Online Brand Awareness: Determining the Relative Importance of Facebook and Other Strategies among the Malaysian Consumers

The purpose of this study is to determine the relative importance of facebook with other strategies like affiliate marketing and word of mouth in creating online brand awareness. Both exploratory and confirmatory factor analysis is used in the study. The study chooses 303 Malaysian frequent internet users as the respondents. In confirmatory factor analysis, a structural equation modelling (SEM) approach is applied to determine the relationship among the exogenous and endogenous constructs. The study finds facebook as the most influential online brand awareness creating strategies followed by the affiliated marketing and online word of mouth. In creating the online brand awareness; all the strategies have positive influence, however. The study can be a useful guideline for managerial implication in practice

Export performance of Malaysian Telecommunication products: market prospect and challenges

This study tries to examine the export competitiveness of selected telecommunication products by using indicators like Revealed Comparative Advantage (RCA) and Constant Market Share (CMS)analysis and Shift-share method and these are used for identifying potential export markets. The selected four categories of telecommunication products are taken into account on the basis of three digit level Standard International Trade Classification (SITC) for the period between 2000 and 2011. The RCA calculation clearly indicates an increasing strength of comparative advantage of Malaysia, except for the products(SITC-763) and (SITC-764). This is mainly due to the negligible import for these products. The CMS results suggest that export gain s of Malaysia for telecommunication products are largely attributed to the size of the market and also to its competitiveness effects. The CMS analysis also depicts that the competitiveness effect of telecommunication products are subsequently improved in general during the period III and I (2008-11and 2000-03) as compared to those of the period I and II (2000-03and 2004-07) and period II and III (2004-07 and 2008-11).The shift-share indicates that the USA, UK, Netherlands, Switzerlands, Japan and Germany are biggest importing countries of Malaysian telecommunication products although major challenges are the asian countries here

Factors determinant of patients’ satisfaction towards health tourism in Malaysia

Health tourism is a new form of tourism which is increasingly getting popularity around the world. Recently, Malaysia has become a favourite destination for health tourism. In order for Malaysia to attract more health tourists, it is imperative to determine the crucial factors concerning patients’ satisfaction. This research has been designed to analyze the factors that may affect patients’ satisfaction with health tourism, particularly in the context of Malaysia. Specifically, the study tries to examine the relationship between patients’ satisfaction and cost, service quality, motivation, destination image and perceived value. With the aim of achieving these objectives, this study has developed a framework on the basis of prior studies. In addition, data has been collected via self-structured questionnaire from patients visiting Malaysia, specifically Kuala Lumpur for the purpose of health tourism. The collected data from the respective respondents were analyzed through Statistical Package for Social Sciences (SPSS). SPSS has been used in order to assess the demographic profile of the respondents, run exploratory factor analysis and multiple regression analysis. The findings of the study demonstrated that cost, service quality and motivation are significantly related to satisfaction toward health tourism, whereas destination image and perceived value are not

Adaptive Machine Translation with Large Language Models

Consistency is a key requirement of high-quality translation. It is especially important to adhere to pre-approved terminology and adapt to corrected translations in domain-specific projects. Machine translation (MT) has achieved significant progress in the area of domain adaptation. However, real-time adaptation remains challenging. Large-scale language models (LLMs) have recently shown interesting capabilities of in-context learning, where they learn to replicate certain input-output text generation patterns, without further fine-tuning. By feeding an LLM at inference time with a prompt that consists of a list of translation pairs, it can then simulate the domain and style characteristics. This work aims to investigate how we can utilize in-context learning to improve real-time adaptive MT. Our extensive experiments show promising results at translation time. For example, GPT-3.5 can adapt to a set of in-domain sentence pairs and/or terminology while translating a new sentence. We observe that the translation quality with few-shot in-context learning can surpass that of strong encoder-decoder MT systems, especially for high-resource languages. Moreover, we investigate whether we can combine MT from strong encoder-decoder models with fuzzy matches, which can further improve translation quality, especially for less supported languages. We conduct our experiments across five diverse language pairs, namely English-to-Arabic (EN-AR), English-to-Chinese (EN-ZH), English-to-French (EN-FR), English-to-Kinyarwanda (EN-RW), and English-to-Spanish (EN-ES)

Contributing Factors for Turkey Consumption: An Empirical Analysis from Mymensingh City in Bangladesh

