Aim/Purpose: This paper aims to describe how various Kanban elements can help alleviate two prominent types of challenges, communication and collaboration in Global Software Development (GSD). Background: Iterative and Lean development methodologies like Kanban have gained significance in the software development industry, both in the co-located and globally distributed contexts. However, little is known on how such methodologies can help mitigate various challenges in that occur in a globally distributed software development context. Methodology: The study was conducted using a single-case study based on a general inductive approach to analysis and theory development. Through the literature review, collaboration and communication challenges that GSD teams face were identified. Data collected through semi-structured interviews was then inductively analyzed to describe how the case-study teams employed various Kanban elements to mitigate communication and collaboration challenges they face during GSD. Findings: The study found that some Kanban elements, when properly employed, can help alleviate collaboration and communication challenges that occur within GSD teams. These relate to Inclusion Criteria, Reverse Items, Kanban Board, Policies, Avatars, and Backlog. Contribution: The paper contributes to knowledge by proposing two simple concept maps that detail the specific types of communication and collaboration challenges which can be alleviated by the aforementioned Kanban elements in GSD. Recommendations for Practitioners: This paper is relevant to GSD teams who are seeking ways to enhance their team collaboration and communication as these are the most important elements that contribute to GSD project success. It is recommended that relevant Kanban elements be used to that effect, depending on the challenges that they aim to alleviate. Future Research: Future research can investigate the same research questions (or similar ones) using a quantitative approach.

Aim/Purpose: To capture digital training experiences, the paper introduces a novel data collection method – a graphic questionnaire. It aims to demonstrate the opportunities and limitations of this tool for collecting feedback from socially disadvantaged participants of digital literacy training about their progress. Background: In training of digital skills for disadvantaged audiences through informal educational interventions, it is important to get sufficient knowledge on factors that lead to their progress in the course of training. There are many tools to measure the achievements of formal education participants, but assessing the effectiveness of informal digital skills training is researched less. The paper introduces a small-scale case study of the training programme aimed at the developing of reading and digital skills among the participants from three socially disadvantaged groups – people with hearing impairments, children from low income families, and elderly persons. The impact of the training on participants was evaluated using different tools, including a short graphic questionnaire to capture the perceptions of the participants after each training. Methodology: We performed a thematic analysis of graphic questionnaires collected after each training session to determine how the students perceived their progress in developing literacy and digital skills. Contribution The findings of the paper can assist in designing assessment of digital literacy programmes that focus not only on final results, but also on the process of gaining digital skills and important factors that facilitate progress. Findings: The graphic questionnaire allowed the researchers to get insights into the perception of acquired skills and progressive achievements of the participants through rich self-reports of attitudes, knowledge gained, and activities during training sessions. However, the graphic questionnaire format did not allow the collection of data about social interaction and cooperation that could be important in learning. Recommendations for Practitioners: Graphic questionnaires are useful and easy-to-use tools for getting rich contextual information about the attitudes, behaviour, and acquisition of knowledge in digital literacy training. They can be used in applied assessments of digital literacy training in various settings. Their simplicity can appeal to respondents; however, in the long-run interest of respondents in continuing self-reports should be sustained by additional measures. Recommendations for Researchers: Researcher may explore the variety of simple and attractive research instruments, such as “honeycomb” questionnaires and similar, to facilitate data collection and saturate feedback with significant perception of personal experiences in gaining digital literacy skills. Impact on Society: Designing effective digital literacy programmes, including engaging self-assessment methods and tools, aimed at socially disadvantaged people will contribute to their digital inclusion and to solving the issues of digital divide. Future Research: Exploration of diverse research methods and expanding the research toolset in assessing digital literacy training could advance our understanding of important processes and factors in gaining digital skills.

Aim/Purpose: The aim of this study was to examine the sense of challenge and threat, negative feelings, self-efficacy, and motivation among students in a virtual and a blended course on multicultural campuses and to see how to afford every student an equal opportunity to succeed in academic studies. Background: Most academic campuses in Israel are multicultural, with a diverse student body. The campuses strive to provide students from all sectors, regardless of nationality, religion, etc., the possibility of enjoying academic studies and completing them successfully. Methodology: This is a mixed-method study with a sample of 484 students belonging to three sectors: general Jewish, ultra-orthodox Jewish, and Arab. Contribution: This study’s findings might help faculty on multicultural campuses to advance all students and enable them equal opportunity to succeed in academic studies. Findings: Significant sectorial differences were found for the sense of challenge and threat, negative feelings, and motivation. We found that the sense of challenge and level of motivation among Arab students was higher than among the ultra-orthodox Jewish students, which, in turn, was higher than among the general Jewish student population. On the other hand, we found that the perception of threat and negative feelings among Arab students were higher than for the other two sectors for both the virtual and the blended course. Recommendations for Practitioners: Significant feedback might lessen the sense of threat and the negative feelings and be a meaningful factor for the students to persevere in the course. Intellectual, emotional, and differential feedback is recommended. Not relating to students’ difficulties might lead to a sense of alienation, a lack of belonging, or inability to cope with the tasks at hand and dropout from the course, or even from studies altogether. A good interaction between lecturer and student can change any sense of incompetence or helplessness to one of self-efficacy and the ability to interact with one’s surroundings. Recommendations for Researchers: Lecturers can reduce the sense of threat and negative feelings and increase a student’s motivation by making their presence felt on the course website, using the forums to manage discussions with students, and enabling and encouraging discussion among the students. Impact on Society: The integration of virtual learning environments into the learning process might lead to the fulfilment of an educational vision in which autonomous learners realize their personal potential. Hence they must be given tasks requiring the application of high learning skills without compromise, but rather with differential treatment of students in order to reduce negative feelings and the sense of threat, and to reduce the transactional distance. Future Research: Further studies should examine the causes of negative feelings among students participating in virtual and blended courses on multicultural campuses and how these feelings can be handled.

Aim/Purpose This paper focuses on systematizing and rethinking the conformity of modern transdisciplinarity with its prime cause and initial ideas. Background The difficulties of implementing transdisciplinarity into science and education are connected with the fact that its generally accepted definition, identification characteristics, and methodological features are still missing. In order to eliminate these disadvantages of transdisciplinarity, its prime cause and initial ideas had to be detected. It is also important to analyze the correspondence of the existing opinions about transdisciplinarity with the content of these cause and ideas. Methodology The qualitative analysis of the literature reviews on the subject of transdisciplinary was used in order to determine the correspondence of the opinions about the transdisciplinarity with the meaning of its prime cause and initial ideas. These opinions had to be generalized as well. Through this method, it was possible to detect and classify opinions into 11 groups including 39 stereotypes of transdisciplinarity. For substantiation of transdisciplinary approaches that are consistent with the approaches of contemporary science, C.F. Gauss random variables normal distribution was used. The “Gauss curve” helped to show the place of transdisciplinary and systems transdisciplinary approaches in the structure of academic and systems approaches. The “Gauss curve” also demonstrated the step-by-step “broadening of the scientific worldview horizon due to sequential intensification of synthesis, integration, unification, and generalization of the disciplinary knowledge.” Contribution After reconsideration of the results on qualitative analysis of the literature reviews, the generalized definition of transdisciplinarity could be formulated, including the definition for transdisciplinary and systems transdisciplinary approaches. It was proven that transdisciplinarity is a natural stage for the development of contemporary science and education, and the transdisciplinary approaches were able to suggest the methods and tools to solve the complex and poorly structured problems of science and the society. Findings Many existing stereotypes of transdisciplinarity do not meet its prime cause and initial ideas. Such stereotypes do not have deep philosophic and theoretical substantiation. They also do not suggest the transdisciplinary methods and tools. Thus, the authors of such stereotypes often claim them to be transdisciplinary or suggest perceiving them as transdisciplinarity. This circumstance is the reason why many disciplinary scientists, practitioners, and initiators of higher education view transdisciplinarity as a marginal direction of contemporary science. Based on the generalized definition of transdisciplinarity, as well as its prime cause and initial ideas, it was shown that transdisciplinarity is presented in contemporary science in the form of two different approaches, i.e., the transdisciplinary approach and systems transdisciplinary approach. The objective of the transdisciplinary approach is to ensure science development at the stage of synthesis and integration of disciplinary knowledge, while the objective of the systems transdisciplinary approach is to ensure that the problems of modern society are solved through unification and generalization of the disciplinary knowledge. Recommendation for Researchers The researchers should consider that within the limits of the transdisciplinary approach, the disciplinary specialists are managed. Within the limits of the systems transdisciplinary approach, the disciplinary knowledge is managed. Thus, the transdisciplinary approach is efficient for organization and research with participation of the scientists of the complementary disciplines. An example of such research can be a team of researchers of medical disciplines and complementary disciplines from chemistry, physics, and engineering. The systems transdisciplinary approach is efficient for organization and performance of research with participation of the scientists of non-complementary disciplines such as economics, physics, meteorology, chemistry, ecology, geology, and sociology. Future Research In terms of the main initial idea, transdisciplinarity is formed as a global approach. The global approach should have a traditional institutional form: it should be a science discipline (meta-discipline) and have carriers with the transdisciplinary worldview. Training for such carriers can be organized by the universities within the limits of the systems transdisciplinarity departments and Centers of Systems Transdisciplinary Retraining for Disciplinary Specialists. Thus, it is reasonable to initiate discussion for the idea to reform the disciplinary structure of the universities considering creation of such departments and centers.

