Global Knowledge, Memory and Communication

Publisher:: Emerald Group Publishing Limited
Publication date:: 2021-02-01

ISBN:: 2514-9342

Issue Number

No. 74-11, January - January - August - August - August - August - February - June 2025

Latest documents

Does eWoM matter in s-commerce? A comparatives study between Kuwait and United Arab Emirates
Purpose: This study aims to explore the antecedent factors that directly and indirectly influence electronic word of mouth (eWoM) for social commerce (s-commerce) in two developing countries (e.g. Kuwait and the United Arab Emirates [UAE]) by extending social cognitive theory. Design/methodology/approach: This study uses a previous robust model (Rouibah et al., 2021) as theoretical background to investigate and compares the antecedents (trust in Instagram, perceived risks) on eWoM for s-commerce through the mediation of three mediators (perceived enjoyment, perceived value and customer satisfaction) among two Arab countries. Data was collected from Kuwait (n = 1,132) and the UAE (n = 190). Different statistical analyses and structured equation modeling-based analysis of moment structure are used to test the robustness of the research model. Findings: This study found customer satisfaction to be most important factor that mediates the effect independent factors on eWoM for s-commerce in both countries. Surprisingly, perceived enjoyment has no effect, and trust in Instagram and perceived risks are the most important factors that are considered imperative for customer satisfaction and positive feedback. Research limitations/implications: One limitation of this study is that the author does not focus on the difference between the effects of textual and graphical information on customers’ decisions and trust in buying merchandise. Another limitation is that this study focuses on Kuwait and the UAE. Other Gulf Cooperation Council countries are also growing exponentially, and mobile and internet penetration rates are booming; they could be a trigger for more studies on whether differences occur among all of them. Practical implications: The first implication is that it is the first in its field to extend the effects of eWoM. To the best of the author’s knowledge, compared to the online research this study is unique because the authors examine six factors for eWoM in s-commerce using the Instagram platform as opposed to other platforms. Social implications: The third implication of this study is that the previous ones have applied eWoM to different subjects of e-commerce such as tourism and marketing but have concentrated less on s-commerce, where in-depth research is needed much more to explore factors and theories that explain human behavior. Originality/value: Furthermore, most of these studies have focused on the intention to use (Dincer and Dincer, 2023; X. Hu, Chen, Davison, and Liu, 2022; Zhou et al., 2023). However, the attention in this research is on the actual use.
An analysis of literacy differences related to the identification and dissemination of misinformation in Japan
Purpose: This study aims to examine the relationship between various types of literacy on one hand and identification of misinformation and dissemination of such information on the other, in search for better countermeasures against misinformation. Design/methodology/approach: Based on data from a large-scale survey, models are constructed and analyzed to assess the relationships of literacy with both the identification of inaccuracies and dissemination behavior. Findings: Regarding the identification of misinformation, individuals with high critical thinking attitudes (subjective literacy) are less likely to recognize misinformation, while other objective literacies do not have a significant relationship. Regarding dissemination behavior, individuals with high information literacy, media literacy and critical thinking scores tend not to disseminate misinformation, whereas those with high critical thinking attitudes are more likely to disseminate such information. Originality/value: First, it quantitatively elucidates the relationships various literacies have with the accuracy judgment and dissemination behavior of misinformation. This highlights the effectiveness of objective indicators of literacies and the need for caution regarding subjective literacy – i.e. self-confidence in their own literacy. Second, it provides a cross-disciplinary analysis of the relationships, covering not only oft-studied politics and health care but also various other fields, thereby identifying comprehensive literacy strategies against misinformation. Third, it addresses differences in dissemination methods and offers insights into more practical countermeasures.
Integrating facets of information technology governance at a professional council in South Africa
Purpose: The purpose of the study is to explore the integration of facets of information technology (IT) governance at a professional council in South Africa with the view to develop a framework. Design/methodology/approach: This critical emancipatory study used the Information Governance Initiative pinwheel to explore the architecture facet of information governance at the professional council, with a view to developing a framework for entrenching a culture of good corporate governance. Qualitative data was collected through interviews and document analysis. The study was a participatory action research project that involved collaboration between the researcher and study participants in defining and solving the problem through a needs assessment exercise. Findings: The key findings report on the processes taken by a professional council in identifying and implementing the facets of information governance, that is, records management, IT, content management, data governance, information security, data privacy, risk management, regulatory compliance, long-term digital preservation and, even, business intelligence. Research limitations/implications: The study was a participatory action research project that involved collaboration between the researcher and study participants in defining and solving the problem through a needs assessment exercise. Practical implications: The study’s findings suggest that, with the right information governance policy in place, adopting the facets of information governance can be used to address concerns related to information integrity in the short and medium terms. As a long-term option for retaining data and information, it would have various drawbacks and would not, however, ensure the initial dependability of the information. Originality/value: A framework for information governance to ensure that the professional organisation and board members adopt a tailored governance system is suggested.