The study examined the factors influencing yearly consumption of turkey meat in Mymensingh city area. Data were collected from 60 consumers of turkey meat through Purposive sampling technique and face to face interview. Dummy coding was applied to code independent variables which were categorical in nature and multiple linear regression was carried out to find out the factors influencing consumption of turkey meat. Result indicated that the majority of the consumers (more than 50%) favored taste, color and aroma of turkey meat. The findings also revealed that age (P<0.05) and monthly family income (P<0.01) were significantly influencing yearly consumption of turkey meat among consumers in Mymensingh city. The major difficulty faced by the turkey farmer recognized as unavailability of turkey feed in the market, high price of day-old chick, lack of access to agricultural credit, lack of training and marketing facility and un-availability of vaccines. Analyzing the factors affecting consumption of turkey meat would facilitate in marketing decision making process of the turkey farmers and also deliver information to policy makers of Government as well as Department of Livestock Services to take necessary initiatives and support this alternative meat source to rise as a popular consumer choice

Effectiveness of facebook towards online brand awareness : a study on Malaysian facebook users perspective

The purpose of this study is to determine the relative importance of facbook as compared to other strategies such as affiliate marketing and word of mouth in creating online brand awareness. Both exploratory and confirmatory factor analysis is performed in the study. The study chooses 303 Malaysian frequent internet users as the respondents. In confirmatory factor analysis, a structural equation modelling (SEM) approach is applied to determine the relationship among the exogenous and endogenous constructs. The study finds facebook as the most influential online brand awareness creating strategies followed by the affiliated marketing and online word of mouth. In creating the online brand awareness; all the strategies have positive influence, however. The study can be a useful guideline for managerial implication in practice

Teachers’ perception towards total quality management practices in Malaysian Higher Learning Institutions

The service industry is a rapidly changing industry and this dynamic culture offers a challenge for the service companies to lead or to actually survive in this competitive environment. As the education indus-try is a part of the overall service industry, this raises the need for a solid base to be developed to reach for high quality service in the education industry. Though, adoption of TQM in the higher educational institu-tions is of common practice in the Western world, however, the history of TQM adoption in the Malay-sian higher educational institutions is not very long. Therefore, the main purpose of this study was to identify the factors influencing the level of TQM practices in the Malaysian higher learning institutions based on the teacher’s perceptions. In doing so, this study was conducted in both types of Malaysian higher educational institutions (public and private). Total 300 questionnaires were distributed randomly, out of which 206 were returned. After collecting the data, statistical tests were performed using SPSS and Amos. This study has got satisfactory results. Results also show identical results with the previous studies. However, this study has pointed out that there is still room for improvement that affecting the level of TQM practices in the Malaysian educational institutions. Finally, future directions are provided at the end of the paper

The effect of different media ads on consumer’s purchase intension: a pragmatic exploration on the Bangladeshi fast food industry

Advertisement plays a significant role in terms of product or service characteristics clarification to the customer. Regardless of the advertisement’s types, a customer by the exposure of ads will go through specific steps of awareness. Realizing the current needs, this study aimed to examine the relationship between three different types of advertisements and their influence on the customer’s attitude towards fast food industry in Bangladesh. Data were collected by using convenient sampling method from Dhaka city in Bangladesh. The result of the research shows that, consumers have found the online advertising more interesting compared to media and print ads and its due to the rapid growth of internet users. Finally, based on the findings, some recommendations are proposed

Arabisc: context-sensitive neural spelling checker

Traditional statistical approaches to spelling correction usually consist of two consecutive processes – error detection and correction – and they are generally computationally intensive. Current state-of-the-art neural spelling correction models usually attempt to correct spelling errors directly over an entire sentence, which, as a consequence, lacks control of the process, e.g. they are prone to overcorrection. In recent years, recurrent neural networks (RNNs), in particular long short-term memory (LSTM) hidden units, have proven increasingly popular and powerful models for many natural language processing (NLP) problems. Accordingly, we made use of a bidirectional LSTM language model (LM) for our context-sensitive spelling detection and correction model which is shown to have much control over the correction process. While the use of LMs for spelling checking and correction is not new to this line of NLP research, our proposed approach makes better use of the rich neighbouring context, not only from before the word to be corrected, but also after it, via a dual-input deep LSTM network. Although in theory our proposed approach can be applied to any language, we carried out our experiments on Arabic, which we believe adds additional value given the fact that there are limited linguistic resources readily available in Arabic in comparison to many languages. Our experimental results demonstrate that the pro- posed methods are effective in both improving the quality of correction suggestions and minimising overcorrection

The ADAPT system description for the STAPLE 2020 English-to-Portuguese translation task

This paper describes the ADAPT Centre’s submission to STAPLE (Simultaneous Translation and Paraphrase for Language Education) 2020, a shared task of the 4th Workshop on Neural Generation and Translation (WNGT), for the English-to-Portuguese translation task. In this shared task, the participants were asked to produce high-coverage sets of plausible translations given English prompts (input source sentences). We present our English-to-Portuguese machine translation (MT) models that were built applying various strategies, e.g. data and sentence selection, monolingual MT for generating alternative translations, and combining multiple n-best translations. Our experiments show that adding the aforementioned techniques to the baseline yields an excellent performance in the English-to-Portuguese translation task