Aiming at the problems of long evaluation time and poor evaluation accuracy of existing evaluation methods, an improved decision tree-based evaluation method for the effectiveness of college online course teaching reform is proposed. Firstly, the teaching mode of college online course is analysed, and an evaluation system is constructed to ensure the applicability of the evaluation method. Secondly, AHP entropy weight method is used to calculate the weights of evaluation indicators to ensure the accuracy and authority of evaluation results. Finally, the evaluation model based on decision tree algorithm is constructed and improved by fuzzy neural network to further optimise the evaluation results. The parameters of fuzzy neural network are adjusted and gradient descent method is used to optimise the evaluation results, so as to effectively evaluate the effect of college online course teaching reform. Through experiments, the evaluation time of the method is less than 5 ms, and the evaluation accuracy is more than 92.5%, which shows that the method is efficient and accurate, and provides an effective evaluation means for the teaching reform of online courses in colleges and universities.

In order to improve recommendation coverage, a personalised recommendation method for English online learning resources based on improved collaborative filtering algorithm is studied to enhance the comprehensiveness of personalised recommendation for learning resources. Use matrix decomposition to decompose the user English online learning resource rating matrix. Cluster low dimensional English online learning resources by improving the K-means clustering algorithm. Based on the clustering results, calculate the backfill value of English online learning resources and backfill the information matrix of low dimensional English online learning resources. Using an improved collaborative filtering algorithm to calculate the predicted score of learning resources, personalised recommendation of English online learning resources for users based on the predicted score. Experimental results have shown that this method can effectively backfill English online learning resources, and the resource backfilling effect is excellent, and it has a high recommendation coverage rate.

The conventional methods for identifying English online course learning behaviours have the problems of low recognition accuracy and high time cost. Therefore, a multimodal data fusion-based method for identifying English online course learning behaviours is proposed. Firstly, the analytic hierarchy process is used for decision fusion of multimodal data of learning behaviour. Secondly, based on the fusion results of multimodal data, weight coefficients are set to minimise losses and extract learning behaviour features. Finally, based on the extracted learning behaviour characteristics, the optimal classification function is constructed to classify the learning behaviour of English online courses. Based on the transfer information of learning behaviour status, the identification of online course learning behaviour is completed. The experimental results show that the recognition accuracy of the proposed method is above 90%, and its recognition accuracy is and can shorten the recognition time of learning behaviour, with high practical application reliability.

In order to shorten the integration and sharing time of English teaching resources, a MOOC English online and offline mixed teaching resource integration model based on convolutional neural networks is proposed. The intelligent integration model of MOOC English online and offline hybrid teaching resources based on convolutional neural network is constructed. The intelligent integration unit of teaching resources uses the Arduino device recognition program based on convolutional neural network to complete the classification of hybrid teaching resources. Based on the classification results, an English online and offline mixed teaching resource library for Arduino device MOOC is constructed, to achieve intelligent integration of teaching resources. The experimental results show that when the regularisation coefficient is 0.00002, the convolutional neural network model has the best training effect and the fastest convergence speed. And the resource integration time of the method in this article should not exceed 2 s at most.

Under the current framework of police online teaching, in order to effectively solve the lack of high-quality resources of the traditional platform, backward sharing technology, poor performance of the digital platform and the privacy problems faced by each subject in sharing. This paper designs and implements the online teaching platform based on blockchain and interplanetary file system (IPFS). Based on the architecture of a 'decentralised' police online teaching platform, the platform uses blockchain to store hashes of encrypted private information and user-set access control policies, while the real private information is stored in IPFS after encryption. In the realisation of privacy information security storage at the same time to ensure the effective control of the user's own information. In order to achieve flexible rights management, the system classifies private information. In addition, the difficulties of police online teaching and training reform in the era of big data are solved one by one from the aspects of communication mode, storage facilities, incentive mechanism and confidentiality system, which effectively improves the stability and security of police online teaching.

In order to improve the classification accuracy and online allocation accuracy of teaching resources and shorten the allocation time, this paper proposes a new online allocation method of college ideological and political curriculum teaching resources based on differential search algorithm. Firstly, the feedback parameter model of teaching resources cleaning is constructed to complete the cleaning of teaching resources. Secondly, according to the results of anti-interference consideration, the linear feature extraction of ideological and political curriculum teaching resources is carried out. Finally, the online allocation objective function of teaching resources for ideological and political courses is constructed, and the differential search algorithm is used to optimise the objective function to complete the online allocation of resources. The experimental results show that this method can accurately classify the teaching resources of ideological and political courses, and can shorten the allocation time, with the highest allocation accuracy of 97%.

The study aims to analyse the impact of shopping applications on the shopping behaviour of the working women community in Bangalore, a city known as the IT hub. The research uses a quantitative analysis with SPSS version 23 software and a structured questionnaire survey technique to gather data from the working women community. The study uses descriptive statistics, ANOVA, regression, and Pearson correlation analysis to evaluate the perception of working women regarding the significance of online shopping applications. The results show that digital shopping applications are more prevalent among the working women community in Bangalore. The study also evaluates the socio-economic and psychological factors that influence their purchasing behaviour. The findings suggest that online marketers should enhance their strategies to improve their business on digital platforms. The research provides valuable insights into the shopping habits of the working women community in Bangalore.

This paper compares the effect of social isolation on students enrolled in online courses versus students enrolled in on campus courses (called in this paper Face-to-Face or F2F). Grade data was collected from one online section and two F2F sections of a computer literacy course that was recently taught by one of the authors of this study. The same instructor taught all sections thereby providing a controlled comparison between the two forms of teaching (F2F and online). This paper first introduces the plan and the limitation of this study. It provides a literature review and notes the trend of social isolation found in online courses. This paper then presents a summary of the collected data; and offers a conclusion based on the collected data.