This paper contributes to the limited research on roles ICT can play in impression-management strategies and is based on case studies done in the Swedish Police. It also gives a theoretical contribution by adopting a holistic approach to explain how ICT can contribute to giving a misleading picture of conditions. Output generated by ICT has nowadays a central role in follow-up activities and decision-making. Even if this type of output, often in colourful, presentable, graphical arrangements, gives the impression of being accurate and reliable there is a risk of defective data quality. The phenomena can be described as a process divided into five steps. The first step is about how the data is generated and/or collected. The second step is linked to how the data is registered. The third step is about the output generated from the ICT-systems. The fourth step is how the output of ICT is selected for presentation. The fifth step concerns how output generated by ICT is interpreted. This paper shows that ICT can easily be used in impression-management strategies. For example, that personnel take shortcuts to affect the statistics rather than applying methods that may give the desired effects.

Power differences affect implementation of information and communication technology (ICT) in a way that creates differences in ICT use. Involuntary non-use of new ICT at work occurs when employees want to use the new technology, but are unable to due to factors beyond their control. Findings from an in-depth qualitative study show how involuntary non-use of new ICT can be attributed to power differences between occupational groups in the same organization. The findings suggest that experience is a moderating variable and that closeness to formal power holders as well as closeness to the new technology increases the probability for expert control of the ICT-organization processes. These power differences favor ICT experts over ICT novices and result in a high-quality learning environment for the ICT experts characterized by autonomy, inclusion, and adequate work processes and technological solutions. The ICT novices try to navigate in a learning-hostile work environment characterized by marginalization through expert control, isolation, and inadequate work processes and technological solutions. This led to involuntary non-use by the ICT novices, while the experts became more proficient in ICT use. These findings give managers facing a technological organizational change tools to understand important mechanisms for implementing the change in their own organization, and help them take the right actions to integrate new technology and new organization of work.

Together, the fields of education and information technology have identified the need for an online solution to training. The introduction of e-learning has optimised the learning process, allowing organisations to realise the many advantages that e-learning offers. The importance of user involvement in the success of e-learning makes it imperative that the forces driving intention to use e-learning and satisfaction thereof be determined. The purpose of this paper is to investigate the relationships between the metrics influencing intention to use and the satisfaction of using e-learning in companies. The results of a survey distributed amongst a South African software development company’s customer base revealed that the 94 respondents have positive enjoyment and self-efficacy levels, and low computer anxiety levels. Correlation analysis revealed significant relationships between enjoyment and self-efficacy and between enjoyment and satisfaction. Companies should therefore ensure that users enjoy using e-learning as it can directly influence satisfaction and self-efficacy.

Information and communication technologies (ICTs) encompassing computer and network hardware and software, and so on, as well as various services and applications associated with them, are assuming a growing presence within the modern homestead and have an indelible impact on the professional and everyday life of people. This research aims to explore factors influencing the successful adoption and usage of ICTs within Polish households. Based on prior literature and practical experiences, a framework of success factors is provided. The required data was collected from a survey questionnaire administered to a sample of Polish households to examine this framework and identifies which factors are of greatest importance for the adoption and usage of ICTs within households in Poland. Based on 751 questionnaires the paper indicates that the adoption of ICTs within households is mainly influenced by the economic status of households and cost of ICTs, perceived economic benefits from the usage of ICTs, technological availability and security of ICTs, ICT competences and awareness, as well as satisfaction with the adoption of ICTs. Furthermore, gender, education, and place of residence do not reflect significant differences on the factors. Yet, there are significant differences among the factors that could be attributed to age. Both, policy makers and ICT providers can benefit from the findings with regard to bridging the gap of ICT adoption and use in the Polish households.

Several studies extended the Technology Acceptance Model (TAM) by examining the antecedents of perceived usefulness and perceived ease of use; the present study looks at demographic aspect of external variables in virtual library use among undergraduate students. The purpose of this study is to identify the demographic factors sex, level of study, cumulative grade point average, and computer knowledge that act as external factors that are antecedents of perceived usefulness and perceived ease of use. The university management makes a large investment in the provision of a virtual library; investigation of the virtual library acceptance by students is important. TAM and theory of reasoned action (TRA) are utilised to theoretically test a model for the extension and to predict virtual library acceptance and usage. In a survey study, data was collected by using a structured questionnaire given to 394 randomly selected participants in a private university. Data were analysed by Pearson product moment correlation, multiple and hierarchical regression. The result of the study is consistent with TAM factors examined for explaining virtual library usage. The extension model accounts for 2.5% variance in perceived usefulness, 2.1% in perceived ease of use, 11.7% - 15.2% on intention to use and 7.2% on actual use of virtual library. Implications of the findings of the study on user’s virtual library training are discussed.

Aim/Purpose: The purpose of this paper is to examine the key research foci, methodologies, and theoretical perspectives adopted by researchers when studying E-government accessibility for persons with disabilities (PWDs), particularly in developing countries. The study aims to develop a conceptual framework for designing accessible E-government for PWDs in developing countries. Background: Studies on E-government accessibility for persons with disabilities in developing countries have been minimal. The few studies conducted until now have failed to integrate PWDs, a population already marginalized, into the digital society. Accessibility has been identified by researchers as a major hindrance to PWDs participating in E-government. It is imperative therefore to examine the manner in which researchers investigate and acquire knowledge about this phenomenon. Methodology : The study synthesizes literature from top IS journals following a systematic literature review approach. The data synthesis focuses on identifying key concepts relating to E-government accessibility for PWDs. Contribution: The study contributes to the field of E-government, with a focus on how E-government services can be made accessible to PWDs. The study calls on researchers to reflect on their epistemological and ontological paradigms when examining accessibility of E-government services in developing countries. Findings: The findings show that most researchers focus on the evaluation of E-government websites and predominantly adopt quantitative methods. The study also reveals that the use of technological determinism as a theoretical lens is high among researchers. Recommendations for Practitioners : The study recommends that E-government web developers and policy makers involve PWDs from design to evaluation in the development of E-government applications. Recommendation for Researchers: The study advocates the need to conduct studies on E-government accessibility by employing more qualitative and mixed approaches to gain in-depth and better understanding of the phenomenon. Impact on Society : This study creates greater awareness and points out inadequacies that society needs to address to make E-government more inclusive of and participatory for PWDs. Future Research: Further empirical work is required in order to refine the relevance and applicability of various constructs in EADM so as to arrive at a framework for addressing E-government accessibility for PWDs in developing countries.

