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The importance of organizational resilience as an effective means to cope with crises and achieve sustainable growth in crisis situations is gradually gaining attention from both theoretical and practical circles. Based on the review of existing research on organizational resilience, this study uses the scientific knowledge mapping method from the macro perspective and the literature analysis method from the micro level to review the development of organizational resilience research during 1984-2021, and analyzes 108 representative papers on organizational resilience. Finally, this study proposes future research directions based on the existing studies, such as enriching the influence factors of organizational resilience, strengthening the study of the mechanism of organizational resilience and strengthening the study of the effect of organizational resilience. This paper not only provides a reference for domestic scholars to construct an overall framework for organizational resilience research, but also provides theoretical and practical guidelines for enterprises to achieve rebound survival and then sustainable growth in the face of adversity.

Since its launch, open innovation has been one of the hottest research topics in the field of innovation management. However, most of the current literature focuses on open innovation participants, severing the link between actors engaging in open innovation activities and social third-party firms, i.e., lacks discussions of the social attributes of open innovation. Therefore, via the perspective of the evolution of open innovation participants, this paper reviews current research from the aspects of unilateral subjects, bilateral subjects, and third-party subjects. Integrating the perspective with a sociological view, this paper theoretically constructs a framework for the open innovation information spillover effect. Moreover, taking Huawei Technologies Co., Ltd., as an example, this paper verifies the practical existence of the information spillover effect among firms’ open innovation activities. This paper aims to extend the research boundary of open innovation, thereby providing a theoretical reference for further studies.

The developments in information and communications technologies (ICT) come with changes in all the fields of life, including the education system. At the same time, the IoT (Internet of Things) is turning ever more important as regards the overall benefits that it brings to smart cities as well as the education system. Starting March 2020, the COVID-19 pandemic has caused fast-paced changes in education and forced the ICT integration in higher education. Despite that, the IoT is still at the beginning in the education system and the impact of its adoption is far from being fully understood. This article is aimed at describing a smart education environment and the extent to which the IOT is conducive to this desideratum. The paper also identifies and describes the most important benefits and challenges related to the adoption of the IoT in higher education. In order to analyze the impact of the IoT adoption in the education environment, the authors propose an assessment model based on six hypotheses, including their definitions and descriptions. They are validated against the Romanian higher education system, as well as a set of survey data. Structural equation modelling (SEM) is used in the study to validate the suggested model as well as to determine how the adoption of the IoT relates to intra- and extra-university connectivity, to attracting additional resources, to the teaching and learning activities, to data security and integrity as well as to education policies. The last part of the paper dwells on the analysis of a set of survey data and of the hypotheses shaped herein. The paper also includes recommendations, as well as the main conclusions, limitations and future research directions. It contributes both from the theoretical and practical perspective to the development of smart universities in the future.

This paper explains the need for sustainable information-based management technologies for the online community-based ecosystem, its analogies, architecture design, and delivery. Subsequently, this paper describes the benefits of the proposed ecosystem compared to the currently available platforms. Additionally, this article investigates the problems in the systems of two higher learning institutions. Now, the systems used in higher education institutions are disintegrated. The proposed ecosystem objective is to bridge data redundancy and duplication gaps among higher learning institutions. The research methodologies used are document analysis, participant observation and in- depth interviews. This document creates a learning community culture among the five distinguished members: 1) Lecturers, 2) students, 3) administrators, 4) public, and 5) potential employers. Online Community-based Ecosystem (OnCE) is a system created specifically for the learning community culture. The result of the gathered data shows that the OnCE system can impact students’ learning proficiency and positively influence their learning culture. The implication of this research shows that the online community-based ecosystem is essential to support learning and ensure improved facilities, knowledge, and skills, thus preparing graduates before entering the job market, even though courses are taught remotely using educational technology.

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice.

Nowadays, gamification is used to improve the enterprises' relationship with customers and employees. Employee engagement as one of the significant achievements of gamification is a major factor for increasing organizational productivity. In this paper we try to theorize the role of gamification in the enterprises from the employee perspective. The main objective of this research is to identify the major role of gamification as a new facilitating technology and organizational capability through examining the nomological network of influences. We highlight the strong interactions among three organizational capabilities in the form of mechanic options, dynamics, and positive emotions and their mediating role between gamification competence and enterprise's performance. Using a mixed method through expert interviews and questionnaires, we determined the proposed model and localized it to a 1,000-member banking organization. The proposed conceptual model shows that from a gamification standpoint, what factors and how they can cause and increase the employee engagement and thereby improve the organizational performance and capabilities. Using a mixed method, we have shown that there is a statistically significant improvement with positive emotion and that a good feeling of employees toward the system will have a positive impact on their preference for their work. This paper forwards an important debate on the conceptualizing the role of gamification in contemporary enterprises performance by applying gamified approaches, which contributes to literature on internal and enterprise gamification.