This longitudinal, quasi-experimental study investigated students’ cognitive personality type using the Myers-Briggs personality Type Indicator (MBTI) in Internet-based Online and Face-to-Face (F2F) modalities. A total of 1154 students enrolled in 28 Online and 32 F2F sections taught concurrently over a period of fourteen years. The study measured whether the sample is similar to the national average percentage frequency of all 16 different personality types; whether specific personality type students preferred a specific modality of instructions and if this preference changed over time; whether learning occurred in both class modalities; and whether specific personality type students learned more from a specific modality. Data was analyzed using regression, t-test, frequency, and Chi-Squared. The study concluded that data used in the study was similar to the national statistics; that no major differences in preference occurred over time; and that learning did occur in all modalities, with more statistically significant learning found in the Online modality versus F2F for Sensing, Thinking, and Perceiving types. Finally, Sensing and Thinking (ST) and Sensing and Perceiving (SP) group types learned significantly more in Online modality versus F2F.

Aim/Purpose: To understand readiness of students for learning in online environments across different age groups. Background: Online learners today are diverse in age due to increasing adult/mature students who continue their higher education while they are working. Understanding the influence of the learners’ age on their online learning experience is limited. Methodology: A survey methodology approach was followed. A sample of one thousand nine hundred and twenty surveys were used. Correlation analysis was performed. Contribution: The study contributes by adding to the limited body of knowledge in this area and adds to the dimensions of the Online Learning Readiness Survey additional dimensions such as usefulness, tendency, anxiety, and attitudes. Findings: Older students have more confidence than younger ones in computer proficiency and learning skills. They are more motivated, show better attitudes and are less anxious. Recommendations for Practitioners: Practitioners should consider preferences that allow students to configure the learning approach to their age. These preferences should be tied to the dimensions of the online learning readiness survey (OLRS). Recommendations for Researchers: More empirical research is required using OLRS for online learning environments. OLRS factors are strong and can predict student readiness and performance. These are opportunities for artificial intelligence in the support of technology-mediated tools for learning.

Aim/Purpose: In the midst of COVID-19, classes are transitioned online. Instructors and students scramble for ways to adapt to this change. This paper shares an experience of one instructor in how he has gone through the adaptation. Background: This section provides a contextual background of online teaching. The instructor made use of M-learning to support his online teaching and adopted the UTAUT model to guide his interpretation of the phenomenon. Methodology: The methodology used in this study is action research through participant-observation. The instructor was able to look at his own practice in teaching and reflect on it through the lens of the UTAUT conceptual frame-work. Contribution: The results helped the instructor improve his practice and better under-stand his educational situations. From the narrative, others can adapt and use various apps and platforms as well as follow the processes to teach online. Findings: This study shares an experience of how one instructor had figured out ways to use M-learning tools to make the online teaching and learning more feasible and engaging. It points out ways that the instructor could connect meaningfully with his students through the various apps and plat-forms. Recommendations for Practitioners: The social aspects of learning are indispensable whether it takes place in person or online. Students need opportunities to connect socially; there-fore, instructors should try to optimize technology use to create such opportunities for conducive learning. Recommendations for Researchers: Quantitative studies using surveys or quasi-experiment methods should be the next step. Validated inventories with measures can be adopted and used in these studies. Statistical analysis can be applied to derive more objective findings. Impact on Society: Online teaching emerges as a solution for the delivery of education in the midst of COVID-19, but more studies are needed to overcome obstacles and barriers to both instructors and students. Future Research: Future studies should look at the obstacles that instructors encounter and the barriers with technology access and inequalities that students face in online classes.

Aim/Purpose: The authors provide different technology applications useful in online instruction in addition to providing effective strategies for use in a virtual environment. Background: Last year, educators were forced to move their instruction online almost overnight. Many were not prepared to teach effectively in a virtual environment. Contribution: This paper serves as a resource to educators who are unfamiliar with teaching online as well as for those who would like to enhance their current practice. Recommendations for Practitioners: Be flexible when teaching in a virtual environment. Remain open to using new and unfamiliar technologies. Be consistent in providing feedback to students and communicate frequently with them. Impact on Society: The abrupt transition for educators, as well as for most workplaces, to an exclusively online environment in response to COVID has long-lasting effects in how business as usual will be conducted. Being proficient and comfortable in navigating a virtual environment is essential. Future Research: As we continue to work virtually, ongoing research that informs our practice is critical for remaining effective educators. Additionally, it is important to remain knowledgeable about current and new technologies available to us. Keywords online instruction, technology applications, strategies

Aim/Purpose; Fostering student engagement is one of the great challenges of teaching, especially in online learning environments. An educators’ assumptions and beliefs about what student engagement is and how it manifests will shape the strategies they design to engage students in learning. However, there is no agreement on the definition of concept of student engagement and it re-mains a vague construct. Background: Adopting the principles of user-centered design, the author maintains that to design learning experiences which better support student engagement it is important to gain insights into how students perceive and operationalize the concept of engagement in learning. The recent challenges of teaching effectively online prompted the author to reflect more deeply on the concept of engagement and how it might be achieved. Methodology: In the tradition of reflective teaching, the author undertook an informal, qualitative inquiry in her classroom, administering a brief questionnaire to students in her online class. When the themes which emerged were integrated with other literature and findings from the author’s earlier classroom inquiry, some insights were gained into how students ‘operationalize’ the concept of engagement, and weight was added to the authors’ premise of the value of humanistic approaches to university teaching, the need for greater emphasis on student-teacher connection and the necessity of considering the affective domain alongside the cognitive domain in learning in higher education. The insights were brought together and visualized in a conceptual model of student engagement. Contribution: The conceptual model presented in the present paper reflects the author’s present ‘mental model’ of student engagement in classes online and, when the opportunity arrives, in face-to-face classes as well. This mental model shapes the authors’ course design, learning activities and the delivery of the course. Although the elements of the model are not ‘new’, the model synthesizes several related concepts necessary to a humanist approach to under-standing student engagement. It is hoped that the model and discussion presented will be stimulus for further rich discussion around the nature of student engagement. Findings: Interestingly, the affective rather than the cognitive domain framed students’ perspectives on what engagement ‘looks like to them’ and on what teachers should do to engage them. Recommendations for Practitioners: By sharing the process through which the author arrived at this understanding of student engagement, the author has also sought to highlight three key points: the importance of including the ‘student perspectives and expectations’ against which educators can examine their own assumptions as part of the process reflective teaching practices; the usefulness of integrating theoretical and philosophical frameworks in our understandings of student engagement and how it might be nurtured, and finally the necessity of affording greater influence to humanism and the affective domain in higher education. The findings emphasize the necessity of considering the affective dimension of engagement as an essential condition for cognitive engagement and as inextricable from the cognitive dimension of engagement. Recommendations for Researchers: The emphasis in research engagement learning and teaching is on how we (the educators) can do this better, how we can better engage students. While the student perspective is often formulated from data obtained through surveys and focus groups, researchers in learning engagement are working with their own understandings (albeit supported by empirical research). It is crucial for deeper insight to also understand the students’ conceptualization of the phenomena being researched. Bringing the principles of design thinking to bear on educational research will likely provide greater depth of insight. Impact on Society: Empirical, formal, and structured research is undeniably essential to advancing human endeavor in any field, including learning and teaching. It is however important to recognize informal research in the form of classroom inquiry as part of teachers’ reflexive practice is also legitimate and useful to advancing understanding of complex phenomenon such as student engagement in learning through multiple perspectives and experiences. Future Research: Further research on the nature of student engagement in different contexts and against different theoretical frameworks is warranted as is empirical investigation of the premise of the value of humanism and the affective do-main in defining and measuring student engagement in higher education.