Aim/Purpose: This study investigates social media use and its effect on knowledge sharing. Based on the review of related literature, we hypothesised that social media use has a significant effect on outward and inward knowledge sharing. Background: While the notion of social media use in work organisations has been progressively developed, empirical studies linking social media to the context of knowledge sharing have only begun to emerge. Even so, literature on social media use and its impact on public organisation is still tentative and remains a developing area. Methodology: The partial least square method was utilised in testing of hypotheses with data collected from 103 employees, who by virtue of their position and job function(s) interface with the public for the purpose of sharing knowledge via the social media space. Contribution: The study made contributions to the social knowledge management literature in two ways. First, the study developed a research model that links social media use to the two distinct dimensions of knowledge sharing. Second, the study provides a quantitative approach, where statistical techniques were applied to validate the social media use and knowledge sharing link. Findings: Statistically, the public organisations utilise social media partly for knowledge sharing, with its effect being significant on outward knowledge sharing and insignificant on inward knowledge sharing. This indicates that social media were deployed mainly for information dissemination “outward knowledge sharing” and not for stakeholders’ feedback and interaction “inward knowledge sharing”. Recommendations for Practitioners: Public organisations should develop a policy framework and guidelines for social media use to encourage the full use of this technology to inform and interact with stakeholders. It is important for this policy document to adopt best practices regarding interactive spaces so that both knowledge sharing dimensions manifest themselves in social media communications. Second, it is necessary to carry out staff training for the professional use of this technology for knowledge sharing. Recommendation for Researchers: Future studies should extend to more populations in different contexts to validate findings Impact on Society: This paper intends to influence practices adopted by organisations in the public sector to improve the knowledge sharing dimensions via the social media space. Future Research: Future studies may extend to public organisations in other geographical locations around Nigeria. It will be useful for studies to provide an international perspective by sampling public organisations from different countries or by comparing and contrasting the findings of other studies, specifically those from other countries. A longitudinal study should be encouraged to detect advancement or development with regards to the subject matter over a period of time.

Aim/Purpose: This study aims at investigating the factors that influence students’ continuous intention to use Moodle, as an exemplar of learning management systems (LMSs), in the post-adoption phase. Background: Higher education institutions (HEIs) have invested heavily in learning management systems (LMSs), such as Moodle and BlackBoard, as these systems enhance students’ learning and improve their interactions with the educational systems. While most studies on LMSs have focused on the pre-adoption or acceptance phases of this technology, the determinant factors that influence students’ continuance intention to use LMSs have received less attention in the information systems (IS) literature. Methodology: The theoretical model for this study was primarily drawn from the expectation-confirmation model (ECM). A total of 387 Kuwaiti students, from a private American University in the State of Kuwait, participated in this study. Partial least squares (PLS) was employed to analyze the data. Contribution: This study contributes to the existing scientific knowledge in different ways. First, this study extends the expectation confirmation model (ECM) by integrating factors that are important to students’ continuous intention to use LMSs, including system interactivity, effort expectancy, attitude, computer anxiety, self-efficacy, subjective norms, and facilitating conditions. Second, this study adds on a Kuwaiti literature context by focusing on the continuous intention to use LMSs, which is, to the best of our knowledge, the first study that extends and empirically assesses the applicability of the ECM in the LMSs context in a developing country – Kuwait. Third, this study conceptually and empirically differentiates between satisfaction and attitude, as two separate affect constructs, which were taken as interchangeable factors in ECM, and were disregarded by a large number of prior ECM studies concerned with continuous use intention. Finally, this study aims to assist HEIs, faculty members, and systems’ developers in understanding the main factors that influence students’ continuance use intention of LMSs. Findings: While subjective norms were not significant, the results mainly showed that students’ continuous intention to use Moodle is significantly influenced by performance expectancy, effort expectancy, attitude, satisfaction, self-efficacy and facilitating conditions. The study’s results also confirmed that satisfaction and attitude are two conceptually and empirically different constructs, conflicting with the views that these constructs can be taken as interchangeable factors in the ECM. Recommendations for Practitioners: This study offers several useful practical implications. First, given the significant influence of system interactivity on performance expectancy and satisfaction, faculty members should modify their teaching approach by enabling communication and interaction among instructors, students, and peers using the LMS. Second, given the significant influence of performance expectancy, satisfaction, and attitude on continuous intention to use the LMS, HEIs should conduct training programs for students on the effective use of the LMS. This would increase students’ awareness regarding the usefulness of the LMS, enhance their attitude towards the LMS, and improve their satisfaction with the system. Third, given the significant role of effort expectancy in influencing performance expectancy, attitude, and students’ continuous intention to use Moodle, developers and system programmers should design the LMS with easy to use, high quality, and customizable user interface. This, in turn, will not only motivate students’ performance expectancy, but will also influence their attitude and continuous intention to use the system. Recommendation for Researchers: This study conceptually and empirically differentiates between satisfaction and attitude, as two separate affect constructs, which were taken as interchangeable factors in ECM and were disregarded by a large number of prior ECM studies concerned with continuous use intention. Hence, it is recommended that researchers include these two constructs in their research models when investigating continuous intention to use a technology. Impact on Society: This study could be used in other countries to compare and verify the results. Additionally, the research model of this study could also be used to investigate other LMSs, such as Blackboard. Future Research: This study focused on how different factors affected students’ continuous intention to use Moodle but did not consider all determinants of successful system, such as system quality, information quality, and instructional as well as course content quality. Thus, future research should devote attention to the effects of these quality characteristics of LMS.

Aim/Purpose: The main aim of this study is to identify the factors that influence the continuance intention of use of innovative systems by non-academic employees of a private university and associated academic institutions in Bangladesh. Background: The targeted academic institutions have introduced many new online services aimed at improving students’ access to information and services, including a new online library, ERP or online forum, and the jobs-tracking system (JTS). This research is focused only on the JTS for two reasons. First, it is one of the most crucial systems for the Daffodil Family, as it enables efficient working across many institutes spread across the country and abroad. Second, it is employed in a wide variety of organisational institutes, not just the university. This study aims to discover negative factors that lead to a decrease in users’ intentions to continue using the system. The ultimate goal is to improve the motivation among administrative staff to use technology-related innovation by reducing or eliminating the problems. Methodology: G* power analysis was employed to determine the expected sample size. A questionnaire survey was conducted of 211 users of a new job tracking system from a private university in Bangladesh, to collect data for testing the suggested research model. The data was analysed using the structural equation technique, which is a powerful multivariate analysis mechanism. Contribution: This research contributes to the body of literature and helps better understand users’ continuance intention in the post-implementation phase of the JTS. It complements the micro-level examinations of continuance intention of using IT, by building on our understanding of the phenomenon at the individual level. Specifically, this study examines the role of technostress where organisations invest in IT to make their users more comfortable with innovative and new technologies like the JTS. Findings: This research develops a theoretical advancement of the expectation-confirmation theory, with implications for IT managers and senior management dealing with IT-related behaviour. All proposed hypotheses were supported. Specifically, the predictors of exhaustion – work overload, work–life balance, and role ambiguity – are significant. The core factors for satisfaction, perceived usefulness, and confirmation, are also found to be significant. Finally, satisfaction and exhaustion significantly influence continuance intention, in both positive and negative ways. Recommendations for Practitioners: This study gives an idea about some of the difficulties that people face when implementing new and innovative IT, particularly in academia in Bangladesh. It offers insights into strategies the management may want to follow when implementing new technology like the JTS. This study suggests strategies to increase satisfaction and reduce technostress among new users to enhance organisational support for change. Recommendation for Researchers: Methodologically, the study provides researchers about the technique that reduces the threat of the common method bias. First, it created a psychological separation between criterion and predictor variables. Second, the threat of common method variance was actively controlled by modelling a latent method factor and by using marker variables that researchers can use in their work. This study complements the micro-level examinations of continuance intention of using IT by building on our understanding of the phenomenon at the individual level. Researchers can extend this model by integrating other theories. Impact on Society: The findings of the study indicate that work overload, work–life conflict, and role ambiguity create tiredness, leading to lower user satisfaction with the system. Perceived usefulness and confirmation have an increasingly similar effect on users’ satisfaction with the system and their subsequent continuance intention. These findings tell university administrators what measures they should take to improve continuance intention of using innovative technology. Future Research: Future studies could conceptualise a five-factor personality model from the personal perspective of users. This model can also be extended by including the dimensions of absorptive capacity, i.e., the dynamic capabilities of users. Absorptive capacity of understanding, assimilating, and applying might influence the user’s perception of usefulness and confirmation of using JTS.