The continuous development of the IOT technology is rapidly penetrating into all walks of life, which promotes the mobile Internet into a new service system, and mobile teaching methods with the characteristics of flexibility and interactivity are also becoming popular. This kind of learning mode enables students to get rid of the limitation of time and space, and can carry out targeted learning, so that different types of students can reasonably arrange their learning objectives according to their own learning quality. For students majoring in economic management, more and more enterprises require them to have practical ability and cooperation ability. Therefore, it is necessary to focus on cultivating students’ cooperation ability and theoretical practice ability in education and teaching. The traditional teaching mode does not meet the needs of the times. It is necessary to study the economic management teaching mode in the new era of Internet of things to promote the reform of education industry. Therefore, it is of great significance to study the economic management teaching mode based on mobile learning and collaborative learning. This paper first introduces the principle and technical support of the IOT, analyzes the reform of economic management teaching mode under the environment of the IOT and the experimental teaching process using the IOT technology and virtual technology. This paper analyzes the current situation of experimental education and the characteristics of the teaching mode based on mobile learning and collaborative learning through the method of literature research, and uses the method of questionnaire survey to investigate the students in the experimental teaching center of economic management in Colleges and universities. The survey results show that in the IOT environment, the experimental teaching mode based on mobile learning and collaborative learning can effectively mobilize students’ learning enthusiasm, and can improve students’ theoretical and practical ability, cooperative ability and autonomous learning ability to a certain extent.

The emergence of e-commerce has rejuvenated backward and poor remote villages. This paper presents a revelatory case study of three remote villages in China to depict how information and communication technology (ICT, specifically e-commerce) can empower remote areas to thrive. With the concept of affordance as basis, this work identifies critical actors in the development of rural e-commerce (i.e., Taobao Village) and illustrates how they use ICT. Eight deterministic affordances of the same ICT used in the evolution of rural e-commerce are specified, and three evolution paths about how ICT empowers the formation and development of rural e-commerce are depicted. This paper also describes the challenges of the current development of rural e-commerce. The findings of the study are discussed, and suggestions on how to capitalize on ICT for rural e-commerce development are offered.

The Requirements elicitation involves knowledge intensive and collaborative activities. Requirements engineering research has proposed a range of knowledge elicitation and requirements gathering techniques, few of which apply specific strategies for eliciting tacit knowledge from stakeholders. The difficulty of taking the deliberate advantage of important tacit knowledge of stakeholders is one of the eminent problems in requirements elicitation. This paper proposes a model to define and elicit the tacit knowledge that has been generated during the requirements elicitation process. The model is based on adopting and extending the rationale model for requirements rationale knowledge elicitation in the requirements elicitation process context. Moreover, this paper presents a representation code to express the tacit knowledge in this context. Finally, to evaluate the feasibility of the model, a survey instrument was applied on domain experts to gather their opinion regarding the ability of the proposed model in facilitating tacit knowledge elicitation. In addition, controlled experiment used to evaluate the proposed model. To explore the model, a post-questionnaire was used to identify participants' feedback. The findings of the evaluation methodologies that were used showed that the proposed model can facilitate tacit knowledge elicitation in the requirements elicitation context. Also, the proposed model has a significant effect on improving the requirements elicitation.

Higher education institutions (HEI) have realized the advantages of implementing a blended learning environment by using learning management systems (LMSs) to provide effective ways of learning and teaching. However, recent literature has revealed that developing countries' educational institutions fail when they adopt LMS technologies because they ignore the human factors related to these technologies. This study investigated the impact of human factors on the effectiveness of LMS in a blended learning environment at Kuwait's HEIs (KHEIs). In this paper, a pragmatic approach consisting of quantitative and qualitative methods is used. User characteristics traits from the literature review were organized into three main indicators of human impact on the effectiveness of LMS: technological characteristics, psychological characteristics, and student-instructor interaction characteristics. After these indicators were identified, a conceptual model was developed to study the characteristics. A deductive approach was used, and the model was tested for significance through receiving feedback from the universities' students and faculty members. In addition, an inductive approach was implemented through conducting interviews to explore more factors related to the effectiveness of LMS. The inductive approach's results revealed the relevant factors for the usage of the LMS, such as training, needs, expectations, and branding. The human factors that positively affect the success and effectiveness of LMS included attitude, enjoyment, experience, self-efficacy, and promptness, which had the most substantial impacts on user satisfaction. The modified conceptual model that this paper presents includes these impacting factors and provides an acceptable fit to the data. This research has developed an updated framework for demonstrating the effectiveness of LMS as it pertains to human factors, and its findings can be used to enhance user experience in a blended learning environment, thus improving the quality of Kuwaiti education.

