Ya-Fei Liu, Yu-Bo Zhu, Hou-Han Wu and Fangxuan (Sam) Li
This study aims to explore the differences in the tourists’ perceived destination image on travel e-commerce platforms (e.g. Ctrip and Fliggy) and social media platforms (e.g…
Abstract
Purpose
This study aims to explore the differences in the tourists’ perceived destination image on travel e-commerce platforms (e.g. Ctrip and Fliggy) and social media platforms (e.g. Xiaohongshu and Weibo).
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Liyao Song, Bai Chen, Bo Li, Rupeng Zhu and Dan Wang
The supercritical design of tail rotor drive shaft has attracted more attention in helicopter design due to its high power–weight ratio and low maintenance cost. However, there…
Abstract
Purpose
The supercritical design of tail rotor drive shaft has attracted more attention in helicopter design due to its high power–weight ratio and low maintenance cost. However, there exists excessive vibration when the shaft passes through the critical frequency. Dry friction damper is the equipment applied to the drive shaft to suppress the excessive vibration. In order to figure out the damping mechanism of the dry friction damper and improve the damping efficiency, the dynamic model of the shaft/damper system is established based on the Jeffcott rotor model.
Design/methodology/approach
The typical frequency response of the system is studied through bifurcation diagrams, amplitude-frequency characteristic curves and waterfall frequency response spectrum. The typical transient responses under frequency sweeps are also obtained.
Findings
The results show that the response of the system changes from periodic no-rub motion to quasi-periodic rub-impact motion, and then to synchronous full annular rub-impact, and finally, back to periodic no-rub motion. The slip of the rub-impact ring improves the stability of the system. Besides, the effects of the system parameters including critical dry friction force, rub-impact friction coefficient, initial clearance on the stability and the vibration damping capacity are studied. It is observed that the stability changes significantly varying the three parameters respectively. The vibration damping capacity is mainly affected by the critical dry friction force and the initial clearance.
Originality/value
Presented results provide guidance for the design of the dry friction damper.
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Suzi Elen Ferreira Dias, Edson Sadao Iizuka and Eduardo Pinto Vilas Boas
The purpose of this paper is to understand the theoretical discussion of effectuation since the seminal paper in 2001 and to propose an agenda for future studies.
Abstract
Purpose
The purpose of this paper is to understand the theoretical discussion of effectuation since the seminal paper in 2001 and to propose an agenda for future studies.
Design/methodology/approach
Systematic literature review and content analysis of 71 papers.
Findings
Most papers performed a replication of the concepts empirically, and few studies proposed to understand theoretical aspects of effectuation, among them, some authors presented theoretical advances to improve the approach and others participated in an ongoing debate that shows there is no consensus on whether the approach is theory or if considered, appears to be under construction at a rudimentary level or being questioned.
Research limitations/implications
The method requires authors to make choices, so the database used and the criteria defined for searching papers that were analyzed are the main limitations of this research.
Practical implications
The authors suggest that researchers, teachers and practitioners use effectuation analytically and reflectively.
Social implications
The authors present and analyze the current theoretical debate on effectuation. Results suggest the need for new discussions about the concepts, as well as new theoretical efforts of the researchers to analyze the potentialities and limitations of this approach.
Originality/value
Among empirical and applied research, with replications of the concepts of effectuation, this research contributes to a theoretical discussion based on a systematic literature review, seeking to bring new reflections about this approach. Additionally, the authors present an agenda of theoretical gaps for the development of future research.
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Giancarlo Gomes, Laio Oriel Seman, Ana Clara Berndt and Nadia Bogoni
The purpose of this study is to analyze the relationships between Entrepreneurial Orientation, Organizational Learning Capability, Service Innovation and Organizational…
Abstract
Purpose
The purpose of this study is to analyze the relationships between Entrepreneurial Orientation, Organizational Learning Capability, Service Innovation and Organizational Performance. To this end, it was sought to analyze the mediating role of organizational learning capability and service innovation within entrepreneurial orientation and organizational performance relationship in knowledge-intensive organizations.
