Journal of Systems and Information Technology

Phung, Van Dong; Hawryszkiewycz, Igor; Chandran, Daniel

2019 Journal of Systems and Information Technology

doi: 10.1108/jsit-11-2018-0148

Studies have examined the influence of knowledge-sharing factors on attitudes and intentions to share knowledge; thus, there is a need to add to the limited research to examine individuals’ actual knowledge-sharing behaviour (KSB). Drawing upon the social cognitive theory (SCT) and transformational leadership, this study aims to develop a new research model which modifies the standard SCT model and augments it with other theories to examine academics’ KSBs.Design/methodology/approachQuestionnaire surveys based on literature and pilot study were conducted with 785 academic staff from four Vietnamese public universities. This study applied structural equation modelling to test the proposed research model and hypotheses.FindingsThe findings show that environmental factors (subjective norms, trust) and personal factors (knowledge self-efficacy, enjoyment in helping others) had positive impacts on KSB; KSB had a strongly positive effect on innovative behaviour; and transformational leadership positively moderated the effects of subjective norms, trust and knowledge self-efficacy on KSB. Interestingly, psychological ownership of knowledge was found to have insignificant associations with KSB.Practical implicationsThe study findings can be used by university leaders, academic staff and researchers in other similar contexts.Originality/valueUntil now, to the best of the researchers’ knowledge, no studies have applied SCT as a primary lens, in which transformational leadership positioned in a focal behaviour also affected KSB, to investigate research on KSB in organisations, especially in institutions of higher education.

Afolabi, Adekunle Oluseyi; Toivanen, Pekka

2019 Journal of Systems and Information Technology

doi: 10.1108/jsit-01-2019-0019

The roles recommendation systems play in health care have become crucial in achieving effective care and in meeting the needs of modern care giving. As a result, efforts have been geared toward using recommendation systems in the management of chronic diseases. Effectiveness of these systems is determined by evaluation following implementation and before deployment, using certain metrics and criteria. The purpose of this study is to ascertain whether consideration of criteria during the design of a recommendation system can increase acceptance and usefulness of the recommendation system.Design/methodology/approachUsing survey-style requirements gathering method, the specific health and technology needs of people living with chronic diseases were gathered. The result was analyzed using quantitative method. Sets of harmonized criteria and metrics were used along with requirements gathered from stakeholders to establish relationship among the criteria and the requirements. A matching matrix was used to isolate requirements for prioritization. These requirements were used in the design of a mobile app.FindingsMatching criteria against requirements highlights three possible matches, namely, exact, inferential and zero matches. In any of these matches, no requirement was discarded. This allows priority features of the system to be isolated and accorded high priority during the design. This study highlights the possibility of increasing the acceptance rate and usefulness of a recommendation system by using metrics and criteria as a guide during the design process of recommendation systems in health care. This approach was applied in the design of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People. The result has shown that with this method, it is possible to increase acceptance rate, robustness and usefulness of the product.Research limitations/implicationsInability to know the evaluation criteria beforehand, inability to do functional analysis of requirements, lack of well-defined requirements and often poor cooperation from people living with chronic diseases during requirements gathering for fear of stigmatization, confidentiality and privacy breaches are possible limitations to this study.Practical implicationsThe result has shown that with this method, it is possible to isolate more important features of the system and use them during the design process, thereby speeding up the design and increasing acceptance rate, robustness and usefulness of the system. It also helps to see in advance the likely features of the system that will enhance its usefulness and acceptance, thereby increasing the confidence of the developers in their ability to deliver a system that will meet users’ needs. As a result, developers know beforehand where to concentrate their efforts during system development to ascertain the possibility of increasing usefulness and acceptance rate of a recommendation system. In addition, it will also save time and cost.Originality/valueThis paper demonstrates originality by highlighting and testing the possibility of using evaluation criteria and metrics during the design of a recommender system with a view to increasing acceptance and enhancing usefulness. It also shows the possibility of using the metrics and criteria in system’s development process for an exercise other than evaluation.

Abu Ghazaleh, Mohamad; Abdallah, Salam; Zabadi, Abdelrahim

2019 Journal of Systems and Information Technology

doi: 10.1108/jsit-05-2018-0073

Despite the importance of post-implementation activities to support the success of an enterprise resource planning (ERP) system, there has been a lack of research into the factors that influences post-implementation success. Accordingly, this paper aims to present a case study on a public service organization operating in an emerging market economy, namely, the United Arab Emirates in the ERP post-implementation phase to understand the internal forces within the organization that influences ERP system success.Design/methodology/approachA qualitative method using focus group discussions (FGDs) was conducted based upon IT data from the firm and interviews with IT staff, business users and executive management to identify system users’ perceptions in post ERP.FindingsThe authors posit that the internal organizational forces of ongoing support, system user interactions and stakeholder views significantly affect post-implementation capabilities and user satisfaction.Research limitations/implicationsIT professionals and stakeholders believe that identification of the factors determining post-implementation ERP capabilities and user satisfaction should not be limited to specific practices.Practical implicationsThis study provides insights that can assist CIOs and ERP professionals in the service industry to examine the extent of obstructions to post-implementation capabilities that will impact system user satisfaction.Originality/valueUse of FGDs to explore the impact of ERP capabilities upon system user satisfaction in the service sector. The study is one of the first that utilizes Technological frames of reference (TFR) theory in studying ERP post-implementation.