Blockchain is a novel technology capturing the attention of Central Banks and a technology with significant disruptive potential. However, a gap in research effort between practitioners and academics seems to have emerged. This paper analyses and maps that gap by exploring trends in peer-reviewed research contributions through thematic categorisation of academic literature on Distributed Ledger Technology (DLT) use-cases for services, operations and functions performed by central banks. Furthermore, this paper provides summaries of opportunities and challenges for central banks arising from blockchain adaptation to each of those use-cases. To achieve this goal, we utilise a Systematic Mapping Study approach. The paper presents an in-depth assessment of statistical and thematic analysis of research maturity and the types of researchers, with specific emphasis on types of central bank use-cases considered for blockchain adaptation. Our work contributes to an understanding of where the most or least attention is directed, allowing for identification of gaps and opportunities for both academics, practitioners and combinations of each. Results show that the research topic is a comparatively new domain. It confirms the gap between depth and volume of the research provision from industry and academia, with industry leading the trend. Our study also found that the most research-intensive use-cases are those for: 1) Central Bank issued Digital Currency (CBDC), 2) Regulatory Compliance and 3) Payment Clearing and Settlement Systems (PCS) operated by central banks; a comparatively low engagement was found in the areas of 4) Assets Transfer/Ownership and 5) Audit Trail. Engineering and Physical Sciences Research Council, UK

Social Media (SM) platforms, particularly Twitter, have become useful tools for startup companies (henceforth startups) which use the latter to support most of their business activities. As a result, there is a need to gauge the performance of specific business initiatives vis-à-vis public sentiment, or more specifically the spread of such initiatives based on Twitter user-generated content. Previous research which makes use of Twitter analysis to analyze the business activities of startups is minimal, especially for Twitter user content in the Arabic language. Consequently, this paper proposes an analytics-based framework called Startup Initiatives Response Analysis (SIRA) designed to assess the performance of initiatives launched by startups via text classification, sentiment analysis, and statistical analysis techniques. To provide empirical evidence for the viability of the proposed research framework, this paper examined the case of an Arab transportation network startup, carrying out a SIRA analysis of an initiative undertaken by Careem to empower women by encouraging them to work for the company. The results confirm the effectiveness of the proposed framework for statistically measuring the initiative spread and the public feedback based on the user-generated content on the Twitter social platform.

In this paper we present an ontological approach to build a knowledge-base on climate change related facts. Our knowledge space, developed in Ontology Web Language (OWL), enables knowledge within the Semantic Web. It allows a dynamic classification and a semantic characterization of the different events that can be related to each other, as well as to external sources of information. The resulting ontology is structured as a timeline which aims to describe the climate change story from multiple perspectives, including scientific, social, political and technological ones. We have created an instance of the ontology as an attempt to tell the climate change story so far. Such a population is based on the collection of factual information and critical literature review, with a focus on relevant theories, happenings, social and political initiatives. In this paper we present an ontological approach to build a knowledge-base on climate change related facts. Our knowledge space, developed in Ontology Web Language (OWL), enables knowledge within the Semantic Web. It allows a dynamic classification and a semantic characterization of the different events that can be related to each other, as well as to external sources of information. The resulting ontology is structured as a timeline which aims to describe the climate change story from multiple perspectives, including scientific, social, political and technological ones. We have created an instance of the ontology as an attempt to tell the climate change story so far. Such a population is based on the collection of factual information and critical literature review, with a focus on relevant theories, happenings, social and political initiatives.

In the last few years, most of the public universities in the Kingdom of Saudi Arabia (KSA) have adopted electronic learning (e-learning) as an evolutionary educational platform both by choice and by demand. Despite its many advantages, it has increased the ethical and moral challenges faced in the form of the violations of academic integrity that exist in traditional education. Universities all over the world are struggling to overcome these issues. Keeping this in mind, the purpose of this paper is to investigate and priorities the factors of violating academic integrity within Saudi Arabian universities. Based on the previously published literature and using Delphi - based discussions with e-Learning experts, this paper has identified twelve major factors which were related to e-Learning environment, Awareness on Academic Integrity, and e-Learning guiding principles. Analytic Hierarchy Process (AHP) was used to prioritize these factors. It was concluded that inappropriate guidelines provided to students was the most contributing factor while Shortage of feedbacks was least contributing factor among all the identified factors.

