500 research outputs found
Sort by
Can Rumor Clarification Eliminate the Effects of Rumors?: Evidence From China
No full textThis article analyzes the effects of rumor and official rumor clarification on Chinese stock returns under different rumor conditions using an event study. The results are based on a sample of 832 rumor clarification announcements from China Listed Companies spanning the period of 2015 to 2017. The results show that the average cumulative abnormal return after the rumor event is significantly positive in the positive rumor sample and neutral sample, and significantly negative in the negative rumor sample. After the clarification announcements, we find the announcements effective for the positive and neutral rumor sample, but not in the case of the negative sample. However, by comparing different clarification times of each sample, we find that the earlier the clarification time is, the smaller the impact on the companies in positive and negative rumor examples
How to Integrate Universities and Cities Through Local Spatial Developments: Case Study of Wuhan, China
No full textAs irreplaceable knowledge infrastructures, universities have been acknowledged to play the roles of fostering knowledge workers, supporting knowledge economies, and building knowledge cities. Through spatial developments, localized interactions can be built between cities and universities. There has been a global trend to design new knowledge precincts revolving around universities to make knowledge cities. This article focuses on how the local governments in Wuhan, known as the “Forest of Campus” in China, have proposed the vision of making a “Univercity,” building knowledge cities by integrating universities and cities through local spatial developments. To interpret the concept of the knowledge precinct namely “Univercity,” an analytical framework has been set up in the dimensions of fostering knowledge workers, supporting knowledge economies and building knowledge cities. Then, the spatial strategies of making a “Univercity” have been given accordingly, including enhancing the interaction between universities, knowledge businesses, and knowledge cities
Speed of Use of Social Media as an Antecedent of Speed of Business Internationalization
No full textDespite various advances in international business and entrepreneurship literatures and increasing interest in speed of internationalization mainly among international entrepreneurship scholars, the relationship between the use of social media and the internationalization speed of the firm remains poorly investigated. This article presents the reflective construct “speed of use of social media” and proves its positive effect on the third order formative construct “speed of internationalization.” Furthermore, using multi-group analysis, the article demonstrates that this effect is moderated by the industry where the company performs (business-to-customer vs. business-to-business) and its export intensity, but not by the size of the firm. The results obtained open an interesting area for further research in the role of Web 2.0 and social networking in future knowledge management systems of international new ventures companies
Smart Tourism Empowered by Artificial Intelligence: The Case of Lanzarote
No full textArtificial intelligence (AI) is changing the rules of the game in many industries. This case details how the combination of open innovation and artificial intelligence generates new opportunities in the tourism sector. Specifically, how to create new customer experiences through searching tools, social platforms and cognitive interfaces to make intelligent decisions. The authors show that it is possible to increase tourist satisfaction by offering a set of customized activities and experiences according to their personal characteristics and motivations. The combination of cutting-edge digital technologies makes it possible to design new services in an automated and cost-affordable manner. The experience has been carried out in Lanzarote (Canary Islands, Spain), with support of IBM's Watson system. This is a good example of AI-fueled innovation in services, which is adequate for courses on innovation, technology, entrepreneurship and competitive strategy
Multi-Objective Optimization Methods for Transportation Network Problems: Definition, Taxonomy, and Annotation
No full textThis article recapitulates literature research solving transportation problems and these variants, notably the multimodal transportation problems variants. Moreover, the existing optimization methods critiqued and synthesized their efficiency to solve the transportation problem. This problem can be identified by various criteria and objectives functions that distinguished according to the case study. Based on the existing literature research, a taxonomy is proposed to distinguish different factors and criteria that perform and influence the multi-objective optimization on the transportation network planning problems. The transportation problems are cited according to these objective functions, and the variant of the problem by referring to the previous studies. In this article, the authors have focused their attention on a recent multi-objective mathematical model to solve the planning network of the multimodal transportation problem
Stochastic Modelling of Weather-Related Transmission Line Outages