Aim / Purpose This study examined the perception of the role of tutors in online training of preservice teachers during the COVID period, from the perspective of pre-service teachers and their tutors. Background Because of the COVID pandemic, learning in schools was conducted online, therefore preservice teachers’ practicum also took place online, as did the tutoring process. Methodology The research question was: How did preservice teachers and their tutors perceive the experience of teaching during the COVID period perceived by them; specifically, what was their sense of self-efficacy and satisfaction, and what difficulties did they encounter? This was a quantitative study. The sample included 221 participants comprising 111 tutors and 110 preservice teachers. Data were collected in Israel in 2021. Contribution This study sheds light on the process of online tutoring of preservice teachers by their tutors. Findings The study found that preservice teachers and their tutors perceived the practicum during the COVID period to be helpful, answering preservice teachers’ needs and providing professional assistance in their training. This was more so in the professional aspects of teaching, in the emotional aspects of the tutoring process, and in the process of shaping the preservice teachers’ professional identity, and less so in the organizational aspects of the school. In both groups (tutors and preservice teachers), it emerged that during a complex period of social isolation, maintaining contact reinforces the sense of self-efficacy. Tutors who encountered fewer technical difficulties and thought the tutoring process was enjoyable expressed more satisfaction with the tutoring process. Tutors felt that they were able to get better acquainted personally with the preservice teachers they taught, and vice versa, and preservice teachers were able to get to know their tutors personally. Tutors thought that their interpersonal communication benefitted the preservice teachers, that they listened to their mentees, and understood them. Preservice teachers felt that tutors allowed them to voice their expectations and concerns about their teaching experiences. Recommendations for practitioners One of the main goals of practicum in studies toward a teaching certificate is to prepare the students for their role as teachers. In the online tutoring process, emphasis should be placed on professional aspects (such as instruction and classroom management, identifying points for improvement and setting them as goals and challenges for the future) and on emotional aspects (such as promoting growth and personal development of preservice teachers in the process of shaping their professional identity). Recommendations for researchers One of the findings of the study is that the tutor-mentee relationship should be preserved in remote tutoring. The findings showed a positive correlation between maintaining such contact and high self-efficacy for both tutors and preservice teachers. It was found that tutors who reported high self-efficacy felt that interpersonal communication benefitted the teachers they were guiding. Impact on society Information collected in this study indicates that the tutors made a great effort to provide preservice teachers with meaningful coaching during the COVID period. In certain aspects, the tutoring was more successful and in other aspects less so, given the characteristics of the period, such as social distancing, no attendance of regular classes at school, and so forth. Future research It is recommended to continue investigating the online tutoring process, both from the perspective of preservice teachers and of tutors, to explore in-depth the correlation between self-efficacy and interpersonal communication, with emphasis on feedback between the tutors and preservice teachers.

Aim/Purpose. Higher education institutions face difficulties and challenges when it comes to distance learning. The purpose of this paper is to examine self-efficacy indicators and student satisfaction during online English classes. Background. E-learning has been very relevant since the Covid-19 era and is still relevant today. It is possible for students to study regardless of their location or time. By measuring students’ self-efficacy, instructors can gain valuable insights into their students’ ability to create social interaction, cope with technology, and acquire knowledge and tools to manage the learning process. Methodology. This study uses mixed methods along with two measurements. Before and after the course, quantitative and qualitative data were collected. Higher education students in Israel participated. A total of 964 students enrolled in English as a foreign language courses at the pre-basic, basic, and advanced levels. Contribution. Analyzing self-efficacy from several angles provides insight into students. What influences students’ confidence and belief in their ability to succeed in online courses. Moreover, how students perceive their own learning and how they cope with challenges. Findings. Compared to the measurement before the course, self-efficacy decreased on average. Most significant decreases occurred in ‘creating social interactions’ and ‘acquirement of knowledge and tools’ to manage the learning process. A slight decrease was observed in the ability to cope with technology. Additionally, self-efficacy and satisfaction with the course were positively correlated. Recommendations for Practitioners. An overview is provided of the most effective tools and techniques for teaching languages in digital format in this paper. This will allow instructors to design and deliver courses in a more effective way. Thus, they will be able to make better informed decisions, resulting in better outcomes for students. Recommendations for Researchers. Distance Learning courses should resemble the common digital environments in everyday life, rather than imitating face-to-face courses mainly in the field of social interaction. Impact on Society. Digital tools should be encouraged that facilitate effective learning processes instead of sticking to traditional methods that characterize face-to-face courses. Using common interfaces in daily use among the general population will enable the implementation of these recommendations. Future Research. Future studies could be helpful if they compared the English courses developed in the CEFR model with those taught face-to-face as well as those taught online. In addition, motivation and self-monitoring should be examined in both synchronous and asynchronous courses as well.