There has been a rapid growth in the Internet of Things (IoT) enabled smart-homes recently. Although these IoT powered smart-homes offer new opportunities, their household penetration is quite low. The main objective of this paper is to develop a better understanding of the reasons underlying the end-user resistance to the adoption of the IoT enabled smart-homes, with elderly people as the target population. Due to a rapid increase in the worldwide elderly population, various forms of information and communication technology (ICT) services are used for their well-being, and hence the target of this paper. A very few research has focused on the end-user experience of using smart-homes with all of them using an acceptance-based approach. Using different negative-perception modeling, we try to identify the main barriers to smart-home usage by the elderly people. Accordingly, an online survey was conducted with 254 elderly people across four Asian countries. Partial least squares structural equation modeling (PLS-SEM) was used to test our theoretical model having ten constructs. Two constructs (perceived-uselessness and self-efficacy) were found to be non-significant, while the remaining proved to be significant (innovativeness, perceived-reliability, perceived-interoperability, service-cost, privacy-concern, psychological-barrier, home administrative policy, and government-policy). To the best of our knowledge, this is the first research studying the IoT enabled smart-homes using a resistive approach and should provide the groundwork for further research in user-experience studies with IoT technology.

This paper aims to explore and investigate the potential factors influencing students' behavioral intentions to use the e-learning system. This paper proposes an extended technology acceptance model (TAM) that has been tested and examined through the use of both innovation diffusion theory (IDT) and integrating TAM. This paper was conducted on 1286 students utilizing systems of e-learning in Malaysia. The findings were obtained via a quantitative research method. The findings illustrate that six perceptions of innovation characteristics, in particular, have impacts on students' e-learning system behavioral intention. The influences of the relative advantages, observability, trialability, perceived compatibility, complexity, and perceived enjoyment on the perceived ease of use is noteworthy. Moreover, the effects of the relative advantages, complexity, trialability, observability, perceived compatibility, and perceived enjoyment on the perceived usefulness have a strong impact. Therefore, the empirical results provide strong backing to the integrative approach between TAM and IDT. The findings suggest an extended model of TAM with IDT for the acceptance of the e-learning system used to improve the students' learning performance, which can help decision makers in higher education, universities, as well as colleges to evaluate, plan and execute the use of e-learning systems.

Institutional repositories (IRs) have received considerable attention from researchers across disciplines and around the globe. They have potentially increased the public value, ranking, prestige, and visibility of researchers, and relevant universities. However, despite the important and rapid growth of research in this area, few efforts have been made to systematically review and integrate the findings from previous research studies or to examine the current state of study regarding IRs. The primary goal of this paper is to provide a better understanding and an in-depth review of the current state of study regarding IRs. This research uses a systematic literature review (SLR) and followed a protocol to properly organize the work related to institutional repositories. The data were collected from primary studies published from 2007 to 2018 from the six major databases (ScienceDirect, IEEE Explorer, Springer, ACM, Taylor and Francis, and Emerald insight). Several papers regarding IRs were reviewed, applying inclusion and exclusion criteria, and a total of 115 studies were included as the main part of this research. The results obtained from these studies indicated that the absence of knowledge of open access IRs among scholars and institutions and inadequate information and communication technology infrastructure were significant challenges behind the development of open access IRs. Meanwhile, enhanced visibility of the academic institution, increased local and global rankings, increased prestige and public value, and improved teaching, learning, and research development by the scholars of the institution were found to be the main benefits of institutional repositories. This paper also highlighted that most of the studies in this research area were focused on the ”deployment, implementation, and adoption” and ”benefits and challenges” of institutional repositories. The outcomes of this paper can assist future researchers by providing a roadmap of institutional repositories and highlighting guidelines for successful implementation of IRs in higher learning institutions.

The increase in the number of open source software (OSS) users have drawn attention to improving usability. Usability is a clear concept that encompassing both task and user characteristics as well as functionality. Usability is an essential factor that affects user acceptance and OSS sustainability, which is considered as the key to the success of the OSS. To some extent, usability is one concern of the larger issue of system acceptability and sustainability. Therefore, usability is an important factor that needs to be considered since the software that is not usable is not going to be sustainable. The objective of this paper is to review researchers' efforts to improve, investigate, and evaluate the usability factor that may affect the OSS acceptability and sustainability and map the research scenery from the articles into a comprehensible structured taxonomy, which would help the researchers to identify different research gaps of this field. A survey of the usability in OSS conducted and 6033 studies identified by a search in four scholarly databases using a query that includes the keywords (usability or learnability or efficiency or satisfaction) and (open source software or OSS). A total of 46 studies are selected. By manually searching in ACM, Springer, and Google Scholar five other studies identified, and thus a total of 51 studies were the final set that includes in this paper. Based on research topics, a taxonomy created and divided into four principal categories which improve OSS usability, analyze OSS usability, evaluate OSS usability, and select and adopt OSS. A comprehensive overview and synthesis of these categories are presented as well. This paper contributes to identifying the possible opportunities and gaps for enabling the participation of interested researchers in this research area. And give possibilities for extending the use of usability research and practices to create more sustainable software. Also, helps in selecting suitable OSS among the alternatives.

