Browsing by Subject "Artificial intelligence"
  • Item
    Applications of artificial intelligence for strategic management of organisation
    (Bangkok : Assumption University, 2022) Somsit Duangekanong
    Artificial intelligence (AI) is a new tool for organisational and strategic development which has not much been investigated. Therefore, this research investigates perceptions of strategic management experts about the future of Artificial Intelligence and its usage in strategic management. To achieve the research objective, a survey of strategic management specialists, including organisational strategy managers, consultants and academics (n = 231) was conducted. The research used the modified unified theory of acceptance and use of technology (UTAUT) model to investigate the factors that could contribute to an adoption of AI in the strategic management process of organisation. Within this model, situational factors include technological capability and organisational culture. The study showed all relationships of variables within the model were significant. The strongest effect on adoption intention was from technological readiness, while the effect of performance expectancy and effort expectancy was fully mediated. Furthermore, organisational culture had a significant effect on the adoption intention. The implication of these findings is that there is a need to consider utility and ethics of AI implementation for strategic management. There were several limitations of the study, including geographic focus and inclusion of specific adoption factors. In addition, more research is needed to examine AI adoption for strategic management.
  • Item
  • Item
  • Item
  • Item
    An Effective Model for Case-Based Maintenance in Cased-Based Reasoning Systems
    ( 2015-11) Adtha Lawanna
    Case-based reasoning systems have been applied for machine learning, artificial intelligence, knowledge-based systems and other related fields in order to provide the right solution to the right problem regarding the four processes, which are the process to retrieve, reuse, revise, and retain cases. This paper focuses on the last process because it produces two main problems, which are the size of a case base increase and the ability of preserving the competency decreases. These critical issues are occurring when repeating the cycles of case-based reasoning. Consequently, the case-based maintenance methods are developed to handle the situations. Accordingly, this paper proposes an effective model for case-based maintenance in casebased reasoning systems to give the best results compared with random, utility, footprint, footprint and utility deletion including case addition algorithm. By running the seven comparative studies on ten datasets retrieved from the machine learning repository, especially to study the efficiency of each algorithm in terms of reducing the size of the case base by selecting the small number of case solutions and preserving the competency after the maintenance systems are applied. According to experimental results, the effectiveness of the proposed model for storing the number of case solution gives the lower size of a case base, when compared with the existing techniques about 34.34%-114.84%. Besides, the percentage of adapting solutions for the traditional methods are lower than the proposed model as about 1.12-6.64 times, including the percent solving problem is lower than the effective model approximately 4.73%-33.55%.
  • Item
    Handling Covid-19 pandemic crisis to sustain the hotels business
    (Assumption University Press, 2020) Suanghatai Trongjitraksa ; Batra, Adarsh
    Crisis management is a necessary factor in successful digital tactics. In the crisis period, the hospitality industry needs to think wisely to develop a prevention plan quickly, communicate with employees and guests, and make critical shifts to successful revenue management and digital strategy. The study aims to understand the impact of Covid-19 on the hotel industry and to summarize how hotels handle with this pandemic situation. As well as, this study is focusing on what kind of prevention that hotels use to handle with Covid-19 pandemic, what are the recovery process and plan that hotels use to sustain the business after the crisis, and what strategies hotels applied to manage within the organization. The researcher chose a qualitative method with an in-depth interview to collect information from asking 15 questions. The data was collected from eight hotels based in Bangkok and Chonburi province with nine managers. The collection data doing were done from June 22, 2020 to July 8, 2020. The Thematic Analysis technique was applied to analyze. According to this study, the researcher found that Artificial Intelligence is very helpful for back of the house of hotel for productive, validity and capacity and Keep in touch to customer is very necessary to remind them and not forget them. They will feel impress with every massage, email, and call from hotels.
  • Item
  • Item
  • Item
  • Item
  • Item
    Robust forex trading with Deep Q Network (DQN)
    (Bangkok : Assumption University, 2019) Sutta Sornmayura
    Financial trading is one of the most attractive areas in finance. Trading systems development is not an easy task because it requires extensive knowledge in several areas such as quantitative analysis, financial skills, and computer programming. A trading systems expert, as a human, also brings in their own bias when developing the system. There should be another, more effective way to develop the system using artificial intelligence. The aim of this study was to compare the performance of AI agents to the performance of the buy-and-hold strategy and the expert trader. The tested market consisted of 15 years of the Forex data market, from two currency pairs (EURUSD, USDJPY) obtained from Dukascopy Bank SA Switzerland. Both hypotheses were tested with a paired t-Test at the 0.05 significance level. The findings showed that AI can beat the buy & hold strategy with significant superiority, in FOREX for both currency pairs (EURUSD, USDJPY), and that AI can also significantly outperform CTA (experienced trader) for trading in EURUSD. However, the AI could not significantly outperform CTA for USDJPY trading. Limitations, contributions, and further research were recommended.
  • Item
  • Item
  • Item
    The trial of commander data
    (Bangkok : Assumption University, 2019) Pattarawin Tipkrailash ; Clark, Michael
    This paper’s aim is to explore the moral topics raised in the TV series “Star Trek: The Next Generation” Season 2 Episode 9 entitled “Measure of Man”. In this episode Commander Data, an Android, is put on trial to determine if can be considered human, or if he has the same rights as a human being. This paper discusses ethical issues raised by this trial. Picard’s argument in defence of Data appeals to epistemological doubts about whether or not Data is sentient. But this paper will take an alternative approach. It will show how inanimate objects can also possess a value which demand ethical obligations from sentient beings. It will also show how the trial reflects back on human morality and the measure of man refers less to the audience and more to the human beings conducting and observing the trial.