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

Aim/Purpose: This study was designed to examine the effectiveness of mentor’s work with immigrant children and adolescents at risk, using the Elements Way. Background: The New Media offers our “screen kids” a lot of information, many behavioral models, and a new type of social communication. The Elements Way is an educational method designed to enhance openness, development, breakthroughs, goal achievement, and transformation in the age of media and social networks. Methodology: The Elements Way was developed following research on communication in the diversified media, especially new media such as Facebook, WhatsApp, and television reality shows, and the study is an examination of the effectiveness of mentors’ work with immigrant children and adolescents at risk, using the Elements Way. All mentors had been trained in the Elements Way. The study population included 640 mentors working with immigrants’ children in Israel. The work was conducted in 2010-2013. The mixed-methods approach was selected to validate findings. Contribution: Empowering children and enhancing their ability to cope; Creating openness and sharing, making children more attentive to the significant adults in their lives; Supporting children who face the complex reality that characterizes our age. Findings: Significant differences were found in the mentors’ conduct with the children. Work programs were designed and implemented with care and consistency, and mentors succeeded in generating change within the children and achieving desired goals. Of the 640 participating mentors, 62 were not able to promote the child, and interviews with them revealed that their work with the children was not consistent with the Elements Way and began from a different vantage point. Recommendations for Practitioners: Success factors: Self-awareness and awareness of one’s surroundings. Empathy. Willingness to engage in significant interactions. Self-cleansing and self-reflection. Ability to engage in a personal and interpersonal dialogue. Ability to accept and contain the child. Cooperation with the child in creating a work program and assisting the child to achieve the goals that were set in the program. Recommendation for Researchers: Future studies should focus on analyzing the discussions of children and adolescents, to add depth to our insights regarding children and adolescents’ perception of the mentors’ work from their perspective. Impact on Society: Finding the “keys” to openness, development, goal achievement, and transformation in our work with “screen kids.” Future Research: Studies that are designed to examine the effectiveness of mentor’s work with immigrant children and adolescents at risk, using the Elements Way.

Aim/Purpose: To monitor Sustainability Development Goals (SDG) established by the United Nations through the hierarchical architecture of informing systems Background: The paper discusses the case of Poland and its Gdansk region Contribution: The solution combines the big-picture of civilization with small-picture of a nation, regions, cities, and firms Findings: The presented solution can be implemented if the political will can be secured. Recommendations for Practitioners: Take the main idea of this paper and adapt to your local case. Recommendation for Researchers: Develop some prototypes of presented informing systems and test in your local environment Impact on Society: The success of the sustainability of globalizing society can be secured if the coherent informing systems can be applied to the planning, monitoring, and implementation of the UN's universal SDG. Future Research: Work on the modeling of costs and benefits of the presented solution.

Aim/Purpose: The study describes empirical research into agile Requirements Engineering (RE) practices based on an analysis of data collected in a large higher education organization. Background: Requirements Engineering (RE) in agile development contexts is considerably different than in traditional software development. The field of agile RE is still nascent where there is a need to evaluate its impact in real-world settings. Methodology: Using a case study methodology, the study involved interviewing nine experienced software practitioners who reflected on the use and implementation of various agile RE practices in two software development projects of a student management system. Contribution: The primary contribution of the paper is the evaluation of agile RE practices in a large tertiary educational organization. Based on the analysis of the data, it provides valuable insights into the practice of agile RE in a specific context (i.e., education), but just as importantly, the ones that were omitted or replaced with others and why. Findings: While the evolutionary and iterative approach to defining requirements was followed in general, not all agile practices could be fully adhered to in the case organization. Although face-to-face communication with the customers has been recognized as one the most important agile RE practices, it was one of the most difficult practices to achieve with a large and diverse customer base. Addressing people issues (e.g., resistance to change, thinking, and mindset) was found to be a key driver to following the iterative RE process effectively. Contrary to the value-based approach advocated in the literature, the value-based approach was not strictly adhered to in requirements prioritization. Continuous integration was perceived to be a more beneficial practice than prototyping, as it allows frequent integration of code and facilitates delivering working software when necessary. Recommendations for Practitioners: Our study has important implications for practitioners. Based on our empirical analysis, we provide specific recommendations for effective implementation of agile RE practices. For example, our findings suggest that practitioners could address the challenges associated with limited face-to-face communication challenges by producing flexible, accessible, and electronic documentation to enable communication. Recommendations for Researchers: Researchers can use the identified agile RE practices and their variants to per-form in-depth investigations into agile requirements engineering in other educational contexts. Impact on Society: There are a number of new technologies that offer exciting new opportunities that can be explored to maximize the benefits of agile and other requirements techniques. Future Research: Future research could conduct case studies in different contexts and thus con-tribute to developing bundles or collections of practices to improve software development processes in specific contexts.