The aim of this paper to develop a model to measure sustainability for education and incorporate the literature big data adoption and knowledge management sharing in the educational environment. This paper hypothesizes that perceived usefulness, perceived ease of use, perceived risk, and behavioral intention to use big data should influence adoption of big data, while age diversity, cultural diversity, and motivators should impact knowledge management sharing. Therefore, knowledge management sharing influences behavior intention to use technologies and big data adoption would be positively associated with sustainability for education. This paper employed a version of TAM and motivation theory as the research framework and adopted quantitative data collection and analysis methods by surveying 214 university students who were chosen through stratified random sampling. Student's responses were sorted into the 11 study constructs and analyzed to explain their implication of sustainability on education. The data were then quantitatively analyzed using structural equation modeling (SEM). The results showed that perceived usefulness, perceived ease of use, perceived risk, and behavioral intention to use big data were significant determinants of big data adoption, while age diversity, cultural diversity, and motivators were significant determinants of knowledge management sharing. The knowledge management sharing, behavior intention to use technologies, and big data adoption succeeded in explaining 66.7% of sustainability on education. The findings and implications of this paper are provided.

Even though the implementation of different technological tools is already a trend, there are still aspects that should be refined so that companies' business processes can be improved. This is where social media comes to the foreground. Consequently, the objective of this paper is to study the evolution of research on social media implementation in the field of business process management. A systematic literature review was carried out following a search for and selection of articles that met our objective. To classify the sampled papers, we followed validated frameworks regarding social media management and business process management. Additionally, a detailed look at the sampled case studies was done to highlight companies' experiences in the field. Our final sample comprised 47 papers that simultaneously encompassed social media and business process management. The papers were classified according to their publishing frequency, the article type, both the topics and sectors to which they belonged, their methodological approaches, and the importance for business process management capability areas as well as capability subareas. Finally, word frequency queries were used to better understand diverse social media applications in business processes and to derive practical recommendations. The necessity for a multidisciplinary approach toward business processes was detected; therefore, topics, such as psychology, business economics, or information systems, were included, emphasizing innovation strategies, including gamification, big data, or crowdsourcing. Our most important recommendation concerns the evolution of business process management through different social media tools as a means to achieve a transition toward the recommended omnichannel management approach.

Knowledge is the most important resource in software development. The success of software development relies on knowledge sharing between software developers working across the globe. Global software development has brought many benefits to the software industry; however, at the same, time knowledge sharing across diverse team members is one of the main concerns of global software development organizations. This paper provides a systematic literature review of 42 studies on knowledge sharing barriers and facilitators from 2010 to 2017 and classifies them into five main categories: Individual, Organizational, Technological, Cultural, and Geographical. In order to synthesize and represent the complexity of the knowledge sharing factors in a more manageable and visual manner, this paper proposes concept maps for each category. The identified factors can be strategically used as the guidelines in the global software development organizations to boost the culture of knowledge sharing.

Increased impact of technology leads numerous studies to conduct research on the effect of social media on performance. Very limited of such studies have tried to observe and record the use of social media for collaborative learning as a way to improve collaborative authoring. This paper tries to the validation of the technology acceptance model (TAM) on social media use for collaborative learning to enhance collaborative authoring among research students. To achieve the study objective, this paper employed a questionnaire as the main data collection method and distributed it to 1118 responses of various researchers from the Universiti Teknologi Malaysia (UTM) all of whom use social media. The findings were obtained via a quantitative research method, structural equation modeling (SEM-AMOS). The findings from our empirical study indicate that all the hypotheses were supported; we demonstrate that the use of social media positively and significantly related to collaborative authoring through collaborative learning between researchers in higher education. Therefore, the proposed model will help academic and decision-makers formulate the strategies that can encourage students and researchers to use social media to improving collaborative authoring through collaborative learning.

This paper provides a new way of representing the actors and relationships of a university-type innovation ecosystem based on knowledge. Thanks to this new representation, analysis, and management of knowledge flows are enabled not only qualitatively but also quantitatively, being possible to use well-known tools, such as social network analysis (SNA). Through this contribution, it is possible to analyze both the behavior of the actors individually and the behavior of the ecosystem as a whole in university-type innovation ecosystems, which contributes to adding new knowledge of great relevance for decision-making. Using this new analysis framework, this paper analyzes the dynamism of innovation ecosystems through the assessment of entrepreneurship role, which is tested within the Universidad Politécnica de Madrid (UPM) case. In addition, to show the potential of this new framework, a series of new concepts is introduced, such as connectors and events, which act as activators for the improvement of the structure and dynamism of the innovation ecosystem.