Aim/Purpose: In this research, we examined the influence of the information system (IS) quality dimensions proposed by Wixom and Todd on reading satisfaction of online newspaper readers in Bangladesh, especially the readers’ intention to revisit and recommendations through electronic word-of-mouth (eWOM). Background: We identified the top 50 most visited websites, of which 13 were online newspapers, although their ranking among Bangladesh online newspapers varies from month to month. The literature illustrates that, despite the wide availability of online news portals and the fluctuations in frequency of visits, little is known about the factors that affect the satisfaction, word-of-mouth, and frequency of visits of readers. An understanding of reader satisfaction will help to gain richer insights into the phenomenon of readers’ intention to revisit and recommendation by eWOM. Stakeholders of online newspapers can then focus on those factors to increase visits to their websites, which will help them attract online advertisements from different organisations. Methodology: Data were collected using a structured questionnaire, from 217 people who responded to the survey. We used SmartPLS 3 to analyze the data collected, as it is based on second-generation analysis, which in turn is based on structural equation modeling (SEM). Contribution: This research explores the impacts of technological dimensions on readers’ satisfaction, as most of the previous research has focused on cultural or social dimensions. Findings: The results supported all of the hypothesized relationships between technological dimensions and reader satisfaction with online newspapers, except for one. The first, information, was predicted with accuracy and completeness, while the second object-based belief, system quality, was predicted by its accessibility, flexibility, reliability, and timeliness. Overall, quality factors influencing readers’ satisfaction were shown to lead to word-of-mouth revisit intentions. Our proposed model was empirically tested and has contributed to a nascent body of knowledge about readers’ revisit intentions and eWOM recommendations regarding online newspapers. It was also shown that strong satisfaction leads to higher revisit intention and eWOM. Recommendations for Practitioners: To keep the users satisfied, online newspapers need to focus on improving information quality (IQ) and system quality (SQ). If they do this well, they will be rewarded with higher revisit intention and recommendations by eWOM. Recommendation for Researchers: This study extends Oh’s customer loyalty model by integrating the Wixom-Todd model. This study reinforces an alternative rationale of the construct satisfaction. Future Research: We ignored negative stimulus like technostress, which can have an impact on satisfaction. In future, we will test the relationship between technostress and its impact on online newspaper reading.

Aim/Purpose: The wide use of online banking and technological advancement has attracted the interest of malicious and criminal users with a more sophisticated form of attacks. Background: Therefore, banks need to adapt their security systems to effectively stem threats posed by imposters and hackers and to also provide higher security standards that assure customers of a secured environment to perform their financial transactions. Methodology : The use of authentication techniques that include the mutual secure socket layer authentication embedded with some specific features. Contribution: An approach was made through this paper towards providing a more reliable and complete solution for implementing multi-level user authentication in a banking environment. Findings: The use of soft token as the final stage of authentication provides ease of management with no additional hardware requirement. Recommendations for Practitioners : This work is an approach made towards providing a more reliable and complete solution for implementing multi-level user authentication in a banking environment to stem cybercrime. Recommendation for Researchers: With this approach, a reliable system of authentication is being suggested to stem the growing rate of hacking activities in the information technology sector. Impact on Society :This work if adopted will give the entire populace confidence in carrying out online banking without fear of any compromise. Future Research: This work can be adopted to model a real-life scenario.

Aim/Purpose: To examine millennial satisfaction towards online food delivery services, including e-service quality, food quality, and perceived value as the determinants and behavioral intention as the consequence. Background: Among the generational cohorts, millennials are a demanding target group for many retailers, including restaurants. Despite many studies examining millennial behavior in the restaurant context, almost no research on millennial attitudes and behavior in the context of online food home delivery service can be found. Methodology: For this research, 332 millennials completed a self-administered survey in Indonesia. To assess the associations between satisfaction and its determinants and consequences, this study employs Partial Least Square modeling. Contribution: This research extends existing knowledge of millennial satisfaction toward online food delivery service by highlighting that food quality, e-service quality and perceived value are the main determinants of satisfaction for online food purchasing among millennials. Further, this study offers support for the spillover theory in the online food home delivery service from millennial perspective. Findings: This study uncovers the important direct dual influences of e-service quality and food quality on millennial satisfaction with online food delivery services. Further, this study notes that e-service and food quality also have an indirect influence on satisfaction via perceived value. Moreover, satisfied millennial customers are more likely to re-purchase, recommend to others, and re-purchase at an increased price. Recommendations for Practitioners: For small and medium restaurants, it is suggested that they need to focus solely on their core business of providing food. If they want to offer an e-service, they should develop strategic cooperation with one or more online service providers. Recommendation for Researchers: Millennials tend to repurchase, recommend, and be willing to pay more in the future extends the existing models that look at the associations among quality, satisfaction and behavioral intention. Thus, in online restaurant purchasing services, both e-service quality and food quality should be included in the future research models. Impact on Society: This study could help restaurant industries to increase their business performance and, indirectly, impact on society as a whole by providing high quality food, employment opportunities, and tax revenues. Future Research: Future researchers can reassess the model in different countries and/or with other generation cohorts as well as including other variables such as trust, image, involvement, as well as socio-demographic factors.

