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The e-freight program launched by the International Air Transport Association (IATA) has gradually become a standard specification for international air freight operations. This study examined critical factors affecting air freight forwarders’ decision to adopt the IATA e-freight using a technology-organization-environment model with air freight forwarders in Taiwan as the base. Our findings show that ‘information technology (IT) competence’, ‘trading partner pressure’, ‘government policy’ and ‘competitive pressure’ all have significant positive effects on air freight forwarders’ decision to adopt the e-freight and the top three factors among these are ‘government funding’, ‘government’s active promotion’ and ‘government’s requirement of electronic air waybill (e-AWB)’. Finally, this study proposes strategies that can encourage air freight forwarders to decide on e-freight adoption for the information of relevant oK regyawniozradtison International Air Transport Association (IATA); IATA e-freight; Technology organization environment model; Air freight forwarder

This study examines whether and how a client's business strategy can affect the relationship between auditor characteristics and financial reporting quality.

In this study, auditor industry specialization and tenure were used as proxies for auditor characteristics. The client business strategy was measured using the resource allocation index method. Finally, discretionary accruals are used to assess financial reporting quality. This study includes 1,450 firm-year observations and 145 companies listed on the Tehran Stock Exchange (TSE) over a ten-year period from 2011 to 2020. The research hypotheses were analyzed using a multivariate regression model and panel data.

The results show that auditor industry specialization increases financial reporting quality. This relationship improves when the client's business strategy deviates from the industry–normal strategy. The research findings state that auditor tenure has a positive association with financial reporting quality, and this relationship is strengthened when the company's business strategy deviates from the normal industry strategy.

The findings of this study provide important evidence for investors, firm management, and auditing firms. Investors must consider the auditor characteristics when selecting companies listed on the TSE. Managers of Iranian companies are advised to consider the auditor's characteristics when choosing an audit firm to increase financial reporting quality. Audit firms should evaluate their business strategies in audit planning to increase the quality of financial reporting.

To the best of the authors’ knowledge, this is the first empirical study to examine the relationship between auditor characteristics and the financial reporting quality in the emerging capital market by considering the clients' business strategy.

This study aims to examine the micromechanisms of how knowledge culture fosters human capital development.

An empirical model was developed by using the structural equation modeling method based on a sample of 321 Polish knowledge workers employed in different industries.

This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does not, and this hiding is considered a waste of knowledge. If tacit knowledge does not circulate within an organization, it is a severe waste of an organization. The findings indicate that shame from making mistakes might impede the sharing of knowledge gained from making those mistakes, and in such cases, the knowledge remains hidden.

Leaders aiming to ensure human capital growth should implement an authentic learning culture composed of a learning climate and mistakes acceptance components that enable open discussion about mistakes on each organizational level.

The knowledge culture is found to be an essential element of building human capital but, at the same time, not sufficient without a learning culture, and its mistakes acceptance component. A permanent organizational learning mode that supports a continuous organizational shared mental model reframing is an antidote to tacit knowledge hiding.

This study aims to review the literature on sharing economy logistics and crowd logistics to answer the three following questions: How is the literature on sharing economy logistics structured? What are the main trends in sharing economy logistics and crowd logistics? What are the future research options?

Bibliometric analysis is used to evaluate 85 articles published over the past 12 years; it identifies the top academic journals, authors and research topics contributing to the field.

The sharing economy logistics and crowd logistics literature is structured around several disciplines and highlights that some are more scientifically advanced than others in their subject definitions, designs, modelling and innovative solutions. The main trends are organized around three clusters: Cluster 1 refers to the optimal allocation of costs, prices, distribution and supplier relationships; Cluster 2 corresponds to business related crowdsourcing and international industry practices; and Cluster 3 includes the impact of transport on last-mile delivery, crowd shipping and the environment.

The study is based on data from peer-reviewed scientific journals and conferences. A broader overview could include other data sources such as books, book chapters, working papers, etc.

Future research directions are discussed in the context of the evolution from crowd logistics to crowd intelligence, and the complexities of crowd logistics such as understanding how the social crowd can be integrated into the logistics process. Our results are part of the crowd science and engineering concept and provide some answers about crowd cyber-system questions regarding crowd intelligence in logistic sector.

The purpose of this paper is to examine the impacts of farmland renting-in on planted grain acreage.

A survey data of five counties were analyzed with the two-stage ordinary least squares model.

Households renting-in land trended to plant more maize, and the more land was rented by a household the more maize was planted, while wheat acreage showed non-response to farmland renting-in.

Overall, the analysis suggests that policy makers should be prepared for different changing trends of grain crop acreage across the nation as farmland transfer continues. Future research should pay attention to the effect of farmland transfer on agricultural productivity and rural household income growth.

As the Chinese Government is promoting larger-scale and more mechanized farms as a way of protecting grain security, it is important to understand whether farmland renting-in will reduce planted grain acreage. This study provides empirical evidence showing the answer to that question may differ across different regions and depend on the particular grain crop in question.

This study aims to find how can fashion micro-influencers and their electronic word-of-mouth (eWOM) messages increase consumer engagement on social media, focusing on micro-influencers’ influence, typology, eWOM content and consumer engagement.

A total of 20,000 microblogs were collected from Irish fashion micro-influencers and analyzed through keyword classification and content analysis in NVivo. The determinants of eWOM persuasiveness for consumer engagement on social media were investigated based on Sussman and Siegal’s information adoption model.

The study finds that among the four types of micro-influencers, market mavens and their eWOM messages have the highest impact on consumer engagement on social media, and it presents a repetitive and persuasive eWOM model of market mavens to increase consumer participation. Also, the study discovers that micro-influencers’ occasion-related microblogs have an increasing impact on consumer interactions whereas microblogs with brands have a decreasing engagement with consumers on social media.

This study advances prior studies on the relationship between influencers’ eWOM messages and consumer participation on social media by the development of a persuasive eWOM model of micro-influencers to increase consumer engagement and fill in the lack of relevant literature. Also, findings provide actionable insights for marketing communication practitioners to persuade consumers to participate in eWOM communications and establish strong consumer-brand relationships on social media.

Recently, deep learning (DL) has been widely applied in various aspects of human endeavors. However, studies have shown that DL models may also be a primary cause of data leakage, which raises new data privacy concerns. Membership inference attacks (MIAs) are prominent threats to user privacy from DL model training data, as attackers investigate whether specific data samples exist in the training data of a target model. Therefore, the aim of this study is to develop a method for defending against MIAs and protecting data privacy.

One possible solution is to propose an MIA defense method that involves adjusting the model’s output by mapping the output to a distribution with equal probability density. This approach effectively preserves the accuracy of classification predictions while simultaneously preventing attackers from identifying the training data.

Experiments demonstrate that the proposed defense method is effective in reducing the classification accuracy of MIAs to below 50%. Because MIAs are viewed as a binary classification model, the proposed method effectively prevents privacy leakage and improves data privacy protection.

The method is only designed to defend against MIA in black-box classification models.

The proposed MIA defense method is effective and has a low cost. Therefore, the method enables us to protect data privacy without incurring significant additional expenses.