Although electronic records management system (ERMS) is important in bringing about the productivity of organizations, majority of them refuse to implement it, while a few embark on implementing it blindly, without guidance, which often results in failure. This paper, therefore, proposed a model for the ERMS adoption to support the productivity and performance of higher professional education (HPE) institutions in the Yemeni context. This paper used the unified theory of acceptance and use of technology (UTAUT) and a mixed explanatory approach to gather quantitative and qualitative data. Data were then analyzed through the use of SPSS 21, with SEM and Smart PLS V3 software used to test the proposed model. The model was also confirmed by five experts who were interviewed to obtain qualitative data. Based on the analysis results, all the fit indices met the recommended values range that assumed the acceptability of the developed model. The model was found to be of a good fit, and the theory upon which the model was developed was stable. The quantitative findings showed that performance expectancy, effort expectancy, social influence, facilitating conditions, policy, and training have a significant relationship with the ERMS adoption, which in return has a significant relationship with HPE organizations’ productivity. This was supported by the qualitative results, confirming the theoretical study and contributing to the understanding of the ERMS adoption among HPEs. Such adoption ensures educational institutions’ productivity.

Higher education institutions, like nearly all organizations, need to implement information management systems that enable them to handle routine operations easily and, at the same time, generate many types of standardized and ad hoc reports. Higher professional education (HPE) institutions face unique challenges when implementing their computer-based information management systems. Electronic records management systems (ERMSs) help manage the extensive information needed to plan and make well-informed decisions. ERMS is a fairly new addition to organizations, and those organizations are still learning how to use them effectively. Unfortunately, some organizations are still slow to adopt these systems. With this in mind, this paper proposes a framework that identifies the key factors that influence HPEs in adopting their own ERMS. The framework developed in this paper is based on two other models: the unified theory of acceptance and use of technology (UTAUT) and technology–organization–environment (TOE). The questionnaires we distributed to 364 respondents in the HPE sector to collect the views of as many stakeholders as possible. These survey responses led the study to propose a framework that identifies the critical factors that influence the adoption of ERMSs in HPEs. This framework is expected to guide HPE institutions in understanding the most essential factors (individual, technological, and environmental) that must be addressed to adopt an ERMS.

Increasing supply chain performance (SCP) has always been a common phenomenon in the history of organizations. Recent technological advancements [including, radio frequency identification (RFID) in combination with big data predictive analytics (BDPA)] have been able to significantly leverage SCP. In this respect, there is an urgent need for acceptance of RFID technology as well as BDPA to be empirically investigated in order to better understand the enhancement of SCP. Therefore, this paper aims at establishing and empirically investigating the relationship between BDPA acceptance, RFID acceptance, and SCP, respectively. The population of this paper comprises the pharmaceutical logistics industry in China. The sample was obtained from employees through the use of a simple random sampling method. Data were collected through an adapted questionnaire. SmartPLS 3.0 software was used for structural equation modeling analysis. Partial least square-structural equation modeling (PLS–SEM), the value of path coefficient, was found to be 0.700. This showed a direct positive effect of BDPA acceptance on SCP. Moreover, RFID acceptance was also tested through the “variance accounted for” method of mediation. Results showed a partial mediation of 57% between BDPA and SCP. Theoretically, this paper fills the knowledge gap by finding relationships between BDPA and SCP via a mediation role of RFID technology. Practically, it would be beneficial for supply chain managers in the pharmaceutical industry to adopt and implement BDPA and RFID technology so as to enhance SCP.

Software Outsourcing Partnership (SOP) is a type of cooperative client-vendor relationship. SOP is an emerging strategy and is different from ordinary software development outsourcing (SDO). Usually, a fruitful outsourcing association might be converted to an outsourcing partnership. Conversely, SOP is not a risk-free business, numerous barriers associated with SOP. The overarching target of this exploratory paper is to find and analyze a list of barriers that are considered obstacles for vendors in the conversion of their surviving contractual outsourcing relationship to a partnership. Firstly, twenty-six barriers to SOP formation were identified through systematic literature review (SLR) from a sample of 106 papers and then an empirical survey was conducted with fifty experts to analyze the significance and applicability of these barriers in the SOP context. The identified barriers were further analyzed based on five variables such as decades, company size, continents, location of analysis, and perspective of the study. Ten barriers were considered as critical barriers (CBs) via SLR. Industrial experts indicate they extremely agree with five CBs. Eight CBs were equally reported on all continents. We found ten CBs common in all types of organizations. Further, twelve CBs were shared in both decades while ten CBs were found common in both academia and industry. Furthermore, four CBs were specific to clients; five were specific to vendors while ten were common to both. The association of various barriers with SOP formation is found statistically significant for twenty-five barriers with effect size (0.41