Design/methodology/approach
The sample consisted of 159 architecture and urbanism companies from Santa Catarina, Brazil. The study opted to use managers as key informants since they are the ones that have general information about the organization and are a valuable source for assessing the different variables of the organization. For data analysis, the PLS-PM algorithm (Partial Least Squares Path Modeling) was used.
Findings
Results showed that entrepreneurial orientation is a strong driver of service innovation and organizational performance. Organizational learning capability acts as a facilitator of innovation and has a positive influence on organizational performance. Another theoretical contribution of this study to organizational learning capability is the confirmation of its mediation in service innovation and organizational performance. Management needs to make its organization more proactive and creative, continually promoting new ideas. Architecture and urbanism organizations should pay more attention to maintaining and promoting entrepreneurial orientation permanently. The trend toward both proactivity and risk-taking can be an inherent advantage of these knowledge-intensive business services.
Originality/value
Few studies have explored the mediating role of organizational learning capability and service innovations in organizational performance. In particular, the combined effects of entrepreneurial orientation and organizational learning capability have been neglected by the knowledge-intensive organizations literature. The study is justified by providing a more complete view of the relationship between entrepreneurial orientation and the performance of knowledge-intensive organizations, highlighting the role of organizational learning capability and performance in service innovation.
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Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are…
Abstract
Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are limited to 140 characters. This led users to create their own novel syntax in tweets to express more in lesser words. Free writing style, use of URLs, markup syntax, inappropriate punctuations, ungrammatical structures, abbreviations etc. makes it harder to mine useful information from them. For each tweet, we can get an explicit time stamp, the name of the user, the social network the user belongs to, or even the GPS coordinates if the tweet is created with a GPS-enabled mobile device. With these features, Twitter is, in nature, a good resource for detecting and analyzing the real time events happening around the world. By using the speed and coverage of Twitter, we can detect events, a sequence of important keywords being talked, in a timely manner which can be used in different applications like natural calamity relief support, earthquake relief support, product launches, suspicious activity detection etc. The keyword detection process from Twitter can be seen as a two step process: detection of keyword in the raw text form (words as posted by the users) and keyword normalization process (reforming the users’ unstructured words in the complete meaningful English language words). In this paper a keyword detection technique based upon the graph, spanning tree and Page Rank algorithm is proposed. A text normalization technique based upon hybrid approach using Levenshtein distance, demetaphone algorithm and dictionary mapping is proposed to work upon the unstructured keywords as produced by the proposed keyword detector. The proposed normalization technique is validated using the standard lexnorm 1.2 dataset. The proposed system is used to detect the keywords from Twiter text being posted at real time. The detected and normalized keywords are further validated from the search engine results at later time for detection of events.
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Balamurugan Souprayen, Ayyasamy Ayyanar and Suresh Joseph K
The purpose of the food traceability is used to retain the good quality of raw material supply, diminish the loss and reduced system complexity.
Abstract
Purpose
The purpose of the food traceability is used to retain the good quality of raw material supply, diminish the loss and reduced system complexity.
Design/methodology/approach
The proposed hybrid algorithm is for food traceability to make accurate predictions and enhanced period data. The operation of the internet of things is addressed to track and trace the food quality to check the data acquired from manufacturers and consumers.
Findings
In order to survive with the existing financial circumstances and the development of global food supply chain, the authors propose efficient food traceability techniques using the internet of things and obtain a solution for data prediction.
Originality/value
The operation of the internet of things is addressed to track and trace the food quality to check the data acquired from manufacturers and consumers. The experimental analysis depicts that proposed algorithm has high accuracy rate, less execution time and error rate.
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In this research, the authors demonstrate the advantage of reinforcement learning (RL) based intrusion detection systems (IDS) to solve very complex problems (e.g. selecting input…
Abstract
Purpose
In this research, the authors demonstrate the advantage of reinforcement learning (RL) based intrusion detection systems (IDS) to solve very complex problems (e.g. selecting input features, considering scarce resources and constrains) that cannot be solved by classical machine learning. The authors include a comparative study to build intrusion detection based on statistical machine learning and representational learning, using knowledge discovery in databases (KDD) Cup99 and Installation Support Center of Expertise (ISCX) 2012.