Aim/Purpose: The flipped classroom approach is one of the most popular active learning approaches. This paper explores the effectiveness of a new pedagogy, known as FOCUSED, for postgraduate students. Background: The flipped classroom approach is a trendy blended learning pedagogy which capitalizes on the flexibility of online learning and the stimulating nature of face-to-face discussion. This article describes a pilot study involving post-graduate students who experienced the flipped classroom approach in one of their courses. Methodology: In additional to online activities, students adopted a newly learned approach to solve a related problem that was given by another group of students during classes. Quantitative data were collected from pre- and post-tests for both self-learned online materials and group discussion during classes so that the effectiveness of the flipped classroom pedagogy could be examined from the perspective of a holistic learning experience. Findings: It was found that the average scores for the post-test for the self-learned online video were much higher than for pre-test, even though the post-tests for both online and face-to-face learning were higher than the respective pre-tests. The qualitative data collected at the end of the flipped classroom activities further confirmed the value of the flipped classroom approach. Even though students could self-learn, more students valued peer interactions in the classroom more than the flexibility of online learning.

Aim/Purpose: This study examined learning during the COVID-19 crisis, as perceived by preservice teachers at the time of their academic studies and their student teaching experience. Background: The COVID-19 crisis is unexpected. On one hand, it disrupted learning in all learning frameworks, on the other, it may create a change in learning characteristics even after the end of the crisis. This study examined the pro-ductive, challenging, and thwarting factors that preservice teachers encountered during their studies and in the course of their student teaching during the COVID-19 period, from the perspective of preservice teachers. Methodology: The study involved 287 students studying at teacher training institutions in Israel. The preservice teachers were studying online, and in addition experienced online teaching of students in schools, guided by their own teacher. The study used a mixed method. The questionnaire included closed and open questions. The data were collected in 2020. Contribution: Identifying the affecting factors may deepen the understanding of online learning/teaching and assist in the optimal implementation of online learning. Findings: Online learning experience. We found that some of the lessons at institutions of higher learning were delivered in the format of online lectures. Many pre-service teachers had difficulty sitting in front of a computer for many hours—“Zoom fatigue.” Preservice teachers who had difficulty self-regulating and self-mobilizing for study, experienced accumulating loads, which caused them feelings of stress and anxiety. The word count indicated that the words that appeared most often were “load” and “stress.” Some preservice teachers wrote that collaborating in forums with others made it easier for them. Some suggested diversifying by digital means, incorporating asynchronous units and illustrative films, and easing up on online lectures, as a substitute for face-to-face lectures. Online teaching experience in schools. The preservice teachers' descriptions show that in lessons taught in the format of lectures and communication of content, there were discipline problems and non-learning. According to the preservice teachers, discipline problems stemmed from difficulties concentrating, physical distance, load, and failure to address the students' difficulties. Recommendations for Practitioners: In choosing schools for student teaching, it is recommended to reach an understanding with the school about the online learning policy and organization. It is important to hold synchronous sessions in small groups of 5 to 10 students. The sessions should focus on the mental wellbeing of the students, and on the acquisition of knowledge and skills. Students should be prepared for participation in asynchronous digital lessons, which should be produced by professionals. It should be remembered that the change of medium from face-to-face to online learning also changes the familiar learning environment for all parties and requires modifying the ways of teaching. Recommendations for Researchers: A change in the learning medium also requires a change in the definition of objectives and goals expected of each party—students, teachers, and parents. All parties must learn to view online learning as a method that enables empowerment and the application of 21st century skills. Impact on Society: Teachers' ability to deploy 21st century skills in an online environment de-pends largely on their experience, knowledge, skills, and attitude toward these skills. Future Research: This study examined the issue from the perspective of preservice teachers. It is recommended to examine it also from the perspective of teachers and students.

