Browsing by Author "Shan, Lom Hui"

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Artificial Intellegence and Porter's Five Forces: An Integration
(Department of Marketing Management, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2021) Wen, Chue Kar; Shan, Lom Hui; Adeline, Y. L.; Chin, Thoo Ai
The influx of Artificial Intelligence (AI) into Marketing has been surging in recent years in various disciplines of Marketing, however the research are only limited to macro-level analyses. Academic criticisms have been built up on Porter's Five Forces (P5F) that the model is limited to macro-level perspective in measuring the attractiveness (or profitability) of an industry, and no longer up to date to latest business practices. It is noticeable that only a few research introduced or integrated technological advancement into the P5F model to keep the P5F model relevant to the modern business world. AI is capable of sensing, reasoning, and acting; especially reasoning is being focused in the recent researches that aims to develop human reasoning into machines to activate them thinking and acting like humans, undertake more complex work and making better informed decisions. The Three-stage Framework idealised by Huang and Rust (2021) consists of Mechanical AI, Thinking AI, and Feeling AI that are applied coherently into each element in the Porter's Five Forces. The Mechanical AI is to perform repetitive or routine work such as data collection; Thinking AI is to process and analyse the data to decision making (without being needed to supervise); and Feeling AI is to perform communication with humans (e.g. customers). The process is looping back to the mechanical AI as there would be feedbacks from humans as inputs. The integration of the Three-stage Framework as a concept of AI categorises Porter's Five Forces into more micro-level on the analysis of the industry, that would ultimately enhance the relevancy of Porter's Five Forces in the modern and ever-changing business environment. This paper aims to integrate Artificial Intelligence into Porter's Five Forces to enhance the relevancy of the model into the latest business practices, by integrating a conceptual model in Artificial Intelligence, Three-stage Framework into Porter's Five Forces. Each element in P5F including Threat of New Entrants, Bargaining Power of Supplier, Threat of Substitution, Bargaining Power of Customers and Degree of Rivalry are integrated with the Three-Stage Framework. The integration would enhance the content of P5F hence P5F would provide researchers to analyse the industry more effectively. Some underlying factors that may be hidden during research may be highlighted or observed by AI. Other than being more analytic, the model could be more predictive in analysing the level of competitiveness and competitors' activities. Conceptually, the integration of the ThreeStage Framework into P5F would create a more possibilities for the market entrants, both suppliers and customers, substitutions, subsequently increases the degree of rivalry and ultimately enhances the attractiveness and profitability of an industry. Following the technological trend, the applications of Artificial Intelligence programs will generally enhance the marketing content in Porter's Five Forces that makes it more relevant in the current and future business environment. This study is currently limited to conceptual research, as the practicality of some AI functions are not yet matured. The conceptual integration of the Three-Stage Framework into P5F could be further discovered in specific industries for more empirical results.
Continuance Intention to Use Mobile Payments in Malaysia: Integrating Innovation Resistance Theory and Switching Cost
(Department of Marketing Management, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2021) Sin, Tiong Jia; Shan, Lom Hui; Shollunayagam, Renugala D/O M.; Dyana, Chang Mui Ling
Over recent years, the traditional payment method (i.e. cash) has been gradually replaced by cashless payment. Malaysian mobile payment users are gradually adapting to the new payment method (i.e. cashless payment). This indicates that the usage of cashless payment shows a current popularity trend in the daily routines of people. Furthermore, the Covid19 outbreak has become a catalyst to boost the usage of mobile payments among the mobile users. In Malaysia, mobile payment transactions accounted for a significant proportion in the total amount of annual transactions. According to the Malaysian Communications and Multimedia Commission (2020), the total cashless transactions in 2019 was higher than the past two years which was RM 18.2 billion made from 2094 million transaction. Up to date, Malaysians are using electronic wallets (i.e. Grab, Touch n Go, Boost and others) and Quick Response (QR) payment (i.e. QR code available in mobile banking applications) to conduct their mobile payments. The Innovation Resistance Theory has been applied in this study to provide a better insight of continuance intention of using mobile payments. Moreover, this theory attempts to identify the barriers that are faced by users when they try to adopt a new innovation. The purpose of this study is to examine the relationship between different barriers (i.e. usage barrier, value barrier, risk barrier, tradition barrier and image barrier) and switching cost with respect to the continuance intention of Malaysian mobile payment users to use mobile payment. This study was conducted through a quantitative method. The purposive sampling method has been chosen because the respondents must have usage experience of mobile payment in order to quality to answer the survey. Data collection was collected through self-administrated survey responses. In order to ensure the research instrument was suitable in the Malaysian context, a