A systematic review of information and communication technologies (ICTs) on student motivation: researchers’ reflections on a selected higher education institution (HEIs)
Purpose: Through the review of several journal articles on the adoption of information and communication technologies (ICTs) and how it impacts students’ motivation to continue with their studies or to drop out of their academic program, this study aims to review the literature on the impact of ICTs on student motivation at a university. Design/methodology/approach: This paper is based on a systematic literature review steered by the PRISMA guidelines. This paper uses both Durban University of Technology subscription-based and publicly available papers. The research articles examined were published between 2018 and 2023 in Scopus, Web of Science and ScienceDirect. Findings: Reviewed literature bespeaks that ICTs can increase student motivation by enhancing interactive, engaging and individualized learning. Digital technologies that engage students and offer a more engaging learning environment include instructional apps, online simulations and multimedia content. Using ICTs may be useful in lowering university dropout rates. Originality/value: The systematic review yielded valuable insights for both academic research and real-world applications in education regarding the Durban University of Technology. The study offers a comprehensive analysis of the nexus between ICTs and student motivation.
Enhancing service delivery through digital transformation in the public sector in South Africa
Purpose: This study aims to explore how service delivery can be enhanced through digital transformation in the public sector in South Africa. Design/methodology/approach: This case study used a qualitative research approach to obtain data through semi-structured interviews. The units of analysis were made up of individual professionals limited to purposive sampling to select chief information officers, investigators and administrative officers from national government departments and state-owned enterprises. The collected data from 12 participants was thematically analysed. The findings revealed that the government lacks legislation and strategy for digital transformation, leading to inconsistent implementation of digital transformation that enhances service delivery in the public sector of South Africa. Findings: The findings revealed that the government lacks legislation and strategy for digital transformation, leading to inconsistent implementation of digital transformation that enhances service delivery in the public sector of South Africa. Research limitations/implications: The study was limited to the public sector of South Africa; however, its recommendations are applicable to all organisations that need to provide their services using digital transformation. Practical implications: Practically, the implications of this study will serve as a resourceful benchmark for the public sector and other organisations. Social implications: Socially, the implications of this study ensure proper implementation of its recommendations to enhance service delivery in the public sector and other organisations. Originality/value: Regarding the value that this study brings, it proposes an amendment of the current legislative framework in favour of one that covers digital transformation, which has become dominant in today’s enhanced provision of service delivery.
Quantitative analysis of the relationship between expressing gratitude and forgiveness and user sentiment on social media
Purpose: The purpose of this study is to investigate how expressing gratitude and forgiveness on social media platforms relates to the overall sentiment of users, aiming to understand the impact of these expressions on social media interactions and individual well-being. Design/methodology/approach: The hypothesis posits that users who frequently express gratitude or forgiveness will exhibit more positive sentiment in all posts during the observed period, compared to those who express these emotions less often. To test the hypothesis, sentiment analysis and statistical inference will be used. Additionally, topic modelling algorithms will be used to identify and assess the correlation between expressing gratitude and forgiveness and various topics. Findings: This research paper explores the relationship between expressing gratitude and forgiveness in X (formerly known as Twitter) posts and the overall sentiment of user posts. The findings suggest correlations between expressing these emotions and the overall tone of social media content. The findings of this study can inform future research on how expressing gratitude and forgiveness can affect online sentiment and communication. Originality/value: The authors have demonstrated that social media users who frequently express gratitude or forgiveness over an extended period of time exhibit a more positive sentiment compared to those who express these emotions less. Additionally, the authors observed that BERTopic modelling analysis performs better than latent dirichlet allocation and Top2Vec modelling analyses when analysing short messages from social media. This research, through the application of innovative techniques and the confirmation of previous theoretical findings, paves the way for further studies in the fields of positive psychology and machine learning.
Emotional showdown on social media: analyzing user reactions to the 2016 US presidential campaign