Aim/Purpose: The first goal is to develop a decision support system for pricing and production amounts for a firm facing high levels of product returns. The second goal is to improve the management of the product returns process. Background: This study was conducted at a food importer and manufacturer in Israel facing a very high rate of product returns, much of which is eventually discarded. The firm’s products are commonly considered to be a low-cost generic alternative and are therefore popular among low-income families. Methodology: A decision support module was added to the plant’s business information system. The module is based on a supply chain pricing model and uses the sales data to infer future demand’s distribution. Ergonomic models were used to improve the design of the returns warehouse and the handling of the returns. Contribution: The decision support system allows to improve the plant’s pricing and quantity planning. Consequently, it reduced the size of product returns. The new design of the returns process is expected to improve worker’s productivity, reduces losses and results in safer outcomes. This study also demonstrates a successful integration and of a theoretical economical model into an information system. Findings: The results show the promise of incorporating pricing supply chain models into informing systems to achieve a practical business task. We were able to construct actual demand distributions from the data and offer actual pricing recommendations that reduce the number of returns while increasing potential profits. We were able to identify key deficiencies in the returns operations and added a module to the decisions support system that improves the returns management and links it with the sales and pricing modules. Finally, we produced a better warehouse design that supports efficient and ergonomic product returns handling. Recommendations for Practitioners: This work can be replicated for different suppliers, manufacturers and retailers that suffer from product returns. They will benefit from the reduction in returns, as well as the decrease in the losses associated with these returns. Recommendation for Researchers: It is worthwhile to research whether decision support systems can be applied to other aspects of the organizations’ operations. Impact on Society: Product returns is a lose-lose situation for producers, retailers and customers. Moreover, mismanagement of these returns is harmful for the environment and may result in the case of foods, in health hazards. Reducing returns and improving the handling improves sustainability and is beneficial for society. Future Research: The decision support system’s underlying pricing model assumes a specific business setting. This can be extended using other pricing models and applying them in a similar fashion to the current application.

Aim/Purpose: The aim of the study is to explore factors that affect how healthcare clients in rural areas use infomediaries in maternal mHealth interventions. The study focuses on maternal healthcare clients who do not own mobile phones but use the mHealth intervention. Background: Maternal mHealth interventions in poor-resource settings are bedevilled by inequalities in mobile phone ownership. Clients who do not own mobile phones risk being excluded from benefiting from the interventions. Some maternal mHealth providers facilitate the access of mobile phones for those who do not own them using “infomediaries”. Infomediaries, in this case, refer to individuals who have custody of mobile phones that other potential beneficiaries may use. However, the use of infomediaries to offer access to the “have nots” may be influenced by a number of factors. Methodology: The study uses a case of a maternal mHealth intervention project in Malawi, as well as a qualitative research method and interpretive paradigm. Data was collected using secondary data from the implementing agency, semi-structured interviews, and focus group discussions. Empirical data was collected from maternal healthcare clients who do not own mobile phones and infomediaries. Data were analysed inductively using thematic analysis. Contribution: The study proposed a theoretical framework for studying infomediaries in ICT4D. The study may inform mHealth designers, implementers, and policymakers on how infomediaries could be implemented in a rural setting. Consequently, understanding the factors that affect the use of infomediaries may inform mHealth intervention implementers on how they could overcome the challenges by implementing mHealth interventions that reduce the challenges on the mHealth infomediaries side, and the maternal healthcare clients’ side. Findings: Characteristics of the maternal healthcare client, characteristics of the mHealth infomediary, perceived value of mHealth intervention, and socio-environmental factors affect maternal healthcare clients’ use of mHealth infomediaries. Recommendations for Practitioners: Implementers of interventions ought to manage the use of infomediaries to avoid volunteer fatigue and infomediaries who may not be compatible with the potential users of the intervention. Implementers could leverage traditional systems of identifying and using infomediaries instead of reinventing the wheel. Recommendation for Researchers: This research adopted a single case study to develop the theoretical framework for mHealth infomediary use. We recommend future studies are conducted in order to test and develop this framework further, not only in ICT4D, but also in other areas of application. Impact on Society: People still lack access. The lack of ownership of technology may still exclude them from participating in an information society. The use of infomediaries may help to provide access to technologies to those who do not have them thereby bridging the digital divide gap. Future Research: We propose herein that traditional systems may offer a good starting point for designing a system that would work for communities. We, therefore, recommend that future research may explore these possibilities.

Aim/Purpose: The aim of this study was to explore the factors driving individuals’ behavioral intention to use cryptocurrency in Saudi Arabia using the extended TRA model. Background: Despite the great potential of cryptocurrencies and the exponential growth of cryptocurrency use throughout the world, scholarly research on this topic remained scarce. Whereas prior studies are mostly done in developed countries or specific cultural contexts, limiting the generalizability of their results, they mainly used technology adoption models that cannot fully explain the acceptance of new technology involved with financial transactions such as cryptocurrency and provided contradictory evidence. Entire regions have been excluded from the research on this topic, including Saudi Arabia which has a high potential to increase the volume of cryptocurrency use. Methodology: This study extends the theory of reasoned action (TRA) with the factors from technology adoption models that proved relevant for this topic, namely perceived usefulness, perceived enjoyment, perceived innovativeness, and perceived risk with three sub-factors: security, financial, and privacy risk. Data are collected using a quantitative research methodology from 181 respondents residing in Saudi Arabia and then analyzed by several methods, including exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM). Contribution: This study contributes to the scientific knowledge by extending the TRA model with a range of factors from the technology adoption field, thus enabling the analysis of this topic from human, financial, and technology perspectives and providing additional empirical evidence on the factors that previously either provided contradictory evidence or were not explored in this field. This research also provides the first empirical data on this topic in Saudi Arabia and enables further research on the topic and a comparison of the results. The study also contributes to practice by enhancing the actual understanding of the phenomena and providing valuable information and recommendations for governments, investors, merchants, developers, and the general population. Findings: The study found attitude, subjective norm, perceived usefulness, perceived enjoyment, personal innovativeness, privacy risk, and financial risk as significant predictors of the intention to use cryptocurrencies, whereas the influence of security risk was not found to be significant in Saudi Arabia. Recommendations for Practitioners: Using this study’s results, governments can create appropriate legal frameworks, developers can design fewer complex platforms, and merchants may create appropriate campaigns that emphasize the benefits of cryptocurrency use and transpire trust in cryptocurrency transactions by enhancing the factors with a positive impact, such as usefulness, enjoyment, and personal innovativeness while reducing concerns of potential users regarding the risky factors. By promoting a positive user experience, they can also improve attitudes and social norms towards cryptocurrencies, thus further stimulating the interest in their use. Recommendation for Researchers: As this study validated the influence of factors from technology, financial, and human-related fields, researchers may follow this approach to ensure a comprehensive analysis of this complex topic, especially as privacy risk was never examined in this context, while personal innovativeness, perceived enjoyment, financial, and security risk were explored in just a few studies. It is also recommended that researchers explore the impact of each part of subjective norms: social media, friends, and family, as well as how information on the benefits of cryptocurrencies affects the perception of the factors included. Impact on Society: Understanding the factors affecting cryptocurrency use can help utilize the full potential of cryptocurrencies, especially their benefits for developing countries reflected in safe, speedy, and low-cost financial transactions with no need for an intermediary. The research model of this study could also be used to investigate this topic in other contexts to discover similarities and differences, as well as to investigate other information systems. Future Research: Future studies should test this research model in similar and different contexts to determine whether its validity and study results depend on cultural and contextual factors. They can also include different or additional variables, or use mixed methods, as interviews would augment the comprehension of this topic. Future studies may also explore whether the impact of variables would remain the same if circumstances changed or use cases expanded, and how the preferences of the target population would change within a longitudinal time frame.

