The research model based on the theory of planned behaviour in combination with other human and organisational factors has made a useful contribution towards explaining compliance behaviour in relation to organisational ISPs, with trust being the most significant factor. In adopting a multidimensional approach to management-user interactions via multidisciplinary concepts and theories to evaluate the association between the integrated management-user values and the nature of compliance towards ISPs among selected health professionals, this study has made a unique contribution to the literature.

Abstract-Leadership styles play an important role to enhance employee's information security awareness and may lead to proper information security compliance behavior. Therefore, the current study aims to investigate the indirect effect of leadership styles on user's information security policies compliance behavior through the extent of information security awareness. Questionnaires survey were done among health Statistical results confirm that transactional leadership style has a direct effect to all information security awareness factors, but the mediation effect on the relationship between transactional leadership and user's information security policies compliance behavior through two intervening variables (severity awareness and benefit of security-countermeasure). Meanwhile, transformational leadership style has a direct effect on benefit of security-countermeasure and no mediation effect with the extent of all the intervening variables. The research findings found that severity awareness and benefit of security-countermeasure awareness were significant predictors of information security policies compliance behavior while susceptibility awareness and perceived barrier were insignificant. Our findings were proven to be beneficial to fellow researchers and management of the organization, especially related to the medical sectors in improving current standards of information security awareness in hospitals.Index Terms-Transformational leadership, transactional leadership, information security awareness, health belief model, information security policies compliance behavior.

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Information security awareness is important among users because it can influence user's behavior towards complying with organization information security policies. Therefore, the current study was conducted to examine information security awareness factors affecting user's compliance behavior towards Health Information System (HIS) security policies based on extended Health Belief Model. The questionnaires were distributed to the respondents at selected public hospitals in Malaysia (N = 454). Statistical results confirm that perceived work experience, perceived severity, perceived benefit, cues to action, self-efficacy and perceived barrier were significant predictors of health information system's security policies compliance behaviour while perceived susceptibility was insignificant. Our findings will prove to be beneficial to fellow researchers and policy makers, especially related to the medical sectors in improving user's behavior toward practicing information security.

The Internet technology and pervasive computing has provided consumers with privileges to shop online. In addition, the Industry 4.0 agenda has placed the business web and the social web as the ecosystem domains, which explains why online shopping is a norm today. While many studies have been conducted to investigate the determinants of consumers’ intention to use online shopping, mixed results are always found, especially when the business take unique approaches for their digital presence. Besides, even though self-efficacy has been studied extensively in information system research, technological complexity has always given a challenge to consumers’ computing ability. Building on the Use and Gratification Theory (GTA) and the Social Cognitive Theory (SCT), this study aims to examine the relationships between entertainment gratification, informative gratification, web irritation and self-efficacy towards individual’s intention to use online shopping. Using the quantitative survey approach, data was collected from 217 young executives who are frequent online shoppers. The results of the structural equation modeling suggest entertainment gratification, informative gratification and self-efficacy are the factors that derive consumers’ intention to shop online. On the other hand, web irritation has no significant relationship with online shopping intention. The findings do not only capture the importance for web retailers to provide adequate buying-selling information and to provide the element of fun to the shopping portals, but it also suggests for the web retailers to provide less complicated online shopping features since consumers’ ability to use the technology determines purchase behavior. The findings serve as future research agenda. Keywords: online business, Use and Gratification Theory (GTA), Social Cognitive Theory (SCT), entertainment gratification, informative gratification, web irritation, self-efficacy

One of the main problems in information security was human error due to improper human behaviour. Therefore, this preliminary study was conducted with aims to identify possible factors that can affect user's compliance behaviour towards information security in terms of two aspects: management support and security technology. Two theories were integrated for development of research framework: I) Theory of Planned Behaviour; II) Theory of Acceptance Model. The respondents of this study were the health professionals and IT officers whereby 42 questionnaires were obtained and verified. Exploratory Factor Analysis (EFA) results revealed that the six factors were obtained: Transactional_Lead-ership_Style, Transformational_Leadership_Style, ISP_Training_Support, PU_Security, PU_Security-Countermeasure and PEOU_ISPs. The higher loadings signalled the correlations of the indicated items with the factors on which they were loaded with each of the correspondence factors achieving score of alpha value above 0.80. According to the descriptive analysis, most of the respondents are agreed with all the indicated factors. The preliminary study facilitates researcher in developing new model that integrates TPB and TAM that can be used to increase knowledge of user's compliance behaviour towards health information system's security.

Mobile shopping application can provide retailers the opportunity for showcasing their brands and shopping experiences to the customers since the use of smartphones are increasing. Therefore, this study was conducted to determine the e-service quality of mobile commerce applications (MCA) in enhancing customer loyalty intention behaviour to purchase the product via MCA among online shoppers in Malaysia through the use of the adapted SERVQUAL model. Additionally, the mediating effect of customer satisfaction on the relationship between MCA service quality dimensions and customer loyalty intention behaviour was studied. A purposive sampling technique was used and 120 data were collected through an online survey. The results for direct testing demonstrate that all the SERVQUAL dimensions were significantly influenced customer satisfaction, except reliability, security and usability. Meanwhile, analysis results for the mediating effects demonstrate that customer satisfaction mediates the relationship of SERVQUAL dimensions (assurance, personalization, responsiveness and information quality) and customer loyalty intention. Even though the SERVQUAL dimensions tested in this study were significant, the effect size is rather small. Nevertheless, all these factors are important to be considered for the improvement of MCA, especially everyone is moving forward to a digital business environment and e-service is regarded to play an important role.

This paper presents an integrated language model to improve document relevancy for text-queries. To be precise, an integrated stemming-lemmatization (S-L) model was developed and its retrieval performance was compared at three document levels, that is, at top 5, 10 and 15. A prototype search engine was developed and fifteen queries were executed. The mean average precisions revealed the S-L model to outperform the baseline (i.e. no language processing), stemming and also the lemmatization models at all three levels of the documents. These results were also supported by the histogram precisions which illustrated the integrated model to improve the document relevancy. However, it is to note that the precision differences between the various models were insignificant. Overall the study found that when language processing techniques, that is, stemming and lemmatization are combined, more relevant documents are retrieved.Keywords: Information retrieval, document relevancy, language modeling, stemming, lemmatization, mean average precision INTRODUCTIONThe use of internet all over the world has caused information size to increase, hence making it possible for large volumes of information to be retrieved by the users. However, this phenomenon also makes it difficult for users to find relevant information, therefore proper information retrieval techniques are needed. Information retrieval can be defined as "a problem-oriented discipline concerned with the problem of the effective and efficient transfer of desired information between human generator and human user" [1]. In short, information retrieval aims to provide users with those documents that will satisfy their information need.Many information retrieval algorithms were proposed, and some of the popular ones include the traditional Boolean model (i.e. based on binary decisions), vector space model (i.e. compares user queries with documents found in collections and computes their similarities), and probabilistic model (i.e. based on the probability theory to model uncertainties involved in retrieving data), among others. Over the years, information retrieval has evolved to include text retrieval in different languages, and thus giving birth to language models. The language model is particularly concerned with identifying how likely it is for a particular string in a specific language to be repeated [2]. A popular technique used in the language model is the N-gram model which predicts a preceding word based on previous N-1 words [3]. Other popular techniques include stemming and lemmatization.