Aim/Purpose: This study empirically analyzed and examined the effectiveness of the online advocacy banners on customers’ reactions to make replacements with the similar products in their shopping carts. Background: When a product in a shopping cart is removed, it might be put back into the cart again during the same purchase or it may be bought in the future. Otherwise, it might be abandoned and replaced with a similar item based on the customer’s enquiry list or on the recommendation of banners. There is a lack of understanding of this phenomenon in the existing literature, pointing to the need for this study. Methodology: With a database from a Taiwanese e-retailer, data were the tracks of empirical webpage clickstreams. The used data for analyses were particularly that the products were purchased again or replaced with the similar ones upon the advocacy banners being shown when they were removed from customers’ shopping carts. Few pre-defined Apriori rules as well as similarity algorithm, Jaccard index, were applied to derive the effectiveness. Contribution: This study addressed a measurement challenge by leveraging the information from clickstream data – particularly clickstream data behavior. These data are most useful to observe the real-time behavior of consumers on websites and also are applied to studying click-through behavior, but not click-through rates, for web banners. The study develops a new methodology to aid advertisers in evaluating the effectiveness of their banner campaign. Findings: The recommending/advocating titles of “you probably are interested” and “the most viewed” are not significantly effective on saving back customers’ removed products or repurchasing similar items. For the banners entitled “most buy”, “the most viewed” might only show popularity of the items, but is not enough to convince them to buy. At the current stage on the host website, customers may either not trust in the host e-retailer or in such mechanism. Additionally, the advocating/recommending banners only are effective on the same customer visits and their effects fade over time. As time passes, customers’ impressions of these banners may become vague. Recommendations for Practitioners: One managerial implication is more effective adoption of advocacy/recommendation banners on e-retailing websites. Another managerial implication is the evaluation of the advocacy/recommendation banners. By using a data mining technique to find the association between removed products and restored ones in e-shoppers’ shopping carts, the approach and findings of this study, which are important for e-retailing marketers, reflect the connection between the usage of banners and the personalized purchase changes in an individual customer’s shopping cart. Recommendation for Researchers: This study addressed a new measurement which challenges to leverage the information from clickstream data instead of click-through rates – particularly retailing webpages browsing behavior. These data are most useful to observe the real-time behavior of consumers on websites and also are applied to studying click-through behavior. Impact on Society: Personalization has become an important technique that allows businesses to improve both sales and service relationships with their online customers. This personalization gives e-marketers the ability to deliver real effectiveness in the use of banners. Future Research: The effectiveness is time- and case-sensible. Business practitioners and academic researchers are encouraged to apply the mining methodology to longevity studies, specific marketing campaigns of advertising and personal recommendations, and any further recommendation algorithms.

Aim/Purpose: This study examines the kind of community value companies should provide when strengthening the relationship between customers and brands through the establishment of an online brand community, and how this kind of community value promotes customers’ sense of community engagement and willingness to spread brand reputation. The paper also discusses how an enterprise’s brand symbolism affects the relationship between community value and customers’ engagement in online brand community. This study explored the important role of brand symbolism in the establishment of an online brand community. Background: Many companies want to create online brand communities to strengthen their relationships with consumers as well as to provide better service and value to consumers, for example, Huawei’s Huafen community (club.huawei.com), Apple’s support community (support.apple.com/zh-cn), and Samsung’s Galaxy community (samsungmembers.cn). However, these brand communities may have different interests and consumer engagement about the kind of community value to offer to their customers. Methodology: This study uses data collection from questionnaire surveys to design a quantitative research method. An online questionnaire survey of mobile phone users in China was conducted to collect data on social value, cognitive value, brand symbolism, customer community engagement, and brand recommendation. The brands of mobile phone include Apple, Huawei, Samsung, OPPO, VIVO, MI, and Meizu. The researcher purchased a sample service of WJX, an online survey company (www.wjx.cn), and WJX company distributed the questionnaire to research participants. The WJX company randomly selected 240 subjects from their sample database and then sent the questionnaire link to research participants’ mobile phones. Among the 240 research participants, the researcher excluded participants who lacked online brand community experience or had invalid data to qualify for data collection. After the researcher excluded participants who did not qualify for data collection, only 203 qualified questionnaire surveys advanced to the data collection and analysis phase, which was the questionnaire recovery rate of 84.58%. For the model analysis and hypotheses testing, the researcher used statistical software IBM SPSS Statistics and AMOS 21 and Smartpls3. Contribution: This study deepens the body of literature knowledge by combining online brand community value and brand symbolic value to explore issues that companies should consider when establishing an online brand community for their products and services. This study confirms that brands with high symbolic value establish communities and strengthen social values in the online brand community rather than reducing brand symbolism. Online brand community involves a horizontal interaction (peer interaction) among peers, which can have an effect on the symbolic value of brand (social distance). Findings: First, online brand community value (both cognitive and social value) has a positive impact on customer community engagement. Second, customer community engagement has a positive impact on customers’ brand recommend intention. Third, the customer community engagement is a mediator between the online brand community value and the customer brand recommend intention. Most importantly, fourth, the symbolic value of the brand controls the relationship between community value and customer community engagement. For brands with high symbolic value, the community value should emphasize cognitive value rather than social value. For brands with a low symbolic value, the community provides cognitive or social value, which is not affected by the symbolism of the brand. Recommendations for Practitioners: Practitioners can share best practices with the corporate sectors. Brand owners can work with researchers to explore the characteristics of their online brand communities. On this basis, brand owners and researchers can jointly build and manage online brand communities. Recommendation for Researchers: Researchers can explore different perspectives and factors of brand symbolism that involve brand owners when establishing an online brand community to advance consumer engagement, community value, and brand symbolism. Impact on Society: Online brand community is relevant for brand owners to establish brand symbolism, community value, and customer engagement. Readers of this paper can gain an understanding that cognitive and social values are two important drivers of individual participation in online brand communities. The discussion of these two factors can give readers and brand owners the perception to gain more understanding on social and behavior activities in online brand communities. Future Research: Practitioners and researchers could follow-up in the future with a study to provide more understanding and updated research information from different perspectives of research samples and hypotheses on online brand community.