Aim/Purpose: This study aims to develop a comprehensive conceptual framework that incorporates personal characteristics, social context, and technological features as significant factors that influence the intention of small-city users in China to use mobile health. Background: Mobile health has become an integral part of China’s health management system innovation, the transformation of the health service model, and a necessary government measure for promoting health service parity. However, mobile health has not yet been widely adopted in small cities in China. Methodology: The study utilized a quantitative approach whereby web-based questionnaires were used to collect data from 319 potential users in China using China’s health management system. The data was analyzed using the PLS-SEM (the partial least squares-structural equation modeling) approach. Contribution: This study integrates the protection motivation theory (PMT), which compensates for the limitations of the unified theory of acceptance and use of technology theory (UTAUT) and is a re-examination of PMT and UTAUT in a small city context in China. Findings: The findings indicate that attitude and perceived vulnerability in the personal characteristic factors, social influence and facilitating conditions in the social context factors, and performance expectancy in the technological feature factors influence users’ intention to use mobile health in small cities in China. Recommendations for Practitioners: This study provides feasible recommendations for mobile health service providers, medical institutions, and government agencies based on the empirical results. Recommendation for Researchers: As for health behavior, researchers should fully explain the intention of mobile health use in terms of holism and health behavior theory. Impact on Society: This study aims to increase users’ intention to use mobile health in small cities in China and to maximize the social value of mobile health. Future Research: Future research should concentrate on the actual usage behavior of users and simultaneously conduct a series of longitudinal studies, including studies on continued usage behavior, abandonment behavior, and abandoned-and-used behavior.

Aim/Purpose: The aim of this research paper is to suggest a comprehensive model that incorporates the technology acceptance model with the task-technology fit model, information quality, security, trust, and managerial support to investigate the intended usage of big data analytics (BDA) in banks and insurance companies. Background: The emergence of the concept of “big data,” prompted by the widespread use of connected devices and social media, has been pointed out by many professionals and financial institutions in particular, which makes it necessary to assess the determinants that have an impact on behavioral intention to use big data analytics in banks and insurance companies. Methodology: The integrated model was empirically assessed using self-administered questionnaires from 181 prospective big data analytics users in Moroccan banks and insurance firms and examined using partial least square (PLS) structural equation modeling. The results cover sample characteristics, an analysis of the validity and reliability of measurement models’ variables, an evaluation of the proposed hypotheses, and a discussion of the findings. Contribution: The paper makes a noteworthy contribution to the BDA adoption literature within the finance sector. It stands out by ingeniously amalgamating the Technology Acceptance Model (TAM) with Task-Technology Fit (TTF) while underscoring the critical significance of information quality, trust, and managerial support, due to their profound relevance and importance in the finance domain. Thus showing BDA has potential applications beyond the finance sector. Findings: The findings showed that TTF and trust’s impact on the intention to use is considerable. Information quality positively impacted perceived usefulness and ease of use, which in turn affected the intention to use. Moreover, managerial support moderates the correlation between perceived usefulness and the intention to use, whereas security did not affect the intention to use and managerial support did not moderate the influence of perceived ease of use. Recommendations for Practitioners: The results suggest that financial institutions can improve their adoption decisions for big data analytics (BDA) by understanding how users perceive it. Users are predisposed to use BDA if they presume it fits well with their tasks and is easy to use. The research also emphasizes the importance of relevant information quality, managerial support, and collaboration across departments to fully leverage the potential of BDA. Recommendation for Researchers: Further study may be done on other business sectors to confirm its generalizability and the same research design can be employed to assess BDA adoption in organizations that are in the advanced stage of big data utilization. Impact on Society: The study’s findings can enable stakeholders of financial institutions that are at the primary stage of big data exploitation to understand how users perceive BDA technologies and the way their perception can influence their intention toward their use. Future Research: Future research is expected to conduct a comparison of the moderating effect of managerial support on users with technical expertise versus those without; in addition, international studies across developed countries are required to build a solid understanding of users’ perceptions towards BDA.

Aim/Purpose: This study aims to create customer segmentation who use Online Travel Agent (OTA) mobile applications in Indonesia throughout their hotel booking journey. Background: In the context of mobile hotel booking applications, research analyzing the customer experience at each customer journey stage is scarce. However, literature increasingly acknowledges the significance of this stage in comprehending customer behavior and revenue streams. Methodology: This study employs a mixed-method and exploratory approach by doing in-depth interviews with 20 participants and questionnaires from 207 participants. Interview data are analyzed using thematic analysis, while the questionnaires are analyzed using descriptive statistics. Contribution: This study enriches knowledge in understanding customer behavior that considers the usage of mobile apps as a segmentation criterion in the hotel booking journey. Findings: We developed four user personas (no sweat player, spotless seeker, social squad, and bargain hunter) that show customer segmentation based on the purpose, motivation, and actions in each journey stage (inspiration, consideration, reservation, and experience). Recommendations for Practitioners: The resulting customer segmentation enables hospitality firms to improve their current services by adapting to the needs of various segments and avoiding unanticipated customer pain points, such as incomplete information, price changes, no social proof, and limited payment options. Recommendation for Researchers: The quality and robustness of the customer segment produced in this study can be further tested based on the criteria of homogeneity, size, potential benefits, segment stability, segment accessibility, segment compatibility, and segment actionability. Impact on Society: This study has enriched the existing literature by establishing a correlation between user characteristics and how they use smartphones for tourism planning, focusing on hotel booking in mobile applications. Future Research: For future research, each customer segment’s demographic and behavioral factors can be explored further.

Aim/Purpose: The UAE and other Middle Eastern countries suffer from various cybersecurity vulnerabilities that are widespread and go undetected. Still, many UAE government organizations rely on human-centric approaches to combat the growing cybersecurity threats. These approaches are ineffective due to the rapid increase in the amount of data in cyberspace, hence necessitating the employment of intelligent technologies such as AI cybersecurity systems. In this regard, this study investigates factors influencing users’ intention to adopt AI-based cybersecurity systems in the UAE. Background: Even though UAE is ranked among the top countries in embracing emerging technologies such as digital identity, robotic process automation (RPA), intelligent automation, and blockchain technologies, among others, it has experienced sluggish adoption of AI cybersecurity systems. This selectiveness in adopting technology begs the question of what factors could make the UAE embrace or accept new technologies, including AI-based cybersecurity systems. One of the probable reasons for the slow adoption and use of AI in cybersecurity systems in UAE organizations is the employee’s perception and attitudes towards such intelligent technologies. Methodology: The study utilized a quantitative approach whereby web-based questionnaires were used to collect data from 370 participants working in UAE government organizations considering or intending to adopt AI-based cybersecurity systems. The data was analyzed using the PLS-SEM approach. Contribution: The study is based on the Protection Motivation Theory (PMT) framework, widely used in information security research. However, it extends this model by including two more variables, job insecurity and resistance to change, to enhance its predictive/exploratory power. Thus, this research improves PMT and contributes to the body of knowledge on technology acceptance, especially in intelligent cybersecurity technology. Findings: This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. All the hypotheses were accepted. The relationship between the six constructs (perceived vulnerability (PV), perceived severity (PS), perceived response efficacy (PRE), perceived self-efficacy (PSE), job insecurity (JI), and resistance to change (RC)) and the intention to adopt AI cybersecurity systems in the UAE was found to be statistically significant. This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. 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. PSE and PRE were found to be positively related to the intention to adopt AI-based cybersecurity systems, suggesting the need for practitioners to focus on them. The government can enact legislation that emphasizes the simplicity and awareness of the benefits of cybersecurity systems in organizations. Recommendation for Researchers: Further research is needed to include other variables such as facilitating conditions, AI knowledge, social influence, and effort efficacy as well as other frameworks such as UTAUT, to better explain individuals’ behavioral intentions to use cybersecurity systems in the UAE. Impact on Society: This study can help all stakeholders understand what factors can increase users’ interest in investing in the applications that are embedded with security. As a result, they 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 cybersecurity systems such as facilitating conditions, AI knowledge, social influence, effort efficacy, as well other variables from UTAUT. International research across nations is also required to build a larger sample size to examine the behavior of users.