questionnaire was adopted and adapted which underwent a pilot test to affirm it was feasible for model testing and hypothesis checking. The results of the pilot study reflected that the reliability and discriminant validity of the 34 questions instrument was well established, and this instrument could be applied in the future. Also, the partial least squares-based structural equation modelling was used for analysing the data once the data collection was completed. In short, this research framework is applicable in the future since mobile payment is a common trend in Malaysia. This study contributes to the theory by including switching cost and applying it into the continuance intention to use mobile payment services. It is believed that the study will be able to assist the marketers to remove those barriers which inhibit the mobile users from further use of the cashless payment service. Also, they might benefit from creating a better design mechanism for the applications which can continuously improve their mobile payment service in the future.
Designing Social Media Brand Communication Strategies to Enhance Brand Equity of an Electronic Components Retailer
(Department of Marketing Management, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2021) Chin, Thoo Ai; Syapri, Fitri Nurliza; Sulaiman, Zuraidah; Shan, Lom Hui
Social media is booming massively, and it has become part of billions of people's daily live around the world. Hence, many firm use social media platform to reach out to bigger audience and increase brand equity. In Malaysia, many companies take the opportunities of leveraging social media communication into their business model. However, some businesses like electronics component retailers rarely use social media for marketing. For instance, a small company selling electronics parts is facing a problem to promote their brand to local and online community. Thus, this study aims to investigate factors to increase its brand equity (brand awareness and perceived quality) via social media brand communication, then design marketing strategies for the company. The quantitative method is used in this research, and a questionnaire instrument is used to gather primary data from respondents online using Google Forms. The target population for this study is 150. This study is expected to be a guideline for the company to use firm and user generated content communication on social media to improve the brand equity.
Detecting Fraudulent Financial Reporting and Predicting Business Failure Using Probabilistic Neural Network: Malaysia Chapter
(Department of Marketing Management, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2021) Wen, Chue Kar; Sin, Tiong Jia; Shan, Lom Hui; Dyana, Chang Mui Ling
Methodologies with the integration of machine learning (ML) into fraudulent financial reporting (FFR) and business failure detection have been researched popularly globally however these ML methodologies were not popular researched in Malaysia Specifically. Studies showed that Probabilistic Neural Network (PNN) yielded highest fraudulent detection rate about 98%; and Neural Network achieved overall accuracy of 84% of business failure detection rate. It was also found that there was no specific method mentioned in Malaysia Securities Commission Act 1993 in assessing the financial statements of public listed companies (PLCs), and low expenditure of PLCs in audit functions. Due to the huge impacts resulted from FFR and business failure of public listed companies, there is a need to minimise FFR and business failure incidents with high accuracy detection and prediction tools, which are ML techniques. The applications of ML technique (i.e., PNN) into the research would shorten the analysis time compared to other statistical methods; yield higher accuracy rate that becomes effective layer of screening financial statements; is able to optimise or minimise the loss functions if discrepancies occur in data sets. On the other hand, although the relationship between FFR and business failure has been linked, the two topics have been studied separately in the past. Financially distressed companies may have a higher probability to commit fraudulent financial reporting, and less research that link the two topics although the methodologies and models were found effective in research the two topics. This study aims to firstly determine the accuracy of ML technique, i.e. PNN in the detection of FFR and detection of business failures among the public listed companies in Malaysia. The relationship between business failure and FFR among the PLCs in Malaysia would be identified. This study applies two stage PNN procedures: first stage is to detect FFR among the companies; second stage is to predict business failure of the companies prior to the conduct of FFR. The accuracy of PNN in the applications and the relationship between FFR and business failure will be discovered. Secondary data is to be collected through financial reports from the PLCs that have been identified fraudulent by the Securities Commission Malaysia in the past. A set of identical non-fraudulent and non-failed companies (similar size in same industries) would be as pairs to the fraudulent companies in the study. PNN is expected to yield high accuracy rates in detecting fraudulent companies and predicting business failures. The ML methodology would also be expected to detect the relationship between FFR and business failure (as supported by fraud triangle theory that financial distress is one of the elements in committing frauds). The research should enhance the detectability of frauds and business failures among the PLCs, improves overall corporate governance of the companies and increase public confidences onto PLCs; furthermore, this would also enhance the knowledge of forensic accounting in Malaysia.