Design/methodology/approach
The methodology applies a data analytics approach, consisting of data exploration and machine learning model training and evaluation. To build a network-based intrusion detection system, the authors apply dueling double deep Q-networks architecture enabled with costly features, k-nearest neighbors (K-NN), support-vector machines (SVM) and convolution neural networks (CNN).
Findings
Machine learning-based intrusion detection are trained on historical datasets which lead to model drift and lack of generalization whereas RL is trained with data collected through interactions. RL is bound to learn from its interactions with a stochastic environment in the absence of a training dataset whereas supervised learning simply learns from collected data and require less computational resources.
Research limitations/implications
All machine learning models have achieved high accuracy values and performance. One potential reason is that both datasets are simulated, and not realistic. It was not clear whether a validation was ever performed to show that data were collected from real network traffics.
Practical implications
The study provides guidelines to implement IDS with classical supervised learning, deep learning and RL.
Originality/value
The research applied the dueling double deep Q-networks architecture enabled with costly features to build network-based intrusion detection from network traffics. This research presents a comparative study of reinforcement-based instruction detection with counterparts built with statistical and representational machine learning.
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Haitao Ding, Wei Li, Nan Xu and Jianwei Zhang
This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected…
Abstract
Purpose
This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected environment.
Design/methodology/approach
In this paper, an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed for connected EVs. The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving. Moreover, this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.
Findings
To illustrate the performance for the EEDC-HRL, the controlled EV was trained and tested in various traffic flow states. The experimental results demonstrate that the proposed technique can effectively improve energy efficiency, without sacrificing travel efficiency, comfort, safety and lane-changing performance in different traffic flow states.
Originality/value
In light of the aforementioned discussion, the contributions of this paper are two-fold. An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs. A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.
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Qiang Yang, Jiale Huo, Hongxiu Li, Yue Xi and Yong Liu
This study investigates how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' purchasing and gift-giving behaviors and how broadcaster…
Abstract
Purpose
This study investigates how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' purchasing and gift-giving behaviors and how broadcaster popularity moderates social interaction-oriented content's effect on the two different behaviors in live-streaming commerce.
Design/methodology/approach
A research model was proposed and empirically tested using a panel data set collected from 537 live streams via Douyin (the Chinese version of TikTok), one of the most popular live broadcast platforms in China. A fixed-effects negative binomial regression model was used to examine the proposed research model.
Findings
This study's results show that social interaction-oriented content in broadcasters' live speech has an inverted U-shaped relationship with broadcast viewers' purchasing behavior and shares a positive linear relationship with viewers' gift-giving behavior. Furthermore, broadcaster popularity significantly moderates the effect of social interaction-oriented content on viewers' purchasing and gift-giving behaviors.
Originality/value
This research enriches the literature on live-streaming commerce by investigating how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' product-purchasing and gift-giving behaviors from the perspective of broadcast viewers' attention. Moreover, this study provides some practical guidelines for developing live speech content in the live-streaming commerce context.
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Misbah Faiz, Naukhez Sarwar, Adeel Tariq, Ricardo Vinícius Dias Jordão and Mumtaz Ali Memon
Strategic human capital analytics (SHCA) has proven to be promising for improved organizational performance; however, research remains unclear about its influence on new venture…
Abstract
Purpose
Strategic human capital analytics (SHCA) has proven to be promising for improved organizational performance; however, research remains unclear about its influence on new venture performance. Building on the dynamic capabilities view (DCV), this study investigates the relationship between SHCA and new venture performance via generative capabilities with the moderating role of dual nationality founding members.
Design/methodology/approach
A quantitative research study has been carried out. Data was collected via a survey form from 313 founding members of new tech ventures and analyzed using Hayes process macro model.
Findings
Research results show that the generative capability mediates the linkages between SHCA and new venture performance. Whereas, the dual nationality of a founding member strengthens the linkages between SHCA and generative capability due to their diverse perspective, larger networks, cognitive flexibility, and resilience, which are important for generative capabilities and SHCA.
Originality/value
The originality of these results lies in the exploration of the linkages between dual nationality and generative capability, as well as the special elements, such as diverse perspectives, larger networks, cognitive flexibility, and resilience, which are highlighted as possible advantages of dual nationality in the context of SHCA and new venture performance.