Liang Guo, Ruchi Sharma, Lei Yin, Ruodan Lu and Ke Rong
Competitor analysis is a key component in operations management. Most business decisions are rooted in the analysis of rival products inferred from market structure. Relative to…
Abstract
Purpose
Competitor analysis is a key component in operations management. Most business decisions are rooted in the analysis of rival products inferred from market structure. Relative to more traditional competitor analysis methods, the purpose of this paper is to provide operations managers with an innovative tool to monitor a firm’s market position and competitors in real time at higher resolution and lower cost than more traditional competitor analysis methods.
Design/methodology/approach
The authors combine the techniques of Web Crawler, Natural Language Processing and Machine Learning algorithms with data visualization to develop a big data competitor-analysis system that informs operations managers about competitors and meaningful relationships among them. The authors illustrate the approach using the fitness mobile app business.
Findings
The study shows that the system supports operational decision making both descriptively and prescriptively. In particular, the innovative probabilistic topic modeling algorithm combined with conventional multidimensional scaling, product feature comparison and market structure analyses reveal an app’s position in relation to its peers. The authors also develop a user segment overlapping index based on user’s social media data. The authors combine this new index with the product functionality similarity index to map indirect and direct competitors with and without user lock-in.
Originality/value
The approach improves on previous approaches by fully automating information extraction from multiple online sources. The authors believe this is the first system of its kind. With limited human intervention, the methodology can easily be adapted to different settings, giving quicker, more reliable real-time results. The approach is also cost effective for market analysis projects covering different data sources.
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Zhenxing Gong, Jian Zhang, Yujia Zhao and Lei Yin
Burnout among first-line police in China is high. The purpose of this paper is to examine the relationship between feedback environment, feedback orientation, psychological…
Abstract
Purpose
Burnout among first-line police in China is high. The purpose of this paper is to examine the relationship between feedback environment, feedback orientation, psychological empowerment, and burnout as related to the police work.
Design/methodology/approach
An empirical study was conducted with a sample of 437 basic-level policemen and policewomen in the Shandong province of China. Participants completed a series of questionnaires including the supervisor feedback environment scale, feedback orientation scale, psychological empowerment scale, and the Maslach Burnout Inventory.
Findings
The results indicate that police supervisor feedback environment is negatively related to burnout. The relationship between the supervisor feedback environment and burnout is perfectly mediated by psychological empowerment and significantly moderated by feedback orientation. The mediation effect of psychological empowerment is significantly influenced by feedback orientation.
Originality/value
The findings have contributed to answering several recent questions in the feedback-burnout literature. The authors stress that leaders should strive to build a supportive feedback environment for employees.
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Yanfeng Han, Lei Yin, Guo Xiang, Guangwu Zhou, Haizhou Chen and Xiaolin Zheng
The tribological behavior, i.e. friction coefficient and wear rate, and vibration characteristics of the water-lubricated bearing was investigated. The water-lubricated bearing is…
Abstract
Purpose
The tribological behavior, i.e. friction coefficient and wear rate, and vibration characteristics of the water-lubricated bearing was investigated. The water-lubricated bearing is made of three different materials, i.e. polyether-ether-ketone (PEEK), polyimide (PI) and nitrile-butadiene rubber (NBR).
Design/methodology/approach
The tribological behavior was investigated experimentally on a specially designed test rig. Three vibration sensors were used to record the vibration of the bearing.
Findings
The results indicated that the variation of friction coefficient with rotation speed agrees well with the trend of Stribeck curve. The tested friction coefficient of rubber bearing is higher than that of the other two bearings whether it is in the state of mixed-lubrication or hydrodynamic lubrication, and which causing a larger wear rate in rubber bearing. The PEEK bearing exhibits the best tribological properties due to it has smaller friction coefficient and wear rate. However, it can be found that the rubber bearing gives the minimum vibration acceleration, which means that the rubber bearing has the most potential to improve the stability of water-lubricated bearing rotor system.
Originality/value
In this study, a group of experiment studies conducted on a specially designed test rig. The comprehensive performance, including friction coefficient, vibration acceleration and wear rate, of water-lubricated bearing with three different materials, i.e. PEEK, PI and NBR, was compared systematically. The experiment research may offer a reference for the selection of material in water-lubricated bearing in specific operating conditions.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2019-0447/
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Wei Feng, Lei Yin, Yanfeng Han, Jiaxu Wang, Ke Xiao and Junyang Li
This paper aims to explore the possibility of converting the nitrile butadiene rubber (NBR) water-lubricated bearing material into a self-lubricating bearing material by the…
Abstract
Purpose
This paper aims to explore the possibility of converting the nitrile butadiene rubber (NBR) water-lubricated bearing material into a self-lubricating bearing material by the action of polytetrafluoroethylene (PTFE) particles and water lubrication.
