Ru-Jing Hou, Sheng-Hao Han, Yu-Dong Zhang, Chu-Bing Zhang and Kun Wang
The biggest obstacle to the sustainable development of online brand communities is social loafing. Based on 3M Hierarchical Model of Personality, this paper aims to discuss the…
Abstract
Purpose
The biggest obstacle to the sustainable development of online brand communities is social loafing. Based on 3M Hierarchical Model of Personality, this paper aims to discuss the influence of the Big Five on social loafing in online brand communities, and consider the mediating role of dehumanization from the perspective of moral disengagement theory, so as to alleviate social loafing and promote the sustainable development of online brand communities.
Design/methodology/approach
The data were collected utilizing the online self-report questionnaires. Community members of mobile phone brands represented by HUAWEI and Xiaomi completed the questionnaire sets. Based on the responses of 214 participants, a structural equation modeling was applied to examine the relationship between Big Five on social loafing in online brand communities. Later, bootstrap analysis was used to further explore the indirect effect of dehumanization.
Findings
Only two personality traits, neuroticism and extroversion, have direct effect on social loafing, while agreeableness, conscientiousness and openness not. However, all the Big Five personality traits can indirectly influence social loafing through dehumanization.
Originality/value
This study introduces the concept of social loafing into online brand communities, and analyzes social loafing from the unique research perspective of moral disengagement theory, which can not only contribute to the development of moral disengagement theory and social loafing theory but also provide guiding points for relieving social loafing in online brand communities.
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In the digital era, business-to-business (B2B) salespersons are encouraged to communicate with buyers on social media platforms and shape customer loyalty. However, the effect of…
Abstract
Purpose
In the digital era, business-to-business (B2B) salespersons are encouraged to communicate with buyers on social media platforms and shape customer loyalty. However, the effect of social media usage and its mechanism remain unexplored. The purpose of this paper is to investigate how salespersons’ social media usage influences B2B buyers’ trust beliefs and purchase risk, and therefore, customer loyalty.
Design/methodology/approach
The authors conduct an online-survey, use partial least squares structural equation modeling to analyze the data, and adopt SPSS PROCESS macro 2.13 to test mediation effects.
Findings
Salespersons’ social media usage can enhance buyers’ trust beliefs on salespersons’ ability, integrity and benevolence, but only the latter two can improve customer loyalty. Social media usage does not directly affect purchase risk, and only benevolence can reduce purchase risk. Serial mediation models reveal that the effect of social media usage on customer loyalty is mediated by buyers’ trust beliefs on salespersons’ integrity/benevolence and purchase risk.
Originality/value
First, the authors confirm the effect of social media usage on customer loyalty in B2B context and refute the fallacy of social media uselessness in B2B practices. Second, the research shows that buyers’ trusting beliefs on salesperson’s ability and integrity do not significantly influence perceived risk. The finding is different from the stereotypical judgment in B2C scenarios. Third, the authors distinguish differently weighted influences of buyers’ trusting beliefs on salesperson’s ability, integrity and benevolence, and highlight the role of salespersons’ altruism attributes in shaping customer loyalty.
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Yuanwu Cai, Bo Chen and Chongyi Chang
This paper aims to analyze the stress and strain distribution on the track wheel web surface and study the optimal strain gauge location for force measurement system of the track…
Abstract
Purpose
This paper aims to analyze the stress and strain distribution on the track wheel web surface and study the optimal strain gauge location for force measurement system of the track wheel.
Design/methodology/approach
Finite element method was employed to analyze the stress and strain distribution on the track wheel web surface under varying wheel-rail forces. Locations with minimal coupling interference between vertical and lateral forces were identified as suitable for strain gauge installation.
Findings
The results show that due to the track wheel web’s unique curved shape and wheel-rail force loading mechanism, both tensile and compressive states exit on the surface of the web. When vertical force is applied, Mises stress and strain are relatively high near the inner radius of 710 mm and the outer radius of 1110 mm of the web. Under lateral force, high Mises stress and strain are observed near the radius of 670 mm on the inner and outer sides of the web. As the wheel-rail force application point shifts laterally toward the outer side, the Mises stress and strain near the inner radius of 710 mm of the web gradually decrease under vertical force while gradually increasing near the outer radius of 1110 mm of the web. Under lateral force, the Mises stress and strain on the surface of the web remain relatively unchanged regardless of the wheel-rail force application point. Based on the analysis of stress and strain on the surface of the web under different wheel-rail forces, the inner radius of 870 mm is recommended as the optimal mounting location of strain gauges for measuring vertical force, while the inner radius of 1143 mm is suitable for measuring lateral force.