Purpose: Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media. Design/methodology/approach: For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance. Findings: The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts. Originality/value: Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.
Data literacy training needs of researchers at South African universities
Purpose: The aim of this study was to determine data literacy (DL) training needs of researchers at South African public universities. The outcome of this study would assist librarians and researchers in developing a DL training programme which addressed identified needs. Design/methodology/approach: A survey research method was used to gather data from researchers at these universities by convenience. Online questionnaires were distributed to public universities through library directors for further distribution to researchers. Findings: The results indicate low levels of DL training at the respondent South African public universities with most researchers indicating that they had not received any formal training on DL. A few researchers indicated that they would welcome DL training. Research limitations/implications: This study was exploratory in nature and data was received from eight universities, which is not representative of all the 26 public universities in South Africa. Nonetheless, the low DL confirmed by the majority in the realised sample is indicative of the need to further investigate the subject. Practical implications: Librarians and research support personnel should collaborate on the development of DL training courses, workshops and materials used by researchers at institutions of higher learning to enhance DLs on campus. Originality/value: This study may be novel in South Africa in investigating the DL training needs of researchers at several universities and contributes to the growing body of literature on research data management
Uncertainty avoidance and acceptance of the digital payment systems: a partial least squares-structural equation modeling (PLS-SEM) approach
Purpose: The purpose of this study is to investigate the determinants that likely influence the intention of using digital payment systems such as the Jordan Mobile Payment (JoMoPay) system among public sector employees in Jordan. To achieve the purpose of the current study, the authors developed a new research model based on the extended unified theory of acceptance and use of technology (UTAUT2), with one of Hofstede’s cross-cultural dimension scales [uncertainty avoidance (UA)] to provide a further understanding of the JoMoPay system acceptance in Jordan. Design/methodology/approach: A partial least squares-structural equation modeling approach was used to analyze the data collected by self-administration from the 270 employees working in the Jordanian public sector located in Amman city, the capital city of Jordan. Because most main public sectors are located in Amman and because of the cost and time considerations, the current study applied a non-probability sampling with the purposive sampling technique. Findings: The empirical results reveal that the evident drivers of behavioral intention to use the JoMoPay system are significantly and positively influenced by social influence, UA, performance expectancy, price value and effort expectancy; therefore, the H1, H2, H3, H5 and H6 were supported. Conversely, the results show no significant relationship between facilitating conditions and the behavioral intention to use the JoMoPay system, and hence, the related hypothesis (H4) was not supported. Practical implications: The results of this study provide beneficial information to the Central Bank of Jordan and other service providers in Jordan about employee intentions to adopt JoMoPay system and increase decision-makers’ knowledge on factors that have an important impact in UTAUT2 model. Social implications: The results of this study enable policymakers to understand the important factors that will enhance savings, investments and living standards, create job opportunities as well as reduce the poverty, the paper money printing cost, risks of money transportation cost and the risk of human errors. Originality/value: The outcomes obtained will help both practitioners and researchers elucidate and understand the situation of digital payment systems acceptance among Jordanian public sector employees, as well as help them formulate plans to expedite the adoption process of digital payment systems in the case of UA.
Which of the book recommendation sections is the most similar to the user selections in LibraryThing?
Purpose: This study aims to determine the most similar set of recommendation books to the user selections in LibraryThing. Design/methodology/approach: For this purpose, 30,000 tags related to History on the LibraryThing have been selected. Their tags and the tags of the related recommended books were extracted from three different recommendations sections on LibraryThing. Then, four similarity criteria of Jaccard coefficient, Cosine similarity, Dice coefficient and Pearson correlation coefficient were used to calculate the similarity between the tags. To determine the most similar recommended section, the best similarity criterion had to be determined first. So, a researcher-made questionnaire was provided to History experts. Findings: The results showed that the Jaccard coefficient, with a frequency of 32.81, is the best similarity criterion from the point of view of History experts. Besides, the degree of similarity in LibraryThing recommendations section according to this criterion is equal to 0.256, in the section of books with similar library subjects and classifications is 0.163 and in the Member recommendations section is 0.152. Based on the findings of this study, the LibraryThing recommendations section has succeeded in introducing the most similar books to the selected book compared to the other two sections. Originality/value: To the best of the authors’ knowledge, itis for the first time, three sections of LibraryThing recommendations are compared by four different similarity criteria to show which sections would be more beneficial for the user browsing. The results showed that machine recommendations work better than humans.