Search results

This paper aims to conduct an empirical study to investigate whether an industry’s position affects the transmission of information and economic shocks.

This paper conducts an empirical study of inventory performance based on a large panel of 71 industries in the manufacturing, wholesale and retail sectors over a 10-year period (2007–2016).

It is found that the position of a focal industry in the supply chain network moderates the impacts of macroeconomic uncertainty shocks and shocks from supplier/customer industries on the focal industry’s inventory. On the one hand, more central industries are more sensitive to macroeconomic uncertainty shocks as well as spillover shocks from their supplier and customer industries. On the other hand, uncertainty shocks from more central industries have higher impact on their partner industries than those from less central industries.

A manager needs to take into account the network positions of suppliers/customers in supply network when making inventory decisions. For example, when sharing information with partners, the network position of a partner affects how important its information is.

The key novelty of this paper is the introduction of network structure that represents the supplier–customer relationships in the entire economy, and the modeling of uncertainty shocks transmitted through the supply chain network.

This study aims to investigates the influence of proactive personality on employee radical creativity through transformational leadership, professional ethical standards and creative self-efficacy.

The data were collected from 343 superior–subordinate dyads in China. A confirmatory factor analysis was performed to measure the validity of the variables. A regression analysis was performed to assess the relationship between model assumptions.

The results showed that: (1) Proactive personality was positively related to employee radical creativity. (2) Transformational leadership and professional ethical standards moderated the relationship between proactive personality and radical creativity. Specifically, the relationship between proactive personality and employee radical creativity was strong, as expected. It was the strongest in the presence of high transformational leadership and high professional ethical standards. (3) Creative self-efficacy acted as a mediator in this interaction.

This study is a pioneering investigation in the Chinese context. It empirically examines the interactive relationship between proactive personality and radical creativity through transformational leadership and professional ethical standards. Additionally, it substantiates creative self-efficacy as the psychological mechanism behind this interaction. Consequently, this study offers a comprehensive framework with potential implications for personality assessments in the workplace, leadership training, criteria formulation and enhancement of radical creativity.

Promoting electric vehicles (EVs) is an effective way to achieve carbon neutrality. If EVs are widely adopted, this will undoubtedly be good for the environment. The purpose of this study is to analyze the impact of network externalities and subsidy on the strategies of manufacturer under a carbon neutrality constraint.

In this paper, the authors propose a game-theoretic framework in an EVs supply chain consisting of a government, a manufacturer and a group of consumers. The authors examine two subsidy options and explain the choice of optimal strategies for government and manufacturer.

First, the authors find that the both network externalities of charging stations and government subsidy can promote the EV market. Second, under a relaxed carbon neutrality constraint, even if the government’s purchase subsidy investment is larger than the carbon emission reduction technology subsidy investment, the purchase subsidy policy is still optimal. Third, under a strict carbon neutrality constraint, when the cost coefficient of carbon emission reduction and the effectiveness of carbon emission reduction technology are larger, social welfare will instead decrease with the increase of the effectiveness of emission reduction technology and then, the manufacturer’s investment in carbon emission reduction technology is lower. In the extended model, the authors find the effectiveness of carbon emission reduction technology can also promote the EV market and social welfare (or consumer surplus) is the same whatever the subsidy strategy.

The network externalities of charging stations and the subsidy effect of the government have a superimposition effect on the promotion of EVs. When the network effect of charging stations is relatively strong, government can withdraw from the subsidized market. When the network effect of charging stations is relatively weak, government can intervene appropriately.

Comparing previous studies, this study reveals the impact of government intervention, network effects and carbon neutrality constraints on the EV supply chain. From a sustainability perspective, these insights are compelling for both EV manufacturers and policymakers.

In 2020, an outbreak of Salmonella Stanley linked to imported dried wood ear mushrooms affected 55 individuals in the United States of America. These mushrooms, commonly used in Asian cuisine, require processing, like rehydration and cutting, before serving. The US Centres for Disease Control and Prevention advise food preparers to use boiling water for rehydration to inactivate vegetative bacterial pathogens. Little is known about how food handlers prepare this ethnic ingredient and which handling procedures could enable Salmonella proliferation.

This study used content analysis to investigate handling practices for dried wood ear mushrooms as demonstrated in YouTube recipe videos and to identify food safety implications during handling of the product. A total of 125 Chinese- and English-language YouTube videos were analysed.

Major steps in handling procedures were identified, including rehydration, cutting/tearing and blanching. Around 62% of the videos failed to specify the water temperature for rehydration. Only three videos specified a water temperature of 100 °C for rehydrating the mushrooms, and 36% of the videos did not specify the soaking duration. Only one video showed handwashing, cleaning and sanitising of surfaces when handling the dried wood ear mushrooms.

This study found that most YouTube videos provided vague and inconsistent descriptions of the rehydration procedure, including water temperature and soaking duration. Food preparers were advised to use boiling water for rehydration to inactivate vegetative bacterial pathogens. However, boiling water alone is insufficient to inactivate all bacterial spores. Extended periods of soaking and storage could be of concern for spore germination and bacterial growth. More validation studies need to be conducted to provide guidance on how to safely handle the mushrooms.