The deployment of cryptocurrencies in e-commerce has reached a significant number of transactions and continuous increases in monetary circulation; nevertheless, they face two impediments: a lack of awareness of the technological utility, and a lack of trust among consumers. E-commerce carried out through social networks expands its application to a new paradigm called social commerce. Social commerce uses the content generated within social networks to attract new consumers and influence their behavior. The objective of this paper is to analyze the role played by social media in increasing trust and intention to use cryptocurrencies in making electronic payments. It develops a model that combines constructs from social support theory, social commerce, and the technology acceptance model. This model is evaluated using the partial least square analysis. The obtained results show that social commerce increases the trust and intention to use cryptocurrencies. However, mutual support among participants does not generate sufficient trust to adequately promote the perceived usefulness of cryptocurrencies. This research provides a practical tool for analyzing how collaborative relationships that emerge in social media can influence or enhance the adoption of a new technology in terms of perceived trust and usefulness. Furthermore, it provides a significant contribution to consumer behavior research by applying the social support theory to the adoption of new information technologies. These theoretical and practical contributions are detailed in the final section of the paper. This work was supported in part by the Spanish Research Agency (AEI) and in part by the European Regional Development Fund (FEDER) through project CloudDriver4Industry under Grant TIN2017-89266-R.

This paper surveyed the literature on the criteria of student performance in various educational domains in order to establish the coherent taxonomy and figure out the gap on this pivotal research area. The significant search for articles focused on: 1) student evaluation; 2) education-related; and 3) criteria and domain. The three reliable databases are the Web of Science, ScienceDirect, and IEEE Xplore. These databases are sufficiently broad to cover education and technical literature. The set comprised 178 articles. The biggest group (170/178) included various evaluation criteria and domains. Most domains (84/170) covered criteria, such as performance and skills. Another group (8/178) utilized surveys and reviews to characterize the evaluation criteria for specific specializations. Since 2012, researchers have investigated the process of student evaluation in several domains. Regardless of class, the challenges that prohibited the full adoption of evaluation criteria were the focus of articles and recommended mitigations. Although research areas on student evaluation differed, the results were evenly pivotal. This paper affirms the existing research and provides the supplemental areas for future work.

This paper investigates whether the universities’ communication model and the technology acceptance model, which include four factors, namely, academic performance, student satisfaction, effectiveness, and support assessment, simultaneously enhance student satisfaction and improve the teaching method and academic performance level. This paper aims to adapt a model to improve the assessment method and improve the model of student satisfaction. This paper focuses on improving e-learning to activate the feedback of continued intention of using the model that helps to navigate the student understanding level and academic performance immediately. In this paper, surveys were distributed to (295) undergraduates in four universities in Oman to assess their feedback on e-learning. The partial least squares-structural equation model was used to calculate the measurement of all hypotheses proposed. The results of this paper prove that most of the hypotheses are a positive influence on the continuance of intention to use the proposed model.

The means through which governments deliver services and the way they operate may be considerably enhanced through cloud computing. It can help to address e-government implementation challenges and revolutionize e-government systems in terms of cost savings and the professional use of resources. The aim of this paper is to analyze the importance and performance of the factors that influence the fitness of cloud computing for e-government implementation. This paper integrates the task technology fit model with the diffusion of innovation theory to address this issue. Yemeni public institutions were identified as sources for data collection and 292 information technology employees participated as sample respondents for a structured questionnaire. Security, compatibility, relative advantage, and tasks were the variables found to affect the fitness of cloud computing for e-government activities. However, no impact was seen from the standpoints of trialability and complexity of the technology. In terms of assessing the fitness of cloud computing for e-government services, a greater understanding among policy formulators was sought through the importance-performance matrix analysis (IPMA). The results of IPMA can help identifying areas for strategic focus to assess cloud computing as an alternative technology to implement e-government services.

Mobile learning (m-learning) is increasingly becoming a popular global trend, especially among English language learners. However, despite the growing interest in mobile English language learning, there have been no reviews of research conducted on this subject. This paper represents the first attempt to provide a comprehensive analysis of the existing literature (2010-2015) to identify the taxonomy and distribution of research as well as to identify the advantages and challenges and provide some recommendations to facilitate the effective use of mobile English language learning and its applications. Following a review protocol, articles on mobile English language learning from six major databases (IEEE Xplore, ScienceDirect, Web of Science, ERIC, SpringerLink, and Wiley Online Library) were reviewed. Applying inclusion and exclusion criteria, 133 related articles were identified. The results show that the majority of studies were conducted on application m-learning technologies. Pure mobile applications were the most widely-used applications in the English m-learning context. Meanwhile, concerns regarding quality, usability, integration, financial costs, security and privacy, pedagogical practice, and safety were found to be the main challenges of mobile English language learning. Finally, some recommendations are provided for users, developers/providers, and researchers. The results of this paper can assist users, researchers, policymakers, and practitioners in the education sector to allocate the necessary resources and make plans to mitigate the challenges and facilitate the effective use of mobile English language learning in educational practices.