No full textThe physical environment around transmission lines plays a major role in the resulting reliability of the power network. The inclusion of weather in the failure and repair process will lead to realistic modelling of the power network. This article suggests a modelling methodology to take into account weather-related failures. Besides a maintenance management strategy using dynamic programming, it is suggested to minimizing the cost of maintenance while accounting for weather-related failures. The data obtained from 220kV Transmission lines from Goa, India, is used to stochastically model the phenomenon. A three-state weather model is suggested, and accordingly the failure and repair phenomenon are segregated and stochastically modelled. Time-varying expressions for computing the availability in each weather condition is computed. This model can be used by the power utilities to realistically model weather-related failures
Prediction of Rice Yield via Stacked LSTM
No full textIn order to guarantee the rice yield more effectively, the prediction of rice yield should be taken into account. Because the rice yield every year can be seen as a sequence of time series, many methods applied in prediction of time series can be considered. Long Short-Term Memory recurrent neural network (LSTM) is one of the most popular methods of time series prediction. In consideration of its own characteristics and the popularity of deep learning, an improved LSTM architecture called Stacked LSTM which has multiple layers is proposed in this article. It is based on the idea of increasing the depth of LSTM. The comparison among the Stacked LSTM architectures which have different numbers of LSTM layers and other methods including ARIMA, GRU, and ANN has been carried out on the data of rice yield in Heilongjiang Province, China, from 1980 to 2017. The results showed the superior performance of Stacked LSTM and the effectiveness of increasing the depth of LSTM
Business Intelligence for Human Capital Management
No full textThis article presents the results of an exploratory study of the use of business intelligence (BI) tools to help to make decisions about human resources management in Portuguese organizations. The purpose of this article is to analyze the effective use of BI tools in integrating reports, analytics, dashboards, and metrics, which impacts on the decision making the process of human resource managers. The methodology approach was quantitative based on the results of a survey to 43 human resource managers and technicians. The data analysis technique was correlation coefficient and regression analysis performed by IBM SPSS software. It was also applied qualitative analysis based on a focus group to identify the impacts of business intelligence on the human resources strategies of Portuguese companies. The findings of this study are that: business intelligence is positively associated with HRM decision-making, and business intelligence will significantly predict HRM decision making. The research also examines the process of the information gathered with BI tools from the human resources information system on the decisions of the human resources managers and that impacts the performance of the organizations. The study also gives indications about the practices and gaps, both in terms of human resources management and in processes related to business intelligence (BI) tools. It points out the different factors that must work together to facilitate effective decision-making. The article is structured as follows: a literature review concerning the use of the business intelligence concept and tools and the link between BI and human resources management, methodology, and the main findings and conclusions
Scheduling Aircraft Ground Handling Operations Under Uncertainty Using Critical Path Analysis and Monte Carlo Simulation: Survey and Research Directions
No full textAircraft ground handling is an integral part of airline operations. Although ground handling operations usually are straightforward, it could be very complicated in certain situations, such as troubling cargo loading and unloading incidents, weather conditions or improper use of equipment and breakdowns. Ground handlers need to orchestrate a number of activities within a confined area around airplane in a short period of time. Punctuality is important for airlines and resulting increased efficiencies. In this article, scheduling aircraft ground handling operations with uncertain durations using the critical path analysis and Monte Carlo simulation is considered with the aim of improving aircraft ground services during the turnaround. Having an accurate estimate of aircraft turnaround time considering its type and load, the recourses would be assigned to the ground operations more efficiently. A case study of a long-range wide-body twin-engine jet aircraft is discussed in detail. The results indicate that the proposed method gives improved scheduling relative to the routines observed at a hub airport
Digital Badge Use in Specific Learner Groups
No full textAs educational technology continues to advance, new technologies continue to enter the scene that seek to enhance the delivery and reception of learning in both academic and industry settings. Digital badges are a recent educational innovation that has unique characteristics and capabilities that can allow for individualized pathways for learning and are being implemented in a variety of settings and for multiple purposes. This article reviews the literature on digital badges and four of their core theoretical underpinnings – behaviorism, goal-setting, constructivism, and gamification theory – as well as empirical studies that highlight the contexts and specific learner groups in which digital badges are being utilized. This review contributes to both scholarly research and practical applications of digital badges and offers potential directions for future research involving digital badges