Aim/Purpose. COVID-19 was an unprecedented disruptive event that accelerated the shift to remote work and encouraged widespread adoption of digital tools in organizations. This empirical study was conducted from an organizational-strategic perspective, with the aim of examining how the COVID-19 pandemic outbreak affected employees’ use of organizational information systems (IS) as reflected in frequency. Background. To date, only a limited effort has been made, and a rather narrow perspective has been adopted, regarding the consequences of the adoption of new work environments following COVID-19. It seems that the literature is lacking in information regarding employee use of organizational IS since the outbreak of the pandemic. Specifically, this issue has not yet been examined in relation to employees’ perception about the organization’s digital efforts and technological maturity for remote work. The present study bridges this gap. Methodology. The public sector in Israel, which employs about a third of the Israeli work-force, was chosen as a case study of information-intensive organizations. During the first year of COVID-19, 716 questionnaires were completed by employees and managers belonging to four government ministries operating in Israel. The responses were statistically analyzed using a Chi-Square and Spearman’s Rho tests. Contribution. Given that the global pandemic is an ongoing phenomenon and not a passing episode, the findings provide important theoretical and practical contributions. The period prior to the COVID-19 pandemic and the period of the pandemic are compared with regard to organizational IS use. Specifically, the study sheds new light on the fact that employee perceptions motivated increased IS use during an emergency. The results contribute to the developing body of empirical knowledge in the IS field in the era of digital transformation (DT). Findings. More than half of the respondents who reported that they did not use IS before COVID-19 stated that the pandemic did not change this. We also found a significant positive correlation between the perception of the digital efforts made by organizations to enable connection to the IS for remote work and a change in frequency of IS use. This frequency was also found to have a significant positive correlation with the perception of the organization’s technological maturity to enable effective and continuous remote work. Recommendations for Practitioners. In an era of accelerating DT, this paper provides insights that may support chief information officers and chief digital officers in understanding how to promote the use of IS. The results can be useful for raising awareness of the importance of communicating managerial messages for employees regarding the organizational strategy and the resilience achieved through IS not only in routine, but also in particular in emergency situations. Recommendations for Researchers. Considering that the continual crisis has created challenges in IS research, it is appropriate to continue researching the adaptation and acclimation of organizations to the “new normal”. Impact on Society. The COVID-19 pandemic created a sudden change in employment models, which have become more flexible than ever. The research insights enrich the knowledge about the concrete consequences of this critical change. Future Research. We suggest that researchers investigate this core issue in other sectors and/or other countries, in order to be obtain new and complementary empirical insights on a comparative basis.

Aim/Purpose: The primary purpose of this study is to investigate the factors that impact the behavioral intention to use social media (SM) for knowledge sharing (KS) in the disaster relief (DR) context. Background: With the continuing growth of SM for KS in the DR environment, disaster relief organizations across the globe have started to realize its importance in streamlining their processes in the post-implementation phase. However, SM-based KS depends on the willingness of members to share their knowledge with others, which is affected by several technological, social, and organizational factors. Methodology: A survey was conducted in Somalia to gather primary data from DR practitioners, using purposive sampling as the technique. The survey collected 214 valid responses, which were then analyzed with the PLS-SEM approach. Contribution: The study contributes to an understanding of the real-life hurdles faced by disaster relief organizations by expanding on the C-TAM-TPB model with the inclusion of top management support, organizational rewards, enjoyment in helping others, knowledge self-efficacy, and interpersonal trust factors. Additionally, it provides useful recommendations to managers of disaster relief organizations on the key factors to consider. Findings: The findings recorded that perceived usefulness, ease of use, top management support, enjoyment in helping others, knowledge self-efficacy, and interpersonal trust were critical factors in determining behavioral intention (BI) to use SM-based KS in the DR context. Furthermore, the mediator variables were attitude, subjective norms, and perceived behavioral control. Recommendations for Practitioners: Based on the research findings, it was determined that management should create different discussion forums among the disaster relief teams to ensure the long-term use of SM-based KS within DR organizations. They should also become involved in the discussions for disaster-related knowledge such as food supplies, shelter, or medical relief that disaster victims need. Disaster relief managers should consider effective and adequate training to enhance individual knowledge and self-efficacy since a lack of training may increase barriers and difficulties in using SM for KS during a DR process. Recommendation for Researchers: The conceptual model, further empirically investigated, can be employed by other developing countries in fostering acceptance of SM for KS during disaster relief operations. Impact on Society: Disaster relief operations can be facilitated using social media by considering the challenges DR practitioners face during emergencies. Future Research: In generalizing this study’s findings, other national or global disaster relief organizations should consider, when applying and testing, the research instruments and proposed model. The researchers may extend this study by collecting data from managers or administrators since they are different types of users of the SM-based KS system.

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 aims to explore the use of mobile health applications (mHealth apps) by lay users in Kuwait. Specifically, it seeks to: (i) identify and highlight the impact of factors that contribute to their use of mHealth apps and (ii) validate a model of these users’ usage of mHealth apps. Background: The advancement of information technologies has paved the way for efficiency and effectiveness in healthcare sectors in developed countries. Kuwait has attempted to revolutionise healthcare systems through mobile applications of information technology solutions to educate users on better methods of receiving customised health services. However, end-user usage of mHealth apps remains in the infancy in developing countries, including Kuwait. Lay users are often vulnerable and frequently overlooked by researchers and health technology providers. Methodology: A cross-sectional study was conducted among 225 lay users of mHealth apps in Kuwait using an online questionnaire to achieve the study objectives. A purposive sampling method utilising convenience and snowballing sampling techniques was used in which all the respondents were lay users. Descriptive statistics, Pearson correlation, and regression analyses were employed to analyse the collected data. Contribution: The study contributes to the extant literature on health informatics and mHealth by providing a comprehensive understanding of how technological, social, and functional factors are related to mHealth apps in the context of developing countries. It identifies key drivers of mHealth app use, suggests expanding the TAM model, and facilitates comparisons with developed countries, addressing gaps in mHealth research. Findings: Four factors (i.e., perceived trust (PT), perceived ease of use (PEU) and behaviour control (PBC), perceived usefulness (PU), and subjective norms (SN)) were identified that influence the use of mHealth apps. These four identified factors also contributed to lay users’ use of these mHealth apps. Among these four factors, perceived trust (PT) was the main contributor to lay users’ use of these mHealth apps. Recommendations for Practitioners: Based on the empirical results, this study provides feasible recommendations for the government, healthcare providers, and developers of mHealth apps. The findings urge developers to enhance app functionality by prioritising privacy and security to build user trust while outlining guidelines for future development focused on user-centric design and compliance with data privacy regulations. Additionally, the government should establish supportive policies and funding, ensure regulatory oversight, and promote public awareness to foster trust. Healthcare providers should integrate mHealth apps into their services, train staff for practical use, gather users’ feedback, and collaborate with developers to create tailored healthcare solutions. Future Research: Additional research is required to apply probability sampling techniques and increase the sample size to generate more reliable and generalisable findings. Additionally, the young age segment must be considered here, and research must be extended to consider the moderating role of demographic factors like age, gender, and educational levels to better understand the adoption of mHealth apps.