This paper employs human cognitive process to analyze the cascade phenomena of subjective Web knowledge. First, the cognitive sentiment calculation is summarized in three stages. Second, attributes of users’ background knowledge are mined. Clustering phenomena exist in users’ background knowledge, which means that users are interested in certain kind of topics. Moreover, they tend to review external information about these topics. Third, how users’ background knowledge impacts emotion decision making is analyzed. The impact is illustrated as the induction of objective and objective information. At last, the cascade phenomena of emotion propagation in cyber space are explained with users’ selective emotion expression. Methods are proposed to interrupt cascade phenomena to reduce the negative impacts of cyber space to human beings. This paper mainly focuses on the psychological space and cyber space, which highlights the propagation mechanism of social emotion in cyber space.

In this paper, we consider collaborative power systems education through the FEEDER consortium. To increase students' access to power engineering educational content, the consortium of seven universities was formed. A framework is presented to characterize different collaborative education activities among the universities. Three of these approaches of collaborative educational activities are presented and discussed. These include 1) cross-institutional blended courses (“MS-MD”); 2) cross-institutional distance courses (“SS-MD”); and 3) single-site special experiential courses and concentrated on-site programs available to students across consortium institutions (“MS-SD”). This paper presents the advantages and disadvantages of each approach.

The aim of this study is the computerization of the argument Delphi method. The Delphi method is mainly designed for qualitative prediction within a group of experts, where the experts make predictions and a facilitator controls these predictions until the experts end up with a level of consensus. Argument Delphi, as opposed to the classical Delphi model, is built on the contradictions of the ideas of the experts. Argument Delphi mainly focuses on a discussion topic and asks experts to create new arguments and criticize other arguments from other experts. After a certain level of contradiction, the method yields an amount of contradictory, criticized arguments and builds a decision over these antitheses, as in the Hegelian approach. This is the first time the argument Delphi method has been modeled in a graph of arguments and the problem of qualitative decision has been transferred into a graph problem using Delphi method. This paper is also the first time that argument aggregation and evaluation methods have been proposed. Moreover, the computerized version of argument Delphi is applied to real-world problems using crowd involvement through Facebook. The problem is defined as the prediction of petroleum prices for the end of year and more than 100 contributors from all around the world argued and criticized each other. This paper also discusses the findings of this case study.

In the data-driven world, data is created in huge volume and then analyzed by several organizations to get benefit from them. Smart city is one of the examples to use big data to offer improved services for its resident and tourist. However, some countries face certain obstacles to analyze the big data integration for sustainability in smart city development. Therefore, the purpose of this research paper is to identify and analyze the significant barriers related to sustainable smart city development. To accomplish this objective, fourteen barriers of big data analytics are selected through the combined approach of literature review and expert input. After that, these barriers are evaluated using the best worst method for obtaining deeper insights. The result of this study reveals that the most significant barrier is ‘lack of technologies for BDA’, ‘lack of BDA framework’, ‘nature of big data’, and ‘low availability of analytics platforms for big data’. These barriers need to address on priority to develop a sustainable smart city. This study is helpful to the urban planner, government, and consultancy agencies to decide on the adoption of BDA for sustainable smart city development. Further, they can also optimize their resources in the best possible manner to achieve the sustainable development of the existing smart cities.

The Internet of Medical Things (IoMT) has revolutionized health care services by providing significant benefits in terms of patient well being and relevant costs. Traditional risk assessment methodologies, however, cannot be effectively applied in the IoMT context since IoMT devices form part of a distributed and trustless environment and naturally support functionalities that favor reliability and usability instead of security. In this work we present a survey of risk assessment and mitigation methodologies for IoMT. For conducting the survey, we assess two streams of literature. First, we systematically review and classify the current scientific research in IoMT risk assessment methodologies. Second, we review existing standards/best practices for IoMT security assessment and mitigation in order to i) provide a comparative assessment of these standards/best practices on the basis of predefined criteria (scope and/or coverage, maturity level, and relevant risk methodology applied) and ii) identify common themes for IoMT security controls. Based on the analysis, we provide various IoMT research and implementation gaps along with a road map of fruitful areas for future research. The paper could be of significant value to security assessment researchers and policymakers/stakeholders in the health care industry.