Aim/Purpose: This study examines the impact of transitioning from in-person classrooms to remote online business education and provides analysis of key factors impacting course and instructor ratings as well as strategies for higher education institutions to provide engaging instruction. Background: “Zoom”ing into teaching and moving out of traditional classrooms during the COVID-19 pandemic has been a path full of twists and has impacted student perceptions of courses as well as instructors. One challenge has been to make the quality of synchronous online instruction perceived by students as positive as classroom-delivered ones. Methodology: We analyze primary data collected in the course evaluation process from Business & Accounting students over six semesters between Fall 2019 to Spring 2022, covering pre-pandemic instruction in the classroom and the conversion to virtual instruction via Zoom. A total of 1782 observations for 38 courses were examined using mean comparison, regression and correlation analyses, and pairwise comparisons. Contribution: We provide insights from the evaluation of those instructors who were able to make their Zoom-delivered courses perceived by students as equivalent or better than room-delivered ones. Specifically, clear presentation, stimulating delivery, providing feedback and encouraging discussion were positively correlated with successful online classes. Findings: We find that there is a clear downward shift in course and instructor ratings as the change to synchronous online delivery was made. However, in the Spring of 2022, even though instructors and students were still not completely back in the classroom, both instructor and course ratings moved back closer to the pre-pandemic levels. The parameters associated with instructor ratings, such as providing feedback, clear presentations, stimulating sessions, and encouraging discussion, showed similar downward fluctuations. Also, aspects related to course content were affected by the transition to online modality, including training on critical thinking quantitative analysis, research and writing abilities, and overall usefulness of the content. Moore’s model of Transactional Distance helps explain these changes. Recommendations for Practitioners: We recommend that practitioners allow sufficient time for students and faculty to learn through online instruction delivery and supply training for both populations in adapting to learning in this delivery mode. Recommendation for Researchers: The disruption in higher education caused by COVID-19 has provided a wealth of information on the pluses and minuses of online delivery. Careful inspection of trends can help provide guidance to higher education leaders. Impact on Society: One of the many changes the COVID-19 pandemic brought was the opportunity to try alternate ways of connecting and learning. This study shows how this experience can be used to guide the future of higher education. Future Research: Further research is needed to explore the in-depth reactions of students and faculty to the switch from classroom to online delivery, to explore whether these findings can be more broadly applied to other subjects and other types of universities.

Aim/Purpose: This study identifies the elements that influence intentions to purchase from the most popular Arabic online classifieds platform, OpenSooq.com. Background: Online purchasing has become popular among consumers in the past two decades, with perceived risk and trust playing key roles in consumers’ intention to purchase online. Methodology: A questionnaire survey was conducted of Internet users from three Jordanian districts to investigate how they used the OpenSooq platform in their e-commerce activities. In total, 202 usable responses were collected, and the data were analyzed with PLS-SEM for hypothesis testing and model validation. Contribution: Though online trading is increasingly popular, the factors that impact the behavior of consumers when purchasing high-value products have not been adequately investigated. Therefore, this study examined the factors affecting perceived risk, and the potential impact of privacy concerns on the perceived risk of online smartphone buyers. The study framework can help explore online behavior in various situations to ascertain similarities and differences and probe other aspects of online buying. Findings: Perceived risk negatively correlates with online purchasing behavior and trust. However, privacy concern and perceived risk, transaction security and trust, and trust and online purchasing behavior exhibited positive correlations. Recommendations for Practitioners: Customers can complete and retain online purchases in a range of settings illuminated in this study’s methods and procedures. Moreover, businesses can manage their IT arrangements to make Internet shopping more convenient and build processes for online shopping that allow for engagement, training, and ease of use, thus improving their customers’ online purchasing behavior. Recommendation for Researchers: Given the insight into the understanding and integration of variables including perceived risk, privacy issues, trust, transaction security, and online purchasing behavior, academics can build on the groundwork of this research paradigm to investigate underdeveloped countries, particularly Jordan, further. Impact on Society: Understanding the characteristics that influence online purchasing behavior can help countries realize the full potential of online shopping, particularly the benefits of safe, fast, and low-cost financial transactions without the need for an intermediary. Future Research: Future research can examine the link between online purchase intent, perceived risk, privacy concerns, trust, and transaction security to see if the findings of this study in Jordan can be applied to a broader context in other countries.

Aim/Purpose: The objective of this research is to investigate the effect of review consistency between textual content and rating on review helpfulness. A measure of review consistency is introduced to determine the degree to which the review sentiment of textual content conforms with the review rating score. A theoretical model grounded in signaling theory is adopted to explore how different variables (review sentiment, review rating, review length, and review rating variance) affect review consistency and the relationship between review consistency and review helpfulness. Background: Online reviews vary in their characteristics and hence their different quality features and degrees of helpfulness. High-quality online reviews offer consumers the ability to make informed purchase decisions and improve trust in e-commerce websites. The helpfulness of online reviews continues to be a focal research issue regardless of the independent or joint effects of different factors. This research posits that the consistency between review content and review rating is an important quality indicator affecting the helpfulness of online reviews. The review consistency of online reviews is another important requirement for maintaining the significance and perceived value of online reviews. Incidentally, this parameter is inadequately discussed in the literature. A possible reason is that review consistency is not a review feature that can be readily monitored on e-commerce websites. Methodology: More than 100,000 product reviews were collected from Amazon.com and preprocessed using natural language processing tools. Then, the quality reviews were identified, and relevant features were extracted for model training. Machine learning and sentiment analysis techniques were implemented, and each review was assigned a consistency score between 0 (not consistent) and 1 (fully consistent). Finally, signaling theory was employed, and the derived data were analyzed to determine the effect of review consistency on review helpfulness, the effect of several factors on review consistency, and their relationship with review helpfulness. Contribution: This research contributes to the literature by introducing a mathematical measure to determine the consistency between the textual content of online reviews and their associated ratings. Furthermore, a theoretical model grounded in signaling theory was developed to investigate the effect on review helpfulness. This work can considerably extend the body of knowledge on the helpfulness of online reviews, with notable implications for research and practice. Findings: Empirical results have shown that review consistency significantly affects the perceived helpfulness of online reviews. The study similarly finds that review rating is an important factor affecting review consistency; it also confirms a moderating effect of review sentiment, review rating, review length, and review rating variance on the relationship between review consistency and review helpfulness. Overall, the findings reveal the following: (1) online reviews with textual content that correctly explains the associated rating tend to be more helpful; (2) reviews with extreme ratings are more likely to be consistent with their textual content; and (3) comparatively, review consistency more strongly affects the helpfulness of reviews with short textual content, positive polarity textual content, and lower rating scores and variance. Recommendations for Practitioners: E-commerce systems should incorporate a review consistency measure to rank consumer reviews and provide customers with quick and accurate access to the most helpful reviews. Impact on Society: Incorporating a score of review consistency for online reviews can help consumers access the best reviews and make better purchase decisions, and e-commerce systems improve their business, ultimately leading to more effective e-commerce. Future Research: Additional research should be conducted to test the impact of review consistency on helpfulness in different datasets, product types, and different moderating variables.