This study will make a distinctive contribution to the field of food safety by being the first to investigate the handling procedure of a unique ethnic food ingredient, dried wood ear mushrooms, which has been linked to a previous outbreak and multiple recalls in the United States of America. The valuable data collected from this study can help target food handling education as well as influence future microbial validation study design and risk assessment.

This paper aims to examine the existing literature on firms’ power through the lens of the supply chain and highlights some gaps that could be covered by future research.

This study uses a systematic framework-based review combining the insights of the antecedents, decisions and outcomes (ADO) and theories, contexts and methods (TCM) frameworks. The review was carried out using a sample of 108 articles published between 1984 and 2022 in 25 prestigious journals.

The ADO framework maps out the state of the art of the antecedents of power (i.e. sources and types of firm power), the decision to use power and the effect that exercising power over other firms may have on firm performance and the quality of inter-firm relationships. In addition, this framework highlights factors that mediate or moderate the decision to exercise power and the factors that mediate or moderate the outcomes of exercising power or power asymmetry. The TCM framework provides insights into the theories, contexts (i.e. countries, industries, level of analysis and sources of data) and methods used by the existing literature. The content analysis using the aforementioned frameworks provides the basis to elaborate propositions for future research on power in the supply chain from the perspective of gender differences.

This systematic literature review offers a comprehensive guide for researchers to understand the antecedents, decisions and outcomes of firm power in the supply chain, as well as the TCM used in the literature. The content analysis using frameworks provides a road map to investigate the proposed factors that might moderate the decision to exercise power and the outcome of exercising power or power asymmetry from the perspective of gender differences. In addition, based on content analysis, the authors make propositions about TCM that could be applied in future research.

From a practical perspective, this systematic literature review may help managers to better understand the sources and consequences of their firm’s power. This would allow managers to make better decisions when negotiating with their supply chain parties, which could potentially lead to better performance for their firms and the whole supply chain.

To the best of the authors’ knowledge, this study is the first to conduct a comprehensive systematic literature review of the different dimensions of firms’ power in the supply chain.

Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.

After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.

The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.

The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.

This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.

This study aims to contribute novel insights into understanding and mitigating the harmful consequences of abusive supervision (AS) by examining the association between AS experiences, revenge, forgiveness, and the moderating role of emotional intelligence (EI). The key argument is that employees' EI can influence the AS experience through affective processes, countering supervisors' abusive behaviors.

A between-person scenario-based experiment was conducted with 366 participants divided into AS and control groups. The study explored the association between AS experience and revenge/forgiveness, mediated by core affect (valence and activation). EI abilities were measured as a moderator. Data analysis examined the relationships and interactions among AS, revenge/forgiveness, EI, and affective experiences.

The study reveals significant findings indicating that AS experiences were positively associated with revenge and negatively associated with forgiveness. The mediation analysis confirmed the role of core affect in these relationships. EI emerged as a moderator, shaping the association between AS experiences and revenge/forgiveness. Importantly, participants with higher EI exhibited lower revenge intentions, demonstrating the potential of EI to mitigate the adverse effects of AS. Unexpectedly, individuals with high EI also expressed fewer forgiveness intentions.

This study provides a comprehensive understanding of how employees can effectively counterbalance the impact of AS through higher levels of strategic EI. Examining core affect as a mediator offers novel insights into coping mechanisms in response to AS experiences and their consequences.

The study acknowledges several limitations, as the scenarios may only partially capture the complexities of real-life AS situations. The focus on a specific context and the sample characteristics limit the generalizability of the findings. Future research should explore diverse organizational contexts and employ longitudinal designs.

The findings have practical implications for organizations as enhancing employees' EI skills through training programs interventions and integrating EI into organizational culture and leadership conduct.

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.

Building information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.

The theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.

The study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.

Finally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.

To the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.

This paper aims to analyze the potentials of dynamic, commitment and revenue-sharing contracts; that a nonrebate offering manufacturer can use to safeguard his profit while his competitor offers customer rebates in a supply chain consisting of two manufacturers and a common retailer.

We consider a two-period supply chain model to explore optimal decisions under eight possible scenarios based on the contract and rebate offering decisions. Because the manufacturers are selling substitutable products, therefore, a customer rebate on one of the products negatively impacts the selling quantity of other. Optimal price, rebate, and quantities are examined and compared to explore the strategic choice for both the rebate offering and non-rebate offering manufacturer. Comparative evaluation is conducted to pinpoint how the parameters such as contract parameters and its nature affect the members.

The results demonstrate that all these contracts instigate the rebate offering manufacturer to provide a higher rebate, but do not ensure a higher profit. If the revenue sharing contract is offered to the common retailer, the effectiveness of the rebate program might reduce significantly, and the rebate offering manufacturer might receives lower profits. A non-rebate offering manufacturer might use a commitment contract to ensure higher profits for all the members and make sure the common retailer continues the product.

The effect of customer rebate vs. supply chain contract under competition has not yet been explored comprehensively. Therefore, the study contributes to the literature regarding interplay among pricing decision, contract choice and rebate promotion in a two-period setting. The conceptual and managerial insights contribute to a better understanding of strategic decision-making for both competing manufacturers under consumer rebates.