Originality/value
The research findings provide valuable insights for determining optimal strain gauge locations and designing an effective track wheel force measurement system.
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Wenjie Liu, Jing Zhang, Chenfan Wu and Xiangyun Chang
The purpose of this paper is to identify most favorable (or quasi-preferred) industry characteristics of remanufacturing industry and most favorable (or quasi-preferred) industry…
Abstract
Purpose
The purpose of this paper is to identify most favorable (or quasi-preferred) industry characteristics of remanufacturing industry and most favorable (or quasi-preferred) industry factors which have an effect on these characteristics so as to improve these factors.
Design/methodology/approach
Grey system theory has prominent advantage of using few data and uncertainty information to analyze many factors. Therefore, it is more suited for system analysis than traditional statistical analysis methods like regression analysis, variance analysis and principal component analysis, which require massive data, certain probability distribution in the data and few variant factors. So in this paper, grey incidence analysis method, which is an important part of grey system theory, is used to identify industry characteristics and key industry factor of remanufacturing industry in China and then put forward appropriate industrial policies and countermeasures to improve these industry factors.
Findings
According to the results of this study, it reveals that there are no most favorable industry characteristics and no most favorable industry factors in remanufacturing industry of China. “Annual sale of remanufacturing industry” is identified as quasi-preferred industry characteristic, and “total number of employees with master degree or above in remanufacturing enterprise” is identified as the quasi-preferred industry factor. “Total building area of remanufacturing enterprise” is referred as the most unfavorable industry factors.
Practical implications
Judging from the findings of this study, four practical implications are summarized as follows: “annual sale of remanufacturing industry” should be given great importance because it is a quasi-preferred industry characteristic. “Total number of employees with master degree or above in remanufacturing enterprise” and “total number of research institution and university participated in remanufacturing” should be further strengthened by establishing an industry-university-research institute collaboration network, due to the fact that they are the top two quasi-preferred industry factors. “Total investment of remanufacturing industry” and “total annual R&D expenditures” have not played their due role in improving remanufacturing industry, so they should be moderately controlled so as to reduce waste of investment. “Total building area of remanufacturing enterprise” must be strictly controlled because of its little impact on remanufacturing industry.
Originality/value
In this research, grey incidence analysis is applied to identify key industry factors of remanufacturing industry for the first time. It helps in finding industry factors which are in urgent need of improvement and assists in making appropriate industrial policies and countermeasures to improve them by studying relationships between industry characteristic and industry factors.
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Jiaxin Gao, Xin Gu and Xue Yang
This study aims to deliver a new perspective on how the interaction of independent and cooperative innovation affects firm digitization. Based on resource constraint theory, this…
Abstract
Purpose
This study aims to deliver a new perspective on how the interaction of independent and cooperative innovation affects firm digitization. Based on resource constraint theory, this study argues that the aforementioned interaction negatively affects firm digitization. The moderating role of managerial discretion is also discussed in light of the principles of the awareness-motivation-capability (AMC) framework.
Design/methodology/approach
The proposed hypotheses are empirically tested using a negative binomial modeling approach. The data used are from A-share listed companies in China’s Shanghai and Shenzhen stock markets from 2006 to 2020.
Findings
This study suggests that the interaction of independent innovation and cooperative innovation negatively impacts digitization. In addition, this study argues that environmental discretion and organizational discretion weaken the negative impact of the mentioned interaction on digitization. However, additional discretion in the Chinese context has no effect on above relationships.
Originality/value
This study explores the impact of the interaction of independent and cooperative innovation on digitization and incorporates managerial discretion into this framework based on the AMC framework.
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Sherani, Jianhua Zhang, Muhammad Usman Shehzad, Sher Ali and Ziao Cao
This study aims to determine whether knowledge creation processes (KCPs) – knowledge exchange and knowledge integration affect digital innovation (DI), including information…
Abstract
Purpose
This study aims to determine whether knowledge creation processes (KCPs) – knowledge exchange and knowledge integration affect digital innovation (DI), including information technology (IT)-enabled capabilities (ITECs) as a mediator and absorptive capacity (AC) as a moderator.
Design/methodology/approach
With a survey data set of 390 employees from Pakistani software small- and medium-sized enterprises (SMEs), the current study employed Structural Equation Modeling (SEM) using Smart Partial Least Squares to estimate the structural relationships in the conceptual model.
Findings
The results confirm that KCPs – knowledge exchange and knowledge integration positively enhance software SME's DI; ITECs play a partial mediating role in the linkage between KCPs and DI; AC positively moderates the relationship between knowledge integration and ITECs, and ITECs and DI, while AC doesn’t moderate the relationship between knowledge exchange and ITECs. The AC positively moderates the mediating role of ITECs amongst KCPs (knowledge exchange and knowledge integration) and DI, respectively.