Aim/Purpose: This study aims to examine the ten factors from the Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and Unified Theory of Acceptance and Use of Technology (UTAUT) theories in order to analyze behavioral intentions to use the Indonesian online capital market investment platforms and the effect of behavioral intentions on actual usage. Background: The potential growth of capital market investors in Indonesia is large, and the low use of the Internet for investment purposes makes it necessary for stakeholders to understand the factors that affect people’s intentions to invest, especially through online platforms. Several previous studies have explained the intention to use online investment platforms using the TAM and TPB theories. This study tries to combine TAM, TPB, and UTAUT theories in analyzing behavioral intentions to use an online capital market investment platform in Indonesia. Methodology: The research approach employed is a mixed method, particularly explanatory research, which employs quantitative methods first, followed by qualitative methods. Data were collected by conducting interviews and sending online surveys. This study was successful in collecting information on the users of online capital market investment platforms in Indonesia from 1074 respondents, which was then processed and analyzed using Covariance-Based Structural Equation Modeling (CB-SEM) with the IBM AMOS 26.0 application. Contribution: This study complements earlier theories like TAM, TPB, and UTAUT by looking at the intention to use online capital market investment platforms from technological, human, and environmental viewpoints. This study looks at the intention to use the online capital market investing platform as a whole rather than separately depending on investment instruments. This study also assists practitioners including regulators, the government, developers, and investors by offering knowledge of the phenomena and factors that can increase the capital market’s investment intention in Indonesia. Findings: Attitudes, perceived ease of use, perceived behavioral control, subjective norm, and national pride were found to be significant predictors of the intention to use online investment platforms in Indonesia, whereas perceived usefulness, perceived risk, perceived trust, perceived privacy, and price value were not. Recommendations for Practitioners: All practitioners must be able to take steps and strategies that focus on factors that have a significant impact on increasing usage intentions. The government can enact legislation that emphasizes the simplicity and convenience of investment, as well as launch campaigns that encourage people to participate in economic recovery by investing in the capital market. Meanwhile, the developers are concentrating on facilitating the flow of investment transactions through the platform, increasing education and awareness of the benefits of investing in the capital market, and providing content that raises awareness that investing in the capital market can help to restore the national economy. Recommendation for Researchers: Further research is intended to include other variables such as perceived benefits and perceived security, as well as other frameworks such as TRA, to better explain individuals’ behavioral intentions to use online capital investment platforms. Impact on Society: This study can help all stakeholders understand what factors can increase Indonesians’ interest in investing in the capital market, particularly through online investment platforms. This understanding is expected to increase the number of capital market participants and, as a result, have an impact on economic recovery following the COVID-19 pandemic. Future Research: Future research is expected to investigate additional factors that can influence individuals’ behavioral intention to use an online capital market investment platform, such as perceived benefits and perceived security, as well as the addition of control variables such as age, gender, education, and income. International research across nations is also required to build a larger sample size in order to examine the behavior of investors in developing and developed countries and acquire a more thorough understanding of the online capital market investment platform.

Aim/Purpose: This study investigates the factors that affect the repurchase intentions of Generation Z consumers in India’s online shopping industry, focusing on combining the Expectation-Confirmation Model (ECM) and Extended Technology Acceptance Model (E-TAM). The aim is to understand the intricate behaviors that shape technology adoption and sustained usage, which are essential for retaining customers in e-commerce. Background: Social media and other online platforms have significantly influenced daily life and become essential communication tools owing to technological advancements. Online shopping is no exception, offering a range of product choices, information, and convenience compared with traditional commerce. Indian retailers recognize this trend as an opportunity to promote their brands through e-shopping platforms, leading to increased competition. Generation Z comprises 32% of the world’s population and is a significant emerging customer base in India. Numerous studies have been conducted to study customers’ repurchase intention in the online shopping domain, but few studies have explicitly focused on Generation Z as a customer base. This study aims to comprehensively understand the topic and investigate the variables that impact consumers’ online repurchase intention by examining their post-adoption behavioral processes. Methodology: The study employed a quantitative research design with structural equation modeling using AMOS to analyze responses from 410 participants. This method thoroughly examined hypotheses regarding factors affecting repurchase intention (security, ease of use, privacy, and internet self-efficacy) and the mediating role of e-satisfaction. Contribution: This study makes a unique contribution to the field of e-commerce by focusing on Generation Z in India, a rapidly growing demographic in the e-commerce industry. The results on the mediating role of e-satisfaction have significant implications for e-retailers seeking to enhance customer retention strategies and gain a competitive edge in the market. Findings: The research findings underscore the significant influence of security, ease of use, and internet self-efficacy on repurchase intentions, with e-satisfaction playing a pivotal role as a mediating factor. Notably, while privacy concerns did not directly impact repurchase intentions, they displayed considerable influence when mediated by e-satisfaction, highlighting the intricate interplay between these variables in the context of online shopping, which is the unique finding of this study. Recommendations for Practitioners: This study has several significant implications for practitioners. Effectively addressing computer-related individual differences, such as computer self-efficacy, is crucial for boosting online customers’ repurchase intention. For instance, if an e-retailer intends to target Generation Z customers, they should collaborate with IT professionals and develop various computer literacy programs on online streaming platforms, such as YouTube. These programs will enhance target customers’ confidence in online shopping portals and increase their online repeat purchases. Additionally, practitioners should strive to improve the online shopping experience by making the portal user-friendly. Generation Z is accustomed to a fast Internet experience, so they prefer that the process of completing online transactions is swift with fewer clicks. The search for products, payments, and redress should not be tedious. Furthermore, the primary objective of the e-retailer should be to satisfy customers, as satisfied customers repeat their purchases and increase overall profitability. Recommendation for Researchers: The current study was conducted in the Delhi-NCR region of India, and its findings could serve as a basis for future research. For instance, the scale devised in this study could be utilized to examine the impact of cash-on-delivery as a payment method on purchase intention across the country. Alternatively, a comparative analysis could be conducted to compare cash-on-delivery effects in various countries. Impact on Society: The study’s findings enable stakeholders in the online shopping industry to comprehend the post-adoption behavior of Generation Z users and augment existing literature by establishing a correlation between determinants that impact repurchase intention and e-satisfaction, which serves as a mediator. Future Research: This study examines the factors that impact the propensity of Generation Z shoppers to engage in repeat online purchases. This study focuses on India, where the Generation Y (millennial) customer base is also substantial within the online shopping market. Future research could compare the shopping habits of Generation Z and Generation Y customers, as the latter may place greater importance on privacy and security. Additional studies could broaden the scope of this research and explore the comparative viewpoints of both generations. Also, it would be advantageous to conduct in-depth interviews and longitudinal studies to acquire a more in-depth comprehension of the evolving digitalization of shopping.