Angskun, Thara; Angskun, Jitimon

2019 Journal of Systems and Information Technology

doi: 10.1108/jsit-03-2018-0046

This paper aims to introduce a hierarchical fuzzy system for an online review analysis named FLORA. FLORA enables tourists to decide their destination without reading numerous reviews from experienced tourists. It summarizes reviews and visualizes them through a hierarchical structure. The visualization does not only present overall quality of an accommodation, but it also presents the condition of the bed, hospitality of the front desk receptionist and much more in a snap.Design/methodology/approachFLORA is a complete system which acquires online reviews, analyzes sentiments, computes feature scores and summarizes results in a hierarchical view. FLORA is designed to use an overall score, rated by real tourists as a baseline for accuracy comparison. The accuracy of FLORA has achieved by a novel sentiment analysis process (as part of a knowledge acquisition engine) based on semantic analysis and a novel rating technique, called hierarchical fuzzy calculation, in the knowledge inference engine.FindingsThe performance comparison of FLORA against related work has been assessed in two aspects. The first aspect focuses on review analysis with binary format representation. The results reveal that the hierarchical fuzzy method, with probability weighting of FLORA, is achieved with the highest values in precision, recall and F-measure. The second aspect looks at review analysis with a five-point rating scale rating by comparing with one of the most advanced research methods, called fuzzy domain ontology. The results reveal that the hierarchical fuzzy method, with probability weighting of FLORA, returns the closest results to the tourist-defined rating.Research limitations/implicationsThis research advances knowledge of online review analysis by contributing a novel sentiment analysis process and a novel rating technique. The FLORA system has two limitations. First, the reviews are based on individual expression, which is an arbitrary distinction and not always grammatically correct. Consequently, some opinions may not be extracted because the context free grammar rules are insufficient. Second, natural languages evolve and diversify all the time. Many emerging words or phrases, including idioms, proverbs and slang, are often used in online reviews. Thus, those words or phrases need to be manually updated in the knowledge base.Practical implicationsThis research contributes to the tourism business and assists travelers by introducing comprehensive and easy to understand information about each accommodation to travelers. Although the FLORA system was originally designed and tested with accommodation reviews, it can also be used with reviews of any products or services by updating data in the knowledge base. Thus, businesses, which have online reviews for their products or services, can benefit from the FLORA system.Originality/valueThis research proposes a FLORA system which analyzes sentiments from online reviews, computes feature scores and summarizes results in a hierarchical view. Moreover, this work is able to use the overall score, rated by real tourists, as a baseline for accuracy comparison. The main theoretical implication is a novel sentiment analysis process based on semantic analysis and a novel rating technique called hierarchical fuzzy calculation.

Gunesekera, Asela Indunil; Bao, Yukun; Kibelloh, Mboni

2019 Journal of Systems and Information Technology

doi: 10.1108/jsit-02-2019-0024

The purpose of this study is to review the effect of usability factors on e-learning user relationships, namely, student–student interaction (SSI), student–instructor interaction (SII) and student–content interaction (SCI), in the existing e-learning literature. Further, this study intended to identify whether usability contributes to the satisfaction of e-learners.Design/methodology/approachThis study has undertaken a systematic review using the PRISMA methodology to filter the literature in the domain of e-learning with respect to usability concerns using six databases. An analytical framework has been formulated to evaluate the literature against different dimensions of interactions and usability.FindingsResults reveal that while SSI has grabbed 71.4 per cent research attention with respect to usability factors of e-learning systems, SCI has been given the least focus, i.e. 26.6 per cent. According to the results, e-learning systems’ usability issues influence the user relationships and affect the user satisfaction, which will lead to lack of user continuity.Practical implicationsThe findings of this review will provide insights to instructional designers to construct more satisfied learning content for the users. The analysis framework of this study will encourage researchers to drive future research in e-learning along with the concern of usability.Originality/valueThis research emphasizes on the importance of SCI to focus future e-learning research on a different angle, in addition to SSI and SII. The analysis framework of this study will provide different dimensions, specifically for the empirical research in the domain of e-learning.