Aim/Purpose: This study aims to develop a solution for personalized tourism recommendations that addresses information overload, data sparsity, and the cold-start problem. It focuses on enabling tourists to choose the most suitable tourism-related facilities, such as restaurants and hotels, that match their individual needs and preferences. Background: The tourism industry is experiencing a significant shift towards digitalization due to the increasing use of online platforms and the abundance of user data. Travelers now heavily rely on online resources to explore destinations and associated options like hotels, restaurants, attractions, transportation, and events. In this dynamic landscape, personalized recommendation systems play a crucial role in enhancing user experience and ensuring customer satisfaction. However, existing recommendation systems encounter major challenges in precisely understanding the complexities of user preferences within the tourism domain. Traditional approaches often rely solely on user ratings, neglecting the complex nature of travel choices. Data sparsity further complicates the issue, as users might have limited interactions with the system or incomplete preference profiles. This sparsity can hinder the effectiveness of these systems, leading to inaccurate or irrelevant recommendations. The cold-start problem presents another challenge, particularly with new users who lack a substantial interaction history within the system, thereby complicating the task of recommending relevant options. These limitations can greatly hinder the performance of recommendation systems and ultimately reduce user satisfaction with the overall experience. Methodology: The proposed User-based Multi-Criteria Trust-aware Collaborative Filtering (UMCTCF) approach exploits two key aspects to enhance both the accuracy and coverage of recommendations within tourism recommender systems: multi-criteria user preferences and implicit trust networks. Multi-criteria ratings capture the various factors that influence user preferences for specific tourism items, such as restaurants or hotels. These factors surpass a simple one-star rating and take into account the complex nature of travel choices. Implicit trust relationships refer to connections between users that are established through shared interests and past interactions without the need for explicit trust declarations. By integrating these elements, UMCTCF aims to provide more accurate and reliable recommendations, especially when data sparsity limits the ability to accurately predict user preferences, particularly for new users. Furthermore, the approach employs a switch hybridization scheme, which combines predictions from different components within UMCTCF. This scheme leads to a more robust recommendation strategy by leveraging diverse sources of information. Extensive experiments were conducted using real-world tourism datasets encompassing restaurants and hotels to evaluate the effectiveness of UMCTCF. The performance of UMCTCF was then compared against baseline methods to assess its prediction accuracy and coverage. Contribution: This study introduces a novel and effective recommendation approach, UMCTCF, which addresses the limitations of existing methods in personalized tourism recommendations by offering several key contributions. First, it transcends simple item preferences by incorporating multi-criteria user preferences. This allows UMCTCF to consider the various factors that users prioritize when making tourism decisions, leading to a more comprehensive understanding of user choices and, ultimately, more accurate recommendations. Second, UMCTCF leverages the collective wisdom of users by incorporating an implicit trust network into the recommendation process. By incorporating these trust relationships into the recommendation process, UMCTCF enhances its effectiveness, particularly in scenarios with data sparsity or new users with limited interaction history. Finally, UMCTCF demonstrates robustness towards data sparsity and the cold-start problem. This resilience in situations with limited data or incomplete user profiles makes UMCTCF particularly suitable for real-world applications in the tourism domain. Findings: The results consistently demonstrated UMCTCF’s superiority in key metrics, effectively addressing the challenges of data sparsity and new users while enhancing both prediction accuracy and coverage. In terms of prediction accuracy, UMCTCF yielded significantly more accurate predictions of user preferences for tourism items compared to baseline methods. Furthermore, UMCTCF achieved superior coverage compared to baseline methods, signifying its ability to recommend a wider range of tourism items, particularly for new users who might have limited interaction history within the system. This increased coverage has the potential to enhance user satisfaction by offering a more diverse and enriching set of recommendations. These findings collectively highlight the effectiveness of UMCTCF in addressing the challenges of personalized tourism recommendations, paving the way for improved user satisfaction and decision-making within the tourism domain. Recommendations for Practitioners: The proposed UMCTCF approach offers a potential opportunity for tourism recommendation systems, enabling practitioners to create solutions that prioritize the needs and preferences of users. By incorporating UMCTCF into online tourism platforms, tourists can utilize its capabilities to make well-informed decisions when selecting tourism-related facilities. Furthermore, UMCTCF’s robust design allows it to function effectively even in scenarios with data sparsity or new users with limited interaction history. This characteristic makes UMCTCF particularly valuable for real-world applications, especially in scenarios where these limitations are common obstacles. Recommendation for Researchers: The success of UMCTCF can open up new avenues in personalized recommendation research. One promising direction lies in exploring the integration of additional contextual information, such as temporal (time-based) or location-based information. By incorporating these elements, the model could be further improved, allowing for even more personalized recommendations. Furthermore, exploring the potential of UMCTCF in domains other than tourism has considerable significance. By exploring its effectiveness in other e-commerce domains, researchers can broaden the impact of UMCTCF and contribute to the advancement of personalized recommendation systems across various industries. Impact on Society: UMCTCF has the potential to make a positive impact on society in various ways. By delivering accurate and diverse recommendations that are tailored to individual user preferences, UMCTCF fosters a more positive and rewarding user experience with tourism recommendation systems. This can lead to increased user engagement with tourism platforms, ultimately enhancing overall satisfaction with travel planning. Furthermore, UMCTCF enables users to make more informed decisions through broader and more accurate recommendations, potentially reducing planning stress and leading to more fulfilling travel experiences. Future Research: Expanding upon the success of UMCTCF, future research activities can explore several promising paths. Enriching UMCTCF with various contextual data, such as spatial or location-based data, to enhance recommendation accuracy and relevance. Leveraging user-generated content, like reviews and social media posts, could provide deeper insights into user preferences and sentiments, improving personalization. Additionally, applying UMCTCF in various e-commerce domains beyond tourism, such as online shopping, entertainment, and healthcare, could yield valuable insights and enhance recommendation systems. Finally, exploring the integration of optimization algorithms could improve both recommendation accuracy and efficiency.

Aim/Purpose: This study aims to evaluate the success of deep learning in building user profiles for personalized information access. Background: To better express document content and information during the matching phase of the information retrieval (IR) process, deep learning architectures could potentially offer a feasible and optimal alternative to user profile building for personalized information access. Methodology: This study uses deep learning-based models to deduce the domain of the document deemed implicitly relevant by a user that corresponds to their center of interest, and then used predicted domain by the best given architecture with user’s characteristics to predict other centers of interest. Contribution: This study contributes to the literature by considering the difference in vocabulary used to express document content and information needs. Users are integrated into all research phases in order to provide them with relevant information adapted to their context and their preferences meeting their precise needs. To better express document content and information during this phase, deep learning models are employed to learn complex representations of documents and queries. These models can capture hierarchical, sequential, or attention-based patterns in textual data. Findings: The results show that deep learning models were highly effective for building user profiles for personalized information access since they leveraged the power of neural networks in analyzing and understanding complex patterns in user behavior, preferences, and user interactions. Recommendations for Practitioners: Building effective user profiles for personalized information access is an ongoing process that requires a combination of technology, user engagement, and a commitment to privacy and security. Recommendation for Researchers: Researchers involved in building user profiles for personalized information access play a crucial role in advancing the field and developing more innovative deep-based networks solutions by exploring novel data sources, such as biometric data, sentiment analysis, or physiological signals, to enhance user profiles. They can investigate the integration of multimodal data for a more comprehensive understanding of user preferences. Impact on Society: The proposed models can provide companies with an alternative and sophisticated recommendation system to foster progress in building user profiles by analyzing complex user behavior, preferences, and interactions, leading to more effective and dynamic content suggestions. Future Research: The development of user profile evolution models and their integration into a personalized information search system may be confronted with other problems such as the interpretability and transparency of the learning-based models. Developing interpretable machine learning techniques and visualization tools to explain how user profiles are constructed and used for personalized information access seems necessary to us as a future extension of our work.