Aim/Purpose: This study investigates the intention to invest in online peer-to-peer (P2P) lending platforms among the bottom 40% (B40) Malaysian households by income. Background: The B40 group citizens earn less than USD 1,096.00 (i.e., RM 4,850.00) in monthly household income, thereby possessing relatively small capital investments suitable for online P2P lending. Methodology: Drawing on the technology acceptance model (TAM), this research developed and tested the relevant hypotheses with data collected from 216 respondents. The partial least square structural equation modelling (PLS-SEM) technique was employed to analyse the collected data. Contribution: This study contributes to the body of knowledge on financial inclusion by demonstrating the relevance of modified TAM in explaining the intention to invest in online P2P lending platforms among investors with lower disposable income (i.e., the B40 group in Malaysia). Findings: The findings revealed that information quality, perceived risk, and perceived ease of use are relevant to B40 investment intention in P2P online lending platforms. However, contrary to expectations, trust and financial literacy are insignificant predictors of B40 investment intention. Recommendations for Practitioners: The P2P lending platform operators could enhance financial inclusion among the B40 group by ensuring borrowers provide sufficient, relevant, and reliable information with adequate security measures to minimise risk exposure. The financial regulators should also conduct periodic audits to ensure that the operators commit to enhancing information quality, platform security, and usability. Recommendation for Researchers: The intention to invest in online P2P lending platforms among the B40 group could be enhanced by improving information quality and user experience, addressing perceived risks, reassessing trust-building strategies and financial literacy initiatives, and adopting holistic, interdisciplinary approaches. These findings suggest targeted strategies to enhance financial inclusion and investment participation among B40 investors. Impact on Society: The study’s findings hold significant implications for financial regulators and institutions, such as the Securities Commission Malaysia, Bank Negara Malaysia, commercial and investment banks, and insurance companies. By focusing on these key determinants, policymakers can design targeted interventions to improve the accessibility and attractiveness of P2P lending platforms for B40 investors. Enhanced information quality and ease of use can be mandated through regulatory frameworks, while effective risk communication and mitigation strategies can be developed to build investor confidence. These measures can collectively promote financial growth and inclusion, supporting broader economic development goals. Future Research: Future research could expand the sample size to consider older B40 individuals across different countries and use a longitudinal survey to assess the actual investment decision of the B40 investors.

Aim/Purpose: In this study, we developed a recommendation system model designed to support decision-makers in identifying consumers eligible for pay-later options via consensus-based decision-making. This approach was chosen due to the high and complex risks involved, such as delayed payments, challenges in reaching consumers, and issues of bad credit. Background: The “pay-later” option, which allows consumers to postpone payment for e-commerce purchases, offers convenience and flexibility but also introduces several challenges: (i) by enabling payment deferral, merchants face financial risks, including potential delays or defaults in payment, adversely affecting their cash flow and profitability; and (ii) this payment delay can also heighten the risk of fraud, including identity theft and unauthorized transactions. Methodology: This study initiated a risk analysis utilizing the ROAD process. Considering contemporary economic developments and advancements in neural networks, integrating these networks into risk assessment has become crucial. Consequently, model development involved the amalgamation of three deep learning methods – CNN (Convolutional Neural Networks), RNN (Recurrent Neural Networks), and LSTM (Long Short-Term Memory) – to address various risk alternatives and facilitate multi-stage decision-making recommendations. Contribution: Our primary contribution is threefold. First, our study identified potential consumers by prioritizing those with the smallest associated problem consequence values. Second, we achieved an optimal recall value using a candidate generator. Last, we categorized consumers to assess their eligibility for pay-later rights. Findings: The findings from this study indicate that our multi-stage recommendation model is effective in minimizing the risk associated with consumer debt repayment. This method of consumer selection empowers policymakers to make informed decisions regarding which consumers should be granted pay-later privileges. Recommendations for Practitioners: This recommendation system is proposed to several key parties involved in the development, implementation, and use of pay-later systems. These parties include E-commerce Executive Management for financial analysis and risk evaluation, the Risk Management Team to assess and manage risks related to users utilizing Pay-Later services, and Sales Managers to integrate Pay-Later services into sales strategies. Recommendation for Researchers: Advanced fraud detection mechanisms were implemented to prevent unauthorized transactions effectively. The goal was to cultivate user confidence in the safety of their financial data by ensuring secure payment processing. Impact on Society: Ensuring consumers understand the terms and conditions of pay-later arrangements, including interest rates, repayment schedules, and potential fees, is crucial. Providing clear and transparent information, along with educating consumers about their financial responsibilities, helps prevent misunderstandings and disputes. Future Research: Our future development plans involve the ongoing assessment of the system’s performance to enhance prediction accuracy. This includes updating models and criteria based on feedback and changes in economic or market conditions. Upholding compliance with security and data privacy regulations necessitates the implementation of protective measures to safeguard consumer information. The implementation of such a system requires careful consideration to ensure fairness and adherence to legal standards. Additionally, it is important to acknowledge that algorithms and models may evolve over time through the incorporation of additional data and continuous evaluations.