Design/methodology/approach
A group of experimental studies was carried out on a ring-on-block friction test. The physical properties, tribological properties and interface structure of PTFE-NBR self-lubricating composites filled with different percentages of PTFE particles were investigated.
Findings
The experimental results indicated that the reduction in friction and wear is a result of the formation of the lubricating film on the surface of the composites. The lubricating film was formed of a large amount of PTFE particles continuously supplied under water lubrication conditions and the PTFE particles here can greatly enhance the load capacity and lubrication performance.
Originality/value
In this study, the tribological properties of PTFE particles added to the NBR water-lubricated bearing materials under water lubrication were investigated experimentally, and the research was carried out by a ring-on-block friction test. It is believed that this study can provide some guidance for the application of PTFE-NBR self-lubricating.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2020-0187/
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Lei Yin, Xiaolin Zheng, Dongxing Tang, Yanfeng Han, Rui Zhao and Yi Chen
This study aims to develop a new method to treat the numerical singularity at the critical nodes of two skew coordinates, and optimize the leakage of micro herringbone grooved…
Abstract
Purpose
This study aims to develop a new method to treat the numerical singularity at the critical nodes of two skew coordinates, and optimize the leakage of micro herringbone grooved journal bearings (MHGJBs) with this method.
Design/methodology/approach
A side leakage numerical algorithm is proposed by using the skew meshes with a virtual node (SMVN) method to evaluate the effects of groove angle, bank/groove ratio, groove depth and groove number on load capacity, friction and side leakage of MHGJB.
Findings
The SMVN method is effective in treating the numerical singularity at the critical nodes of two skew coordinates. Besides, a group of optimized parameters of micro herringbone groove is obtained which can not only minimize the side leakage but also improve the load capacity and friction force.
Originality/value
A virtual node method was proposed, which can significantly improve the calculation accuracy in the side leakage model.
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Linnan Gui, Hui Lei and Phong Ba Le
The purpose of this study is to clarify the effects of transformational leadership (TL) on radical and incremental innovation through the mediating roles of knowledge sharing (KS…
Abstract
Purpose
The purpose of this study is to clarify the effects of transformational leadership (TL) on radical and incremental innovation through the mediating roles of knowledge sharing (KS) behaviors. This study also attempts to bring deeper insight of the correlation among the latent factors by examining how knowledge-centered culture (KCC) moderates the effects of TL on KS behaviors and innovation capability.
Design/methodology/approach
This study conducts a questionnaire survey and Structural Equation Modeling to test the proposal research model based on a sample of 321 participants in 85 service and manufacturing firms.
Findings
The results revealed that KS behaviors significantly mediate the relationship between TL and two types of innovation. Specifically, knowledge collecting has more significant effect on incremental innovation compared with influence of knowledge donating. By contrast, knowledge donating has a greater effect on radical innovation compared with effect of knowledge collecting. The paper also highlights the important role of KCC in enhancing the effects of TL on KS activities and innovation capabilities.
Research limitations/implications
The study has highlighted the important role of KCC as it positively moderates the influences of TL on KS and innovation capability.
Practical implications
The study provides evidence that TL style is the main driving force of KS processes. Managers should prioritize practicing this leadership style to improve employees' KS behaviors and firm's innovation capability.
Originality/value
The study significantly fills the gaps in the literature that emphasizes how KS behaviors induce different impacts on specific aspects of innovation capability. By exploring the moderator of KCC, the paper significantly contributes to advancing the understanding of how transformational leaders foster employees' KS behaviors for improving radical and incremental innovation.
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This study aims to examine how members of Gen Z are impacted by Covid-19, specifically focusing on their professional opportunities, work preferences and future outlook.
Abstract
Purpose
This study aims to examine how members of Gen Z are impacted by Covid-19, specifically focusing on their professional opportunities, work preferences and future outlook.
Design/methodology/approach
A survey consisting of 24 questions including a Likert scale, multiple choice and open-ended was created to understand how members of Gen Z perceive Covid-19 impacting their education, employment, mental health and relationships. The survey was disseminated to employees of a corporate restaurant franchise, Christian college admissions and guidance non-profit, and online through social media including Instagram, Facebook, Reddit and LinkedIn. A total of 517 respondents completed the survey. Survey participants came from 29 states and 6 countries.
Findings
Results highlight Gen Z overwhelmingly values interpersonal connections, wants to Zoom less and work more in-person. The findings help anticipate potential professional gaps due to Covid-19 restrictions, as well as point out how Gen Z is markedly different in terms of workforce trends. Content analysis from an open-ended question reveals the extent of disruption Gen Z has experienced, adversely affecting their career plans and stalling professional development. Yet, despite these setbacks, Gen Z maintains a cautiously optimistic future outlook.
Research limitations/implications
Limitations to the study include the sample is largely comprising White women so the generalizability of results may be limited and the self-reporting nature of the survey may pose problems with method variance.