Marketing Remedies to Increase the Purchase Intention of a Robotics Academy Centre
(Department of Marketing Management, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2021) Chin, Thoo Ai; Quan, Woon Zeng; Tat, Huam Hon; Shan, Lom Hui
Malaysia has transformed the education system by launching the Science, Technology, Engineering, Mathematics (STEM) education and implemented the STEM in all schools in Malaysia at the beginning of 2017. Through exposure to STEM, children gain the opportunities to learn the concepts of science and mathematics. The focus on hands-on learning with real-world applications helps to develop many skills for children such as creativity, innovative skills and allows them to explore STEM careers at an early age. These changes have triggered how robotics academies compete for resources and competitive advantage. Most robotic academies provide the latest innovative ways to engage students in STEM. The study will use one of the leading educational robotics and coding academies in Malaysia as the case study. Many of the robotics centers are using social media marketing effectively to increase brand awareness and purchase intention. However, the selected academy is facing low brand awareness and low purchase intention. Therefore, this study aims to investigate factors that increase the purchase intention of robotic education and design social media marketing strategies for the company. The questionnaire is distributed to collect data from parents in Skudai, Johor who have children aged from 5 to 17 years old using a judgmental sampling technique. This is expected that brand awareness, brand association, and perceived quality will be very important for the academy to increase purchase intention using social media marketing strategies.
Mobile Users Information Privacy Concern in Malaysia: Extended Ducoffe Advertising Value Model
(Department of Marketing Management, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2021) Shan, Lom Hui; Chin, Thoo Ai; Yeik, Koay Kian; Sin, Tiong Jia
Short message service (SMS) advertisement has emerged as one of the fastest growing advertising mediums in Malaysia. This has prompted the banking industry to use SMS for advertisements to conveniently and effectively disseminate information concerning products and services to their target mobile users. The acceptance of SMS mobile advertisement and the privacy concerns of mobile users is important for the banking industry to reach its target consumers. Furthermore, privacy concerns were investigated using the Mobile Users Information Privacy Concerns (MUIPC) model as a moderator on the relationship between attitude and acceptance behaviour. The research framework and hypotheses were developed based on the Ducoffe advertising value and MUIPC models using gratification theory and the communication privacy management theory in banking industry. This study extended the Ducoffe advertising value model to investigate the impact of user attitude with regard to acceptance behaviour of SMS mobile advertisement. A cross-sectional method was used to collect data via an online survey. Purposive sampling technique was employed to collect 413 usable samples from respondents who had previously received bank advertisement via SMS. SMART partial least square structural equation modelling was used for data analysis. Three major findings were found in this study. Firstly, for the Ducoffe extended model, entertainment and informativeness were proven to have a relationship with advertising value. However, the irritation factor was not significantly related to advertising value as most of the Malaysian mobile users were positive about accepting bank advertisements via SMS. Secondly, advertising value was found to be related to attitude, of which attitude also positively influenced the acceptance behaviour of SMS mobile advertisement from banks. Finally, the moderating effect of MUIPC was proven for the relationship between attitude and acceptance behaviour from banks. Overall, the study contributes to the current mobile advertisement literature by understanding the mechanism that would be useful for banks in Malaysia to include the formation of acceptance behaviour and privacy concerns when designing appropriate bank advertisements via SMS.