Originality/value
This research uniquely integrates the knowledge-based view and dynamic capability theory to present a comprehensive framework that explains the interdependencies between knowledge process, ITECs and AC in driving DI. This approach advances the understanding of how software SMEs can strengthen internal knowledge and IT resources to achieve superior innovation outcomes.
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Joana Morgado Oliveira and Carlos F. Gomes
This study explores how excellence models can leverage digital transformation on the path to sustainable development in organisations.
Abstract
Purpose
This study explores how excellence models can leverage digital transformation on the path to sustainable development in organisations.
Design/methodology/approach
A survey was used to study the different facets of digital capabilities and their impact on sustainable development success of organisations holding an external recognition from the European Foundation for Quality Management (EFQM). Partial Least Squares structural equation modelling (PLS-SEM) combined with Necessary Condition Analysis (NCA) were used to analyse data.
Findings
Internalising excellence practices is decisive in mediating effective digital capabilities to achieve sustainable development. To achieve high levels of sustainable development success, organisations must achieve high levels of excellence practices internalisation, which are much more important than the excellence model external recognition.
Research limitations/implications
This study addresses essential issues with theoretical and practical value but is limited to a sample of organisations with EFQM recognition in two countries. Future studies should address different organisations and cultural environments.
Practical implications
The findings are relevant for organisations facing digital transformation and sustainable development challenges. They are essential for managers leveraging digital capabilities to capitalise on practices and processes and achieve Sustainable Development Goals. Organisations can benefit from a multidimensional approach to digital capabilities when struggling against external challenges.
Originality/value
This study closes a research gap regarding the impact of digital capabilities on sustainable development success. It is the first empirical study to combine sufficiency and necessity conditions analyses to explore the mediating role of excellence practices internalisation and one of the first to address digital capabilities from a multidimensional perspective.
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Yukun Hu, Suihuai Yu, Dengkai Chen, Jianjie Chu, Yanpu Yang and Qing Ao
A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the…
Abstract
Purpose
A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the interaction among evaluators and improve the credibility of evaluation results.
Design/methodology/approach
This paper proposes a multi-stage approach for design concept evaluation based on complex network and bounded confidence. First, a network is constructed according to the evaluation data. Depending on the consensus degree of evaluation opinions, the number of evaluation rounds is determined. Then, bounded confidence rules are applied for the modification of preference information. Last, a planning function is constructed to calculate the weight of each stage and aggregate information at multiple evaluation stages.
Findings
The results indicate that the opinions of the evaluators tend to be consistent after multiple stages of interactive adjustment, and the ordering of design concept alternatives tends to be stable with the progress of the evaluation.
Research limitations/implications
Updating preferences according to the bounded confidence rules, only the opinions within the trust threshold are considered. The attribute information of the node itself is inadequately considered.
Originality/value
This method addresses the need for considering the evaluation information at each stage and minimizes the impact of disagreements within the evaluation group on the evaluation results.
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Yueting Yang, Shaolin Hu, Ye Ke and Runguan Zhou
Fire smoke detection in petrochemical plant can prevent fire and ensure production safety and life safety. The purpose of this paper is to solve the problem of missed detection…
Abstract
Purpose
Fire smoke detection in petrochemical plant can prevent fire and ensure production safety and life safety. The purpose of this paper is to solve the problem of missed detection and false detection in flame smoke detection under complex factory background.
Design/methodology/approach
This paper presents a flame smoke detection algorithm based on YOLOv5. The target regression loss function (CIoU) is used to improve the missed detection and false detection in target detection and improve the model detection performance. The improved activation function avoids gradient disappearance to maintain high real-time performance of the algorithm. Data enhancement technology is used to enhance the ability of the network to extract features and improve the accuracy of the model for small target detection.
Findings
Based on the actual situation of flame smoke, the loss function and activation function of YOLOv5 model are improved. Based on the improved YOLOv5 model, a flame smoke detection algorithm with generalization performance is established. The improved model is compared with SSD and YOLOv4-tiny. The accuracy of the improved YOLOv5 model can reach 99.5%, which achieves a more accurate detection effect on flame smoke. The improved network model is superior to the existing methods in running time and accuracy.
Originality/value
Aiming at the actual particularity of flame smoke detection, an improved flame smoke detection network model based on YOLOv5 is established. The purpose of optimizing the model is achieved by improving the loss function, and the activation function with stronger nonlinear ability is combined to avoid over-fitting of the network. This method is helpful to improve the problems of missed detection and false detection in flame smoke detection and can be further extended to pedestrian target detection and vehicle running recognition.