countries that make nuclear energy investments demonstrate that education level is the most essential socio-economic factor for the improvement of nuclear energy investments. Also, income inequality is another important variable in this regard. However, consumption behaviour and saving behaviour have the lowest weights.

Given the fierce competition in financial services, service failure management and trust restoration tactics are becoming strategic priorities. Studies investigating trust restoration have increased over the years due to the significance of trust in services and the frequency of trust violations. Drawing on the sense-making and defensive approaches of attribution theory, this study aims to explore the effectiveness of various trust recovery tactics (e.g. apology, explanation, and investigation) in financial services considering the prevalence of service failure severity.

Based on a scenario-based survey, this study gathered data from 402 consumers of different banks in Pakistan. The study analyzed the data using ordinary least square regressions and structural equation modeling.

The study indicated that explanation is more effective in repairing character-competence and commitment-based trust, while investigation remained highly effective for inducing congruence-based trust. Interestingly, an apology was more effective for communication-based trust repairing, while context-based trust recovery was unaffected against all recovery tactics. Despite the prevalence of severe service failure, recovery actions proved fully effective for character-competence and commitment-based trust while partially effective for congruence-based trust recovery. This study also found that severe service failure undermines the effectiveness of recovery actions in repairing communication and context-based trust.

The study extends the literature on trust recovery by integrating sense-making and defensive attribution theory. The sense-making approach contributes to the existing knowledge on trust recovery by elucidating how consumers and service providers develop a shared understanding to facilitate the recovery mechanism of multidimensional trust in financial services.

Consumer forgiveness is an important concept in service failure and recovery research. To advance knowledge and develop future research agenda in this domain, this paper provides a systematic review of the literature on factors influencing consumer forgiveness while adopting the customer journey perspective.

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, a systematic literature review (SLR) was conducted of 102 peer-reviewed journal articles, on factors influencing consumer forgiveness, published between January 2000 and December 2020.

The authors' analysis offers a detailed account of the factors influencing consumer forgiveness across the three stages of the service journey: pre-transgression, transgression and recovery. From the review, the authors identified significant gaps relating to the interactions between the relevant factors influencing forgiveness throughout the various stages of the consumer service journey. Based on the findings, the authors offer several research questions to help managers optimize customer forgiveness following a service failure throughout each stage of consumer service journey.

The authors' review synthesizes the literature on factors contributing to consumer forgiveness and integrates these factors into the customer service journey. The authors' findings inform directions for future research and provide insights regarding the measures that service providers should take to understand and encourage consumer forgiveness.

Nuclear energy investments contribute significantly to the energy independence of countries. This situation helps countries to develop both economically and socially. Therefore, countries need to develop strategies to increase their nuclear energy investments. However, radioactive waste generated in nuclear reactors is one of the most important disadvantages of this type of energy. Due to this situation, the wastes generated must be disposed of effectively for nuclear energy investments to be effective. In this study, it is aimed to create optimal strategies for the effective waste managements generated in nuclear power plants. Within this framework, four different balanced scorecard perspectives are considered as the criteria. In the analysis process, Analytical Hierarchy Process (AHP) methodology is taken into consideration. It is identified that learning and development is the most critical factor for the effective radioactive waste management created in nuclear power plants. On the other side, internal factors are the second most important criterion in this framework. Hence, it is understood that nuclear energy investors should give priority to the technological development for effective waste management in nuclear power plants. With the help of these technological improvements, the wastes can be disposed more successfully. As a result, environmental sustainability can be provided much easily.

This study investigates firms' innovation behaviour under environmental change. Therefore, it examines the effect of trade disputes on corporate technological innovation and how product market competition moderates this relationship.

This research tests the hypotheses using the fixed effects model based on panel data of publicly listed enterprises in China from 2007–2020.

The empirical results validate the positive association between trade disputes and corporate research and development (R&D) intensity as well as the U-shaped relationship between trade disputes and radical innovation. Additionally, the moderating effect of product market competition is verified: a concentrated market with less competition flattens the U-shaped curve of radical innovation induced by trade disputes; as the market becomes more concentrated and less competitive, the U-shaped relationship eventually turns into an inverted U.

First, this study contributes to the corporate innovation and trade dispute literature by expanding the environmental antecedents of technological innovation and the firm-level consequences of trade disputes. Second, this study enriches the theoretical framework of the environment–innovation link through an integrated perspective of contingency theory and dynamic capabilities view. Third, instead of the traditional linear mindset which had led to contradictory results, this study explores a curvilinear effect in the environment–innovation relationship.

Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.

Merely being known as a highly ethical or strong performer cannot shield a company from every kind of crisis. From product failures to environmental and social issues, a brand’s ability to manage crises and rapidly regain consumer trust is essential. This study aims to explore whether consumer perceptions of a brands’ prior commitments to two different areas of corporate responsibility (social and product responsibility) alleviate the postcrisis attribution of accountability and further build brand resilience, examining differences between two types of crisis situations – values versus performance crises.

A scenario-based online survey on product versus ethical labor issues was conducted. The data were collected from a highly valid, nationwide sample set of more than a thousand US consumers. Multigroup structural equation modeling was used as the primary data analysis method.

A brand’s precrisis commitment to social responsibility was found to decrease attribution of accountability across both types of crises. It also strengthened brand resilience, but this effect was more prevalent in a performance than a values crisis. The effects of precrisis commitment to product responsibility on brand resilience were minimal or insignificant across crisis types.

Previous research underexplores which types of corporate responsibility commitments provide a firm with a better protection against crises. This study significantly advances the knowledge regarding the type of commitments that can substantially increase brand resilience, which supports the rationale of making stronger commitments to social responsibility than to product responsibility. Practical insights are provided into how investments in corporate social responsibility help alleviate consumers’ negative perceptions during the outbreak of a brand crisis and build more brand muscle that enables resilience against future crises.