Aim/Purpose: The research aims to investigate the factors that influence the continuous use of mobile banking applications to complete banking monetary transactions. Background: Despite a significant increase in the use of mobile banking applications, particularly during the COVID-19 pandemic, new evidence indicates that the use rate of mobile banking applications for operating banking monetary transactions has declined. Methodology: The study proposed an integrated model based mainly on the process virtualization theory (PVT) with other novel factors such as mobile banking application anthropomorphism and virtual process failure risk. The study model was empirically validated using structural equation modeling analysis on quantitative data from 484 mobile banking application users from Jordan. Contribution: The study focuses on continuing use or post-adoption behavior rather than pre-adoption behavior. This is important since the maximum and long-term viability, as well as the financial investment in mobile banking applications, depend on regular usage rather than first-time use or initial experience. Findings: The results indicate that process virtualizable and anthropomorphism have a strong positive impact on bank customers’ decisions to continue using mobile banking applications to complete banking monetary transactions. Meanwhile, the negative impact of virtualization process failure risk on continuous use has been discovered. The found factors explain 67.5% of the variance in continuous use. Recommendations for Practitioners: The study identified novel, significant factors that affect bank customers’ decisions to use mobile banking applications frequently, and these factors should be examined, matched, satisfied, or addressed when redesigning or upgrading mobile applications. Banks should provide users with clear directions, processes, or tutorials on how to complete monetary transactions effectively. They should also embrace Artificial Intelligence (AI) technology to improve their applications and products with anthropomorphic features like speech synthesizers, Chatbots, and AI-powered virtual bank assistants. This is expected to help bank customers conduct various banking services conveniently and securely, just as if interacting with real people. The study further recommends that banks create and publish clear norms and procedures, as well as promote tolerance and protect consumers’ rights when the process fails or mistakes occur. Recommendation for Researchers: The study provides measurement items that were specifically built for the context of mobile banking applications based on PVT notions. Researchers are invited to reuse, test, and modify existing measurement items, as well as submit new ones if necessary. The study model does not consider psychological aspects like trust and satisfaction, which would provide additional insight into factors affecting continuing use. Researchers could potentially take a different approach by focusing on user resistance and non-adoption. Impact on Society: Financial inclusion is problematic, particularly in underdeveloped nations. According to financial inclusion research, Jordanians rarely utilize mobile banking apps. Continuous usage of mobile banking applications will be extremely beneficial in closing the financial inclusion gap, particularly among women. Furthermore, it could help the country’s efforts to transition to a digital society. Future Research: The majority of study participants are from urban areas. Future studies should focus on consumers who live in rural areas. It was also suggested that the elderly be targeted because they may have different views/perspectives on the continued use of mobile banking applications.

Aim/Purpose: This study investigates the drivers of user satisfaction in e-government services and its influence on continued use intention and citizen trust in government. It employs the integration of the Technology Acceptance Model (TAM) and the Information System Success Model (ISSM). Background: Electronic government, transforming citizen-state interactions, has gained momentum worldwide, including in India, where the aim is to leverage technology to improve citizen services, streamline administration, and engage the public. While prior research has explored factors influencing citizen satisfaction with e-government services globally, this area of study has been relatively unexplored in India, particularly in the post-COVID era. Challenges to widespread e-government adoption in India include a large and diverse population, limited digital infrastructure in rural areas, low digital literacy, and weak data protection regulations. Additionally, global declines in citizen trust, attributed to economic concerns, corruption, and information disclosures, further complicate the scenario. This study seeks to investigate the influence of various factors on user satisfaction and continuance usage of e-government services in India. It also aims to understand how these services contribute to building citizens’ trust in government. Methodology: The data were collected by utilizing survey items on drivers of e-government services, user satisfaction, citizen trust, and continuance use intention derived from existing literature on information systems and e-government. Responses from 501 Indian participants, collected using an online questionnaire, were analyzed using PLS-SEM. Contribution: This study makes a dual contribution to the e-government domain. First, it introduces a comprehensive research model that examines factors influencing users’ satisfaction and continuance intention with e-government services. The proposed model integrates the TAM and ISSM. Combining these models allows for a comprehensive examination of e-government satisfaction and continued intention. By analyzing the impact of user satisfaction on continuance intention and citizen trust through an integrated model, researchers and practitioners gain insights into the complex dynamics involved. Second, the study uncovers the effects of residential status on user satisfaction, trust, and continuance intention regarding e-government services. Findings reveal disparities in the influence of system and service quality on user satisfaction across different user segments. Researchers and policymakers should consider these insights when designing e-government services to ensure user satisfaction, continuance intention, and the building of citizen trust. Findings: The findings indicate that the quality of information, service, system, and perceived usefulness play important roles in user satisfaction with e-government services. All hypothesized paths were significant, except for perceived ease of use. Furthermore, the study highlights that user satisfaction significantly impacts citizen trust and continuance use intention. Recommendations for Practitioners: The findings suggest that government authorities should focus on delivering accurate, comprehensive, and timely information in a secure, glitch-free, and user-friendly digital environment. Implementing an interactive and accessible interface, ensuring compatibility across devices, and implementing swift query resolution mechanisms collectively contribute to improving users’ satisfaction. Conducting awareness and training initiatives, providing 24×7 access to online tutorials, helpdesks, technical support, clear FAQs, and integrating AI-driven customer service support can further ensure a seamless user experience. Government institutions should leverage social influence, community engagement, and social media campaigns to enhance user trust. Promotional campaigns, incentive programs, endorsements, and user testimonials should be used to improve users’ satisfaction and continuance intention. Recommendation for Researchers: An integrated model combining TAM and ISSM offers a robust approach for thoroughly analyzing the diverse factors influencing user satisfaction and continuance intention in the evolving digitalization landscape of e-government services. This expansion, aligning with ISSM’s perspective, enhances the literature by demonstrating how user satisfaction impacts continuance usage intention and citizen trust in e-government services in India and other emerging economies. Impact on Society: Examining the factors influencing user satisfaction and continuance intention in e-government services and their subsequent impact on citizen trust carries significant societal implications. The findings can contribute to the establishment of transparent and accountable governance practices, fostering a stronger connection between governments and their citizens. Future Research: There are several promising avenues to explore to enhance future research. Expanding the scope by incorporating a larger sample size could enable a more thorough analysis. Alternatively, delving into the performance of specific e-government services would offer greater precision, considering that this study treats e-government services generically. Additionally, incorporating in-depth interviews and longitudinal studies would yield a more comprehensive understanding of the dynamic evolution of digitalization.

This study seeks to explore what factors influence students’ ICT use and web technology competence. The objectives of this study are the following: (a) To what extent do certain elements of Rogers’ (2003) Diffusion of Innovations Theory (DOI) explain students’ ICT use, (b) To what extent do personality characteristics derived from the Big Five approach explain students’ ICT use, and (c) To what extent does motivation explain students’ ICT use. The research was conducted in Israel during the second semester of the academic year 2013-14, and included two groups of participants: a group of Educational Technology students (ET) and a group of Library and Information Science students (LIS). Findings add another dimension to the importance of Rogers’ DOI theory in the fields of Educational Technology and Library and Information Science. Further, findings confirm that personality characteristics as well as motivation affect ICT use. If instructors would like to enhance students’ ICT use, they should be aware of individual differences between students, and they should present to students the advantages and usefulness of ICT, thus increasing their motivation to use ICT, in the hopes that they will become innovators or early adopters.

This study attempts to present the variety of possible uses for iPads, in the learning process. The objective is to evaluate a unique implementation model that was tried out at a teacher training college in Israel. The methodology is based on a qualitative research paradigm. The findings show that students’ use the iPads in various contexts: (a) for ongoing personal use; (b) for planning lessons; (c) for active integration in the classroom; and (d) for reading and developing content and games. These findings are summarized in a chart that shows the different uses as levels in a hierarchical taxonomy. Analysis of the iPad’s pedagogical uses may shed light on the various skills students need to acquire in order to become teachers in 21st century. In addition, understanding the various iPad uses and their frequency can affect decision-making at the level of policy in the field of implementation of the use of mobile technologies in educational institutions.

CAPTCHA is one of the most common solutions to check if the user trying to enter a Website is a real person or an automated piece of software. This challenge-response test, implemented in many Internet Websites, emphasizes the gaps between accessibility and security on the Internet, as it poses an obstacle for the learning-impaired in the reading and comprehension of what is presented in the test. Various types of CAPTCHA tests have been developed in order to address accessibility and security issues. The objective of this study is to investigate how the differences between various CAPTCHA tests affect user experience among populations with and without learning disabilities. A questionnaire accompanied by experiencing five different tests was administered to 212 users, 60 of them with learning disabilities. Response rates for each test and levels of success were collected automatically. Findings suggest that users with learning disabilities have more difficulties in solving the tests, especially those with distorted texts, have more negative attitudes towards the CAPTCHA tests, but the response time has no statistical difference from users without learning disabilities. These insights can help to develop and implement solutions suitable for many users and especially for population with learning disabilities.