Practical implications
These findings have implications for Millennials as managers as they identify where resources should be invested including strengthening interpersonal communication skills, providing mentoring opportunities and appealing to their financial conservatism to recruit and retain Gen Z employees. The changes in telecommuting preferences and desire for more interpersonal and in-person communication opportunities highlight how Gen Z is markedly different than previous generations.
Social implications
Gen Z’s optimistic future outlook conveys a sense of resilience and strength in the face of stress. Rather than engaging in cognitive distortions and over generalizations when stressed, results show Gen Z is able to find healthy alternatives and maintain optimism in the face of stress. Additionally, due to the extent of isolation and loneliness Gen Zers reported, the value of in-person connections cannot be overstated. As results convey a sense of being overlooked and missing out on so many rites of passage, inviting Gen Zers to share how they have been impacted, recognizing their accomplishments and listening to them may go a long way to develop rapport.
Originality/value
This study differs from others because it takes a generational look at Covid-19 impacts. The qualitative nature allows us to hear from members of Gen Z in their own words, and as a generational cohort, their voices inform workplace attitudes, practices and managerial procedures.
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Yi‐Long Jaw, Ru‐Yu Wang and Carol Ying‐Yu Hsu
Although the concept of branding has been considered extensively in products and services, branding in Chinese is a relatively emerging phenomenon. This paper aims to present the…
Abstract
Purpose
Although the concept of branding has been considered extensively in products and services, branding in Chinese is a relatively emerging phenomenon. This paper aims to present the enlivenment of branding in Chinese within the cross‐strait markets of Taiwan and Mainland China, which underlies various ideologies.
Design/methodology/approach
This study primarily reviews literatures of brand and brand name translation, defines the essentiality of brand naming, and outlines the branding strategies for entering cross‐strait markets. Furthermore, this study validates the using of substantially interpreted brands that support the authors' four developed propositions.
Findings
This study compares substantially interpreted brands in cross‐strait markets with a reference to commonly used translation methods. The results illustrate interesting ideologies among cross‐strait markets and can help managers achieve global brand recognition.
Research limitations/implications
Since China and Taiwan share the same Chinese culture, the qualitative method proposed by the present authors is more applicable to practitioners who are eager to pursue branding in cross‐strait markets. Thus, the relevant techniques may not be applicable to people less familiar with Chinese culture.
Practical implications
The qualitative case study provides an advisable method for branding in Chinese. The results of this study can provide greater understanding of the various ideologies in cross‐strait markets, as well as help managers achieve global brand recognition.
Originality/value
The various ideologies from branding is complex, especially for those involved with linguistic essentials. Previous research has mainly focused on managerial‐based branding and customer‐based branding. This paper extends the interest into enlivening inspirations.
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Panagiotis Karaiskos, Yuvaraj Munian, Antonio Martinez-Molina and Miltiadis Alamaniotis
Exposure to indoor air pollutants poses a significant health risk, contributing to various ailments such as respiratory and cardiovascular diseases. These unhealthy consequences…
Abstract
Purpose
Exposure to indoor air pollutants poses a significant health risk, contributing to various ailments such as respiratory and cardiovascular diseases. These unhealthy consequences are specifically alarming for athletes during exercise due to their higher respiratory rate. Therefore, studying, predicting and curtailing exposure to indoor air contaminants during athletic activities is essential for fitness facilities. The objective of this study is to develop a neural network model designed for predicting optimal (in terms of health) occupancy intervals using monitored indoor air quality (IAQ) data.
Design/methodology/approach
This research study presents an innovative approach employing a long short-term memory (LSTM) recurrent neural network (RNN) to determine optimal occupancy intervals for ensuring the safety and well-being of occupants. The dataset was collected over a 3-month monitoring campaign, encompassing 15 meteorological and indoor environmental parameters monitored. All the parameters were monitored in 5-min intervals, resulting in a total of 77,520 data points. The dataset collection parameters included the building’s ventilation methods as well as the level of occupancy. Initial preprocessing involved computing the correlation matrix and identifying highly correlated variables to serve as inputs for the LSTM network model.
Findings
The findings underscore the efficacy of the proposed artificial intelligence model in forecasting indoor conditions, yielding highly specific predicted time slots. Using the training dataset and established threshold values, the model effectively identifies benign periods for occupancy. Validation of the predicted time slots is conducted utilizing features chosen from the correlation matrix and their corresponding standard ranges. Essentially, this process determines the ratio of recommended to non-recommended timing intervals.
Originality/value
Humans do not have the capacity to process this data and make such a relevant decision, though the complexity of the parameters of IAQ imposes significant barriers to human decision-making, artificial intelligence and machine learning systems, which are different. Present research utilizing multilayer perceptron (MLP) and LSTM algorithms for evaluating indoor air pollution levels lacks the capability to predict specific time slots. This study aims to fill this gap in evaluation methodologies. Therefore, the utilized LSTM-RNN model can provide a day-ahead prediction of indoor air pollutants, making its competency far beyond the human being’s and regular sensors' capacities.