Aim/Purpose. The aim of this study is to propose a teaching approach based on AI-based chatbot agents and to determine whether the use of this approach increases the students’ motivation. Background. Today, chatbots are an integral part of students’ lives where they are used in various contexts. Therefore, we are interested in incorporating these tools into our teaching process in order to profit from their benefits, assist and guide students while working with to prevent issues such as plagiarism and mainly to boost students’ motivation. Methodology. Using the proposed approach, new chatbot based learning activities were de-signed in three different courses for computer science engineering students. A mixed-method experimental study was conducted to evaluate students’ impression and satisfaction. Survey results of the students (N=58) who participated in the experiment (experimental group) were compared to the results of the students from the control group (N=60). Contribution. Trending AI conversational agents can be engaged in daily teaching activities as a learning assistant and coach to boost students motivation and skills development. Findings. Our study focuses on the impact of chatbots on student’s motivation. The study aimed to analyze the benefits and drawbacks associated with these conversational chatbots. Our findings revealed the significant role that chatbots can play in enhancing student motivation and improving teaching practices.

Aim/Purpose. The study aimed to examine the remote and face-to-face experience of pedagogical training in kindergarten after the third COVID-19 closure in Israel. Background. The outbreak of the COVID-19 epidemic in 2020 changed the training system, and preservice teachers were required to have their practical experience in the kindergartens both remotely and face-to-face. They had to adapt to the new requirements of teacher training programs and receive professional coaching and support from the pedagogical instructor remotely. Methodology. The sample comprised 26 early childhood preservice teachers, who received academic training that includes proficiency in digital technology. The data were collected through feedback that they wrote themselves during the training period and analyzed in the interpretive approach. Contribution. The contribution of the present study is that it examines the pedagogical coaching from the perspective of preservice teachers in a kindergarten during the COVID-19 epidemic, which forced a transition from face-to-face to remote pedagogical training, then back to face-to-face pedagogical instruction. To the best of my knowledge, no such study has been carried out to date, which makes it unique. Findings. The main findings indicate the dissatisfaction of most preservice kindergarten teachers with the remote pedagogical training (about 85%) at the physical, emotional, technological, and pedagogical levels, and the satisfaction of most preservice kindergarten teachers with face-to-face pedagogical training (about 92%) at the physical, emotional, and pedagogical levels. The main conclusion is that technology is a potential barrier in training, and that preservice kindergarten teachers need a pedagogical instructor present at a professional face-to-face meeting. Recommendations for Practitioners. The findings of the study show how important in-person learning and engagement is for everyone especially for Preservice teachers’ and may be helpful for pedagogical coaching teams. Recommendations for Researchers. Preservice teachers’ awareness of the pedagogical coaching experiences could persuade the coaching teams to avoid potential difficulties, increase emotional support, and refine the use of technology to make it a closer substitute for frontal communication. Impact on Society. Face-to-face training based on interpersonal relationship, allows to develop better during the training period.

The purpose of the study is to identify influential factors in the use of collaborative networks within the context of manufacturing. The study aims to investigate factors that influence employees’ learning, and to bridge the gap between theory and praxis in collaborative networks in manufacturing. The study further extends the boundary of a collaborative network beyond enterprises to include suppliers, customers, and external stakeholders. It provides a holistic perspective of collaborative networks within the complexity of the manufacturing environment, based on empirical evidence from a questionnaire survey of 246 respondents from diverse manufacturing industries. Drawing upon the socio-technical systems (STS) theory, the study presents the theoretical context and interpretations through the lens of manufacturing. The results show significant influences of organizational support, promotive interactions, positive interdependence, internal-external learning, perceived effectiveness, and perceived usefulness on the use of collaborative networks among manufacturing employees. The study offers a basis of empirical validity for measuring collaborative networks in organizational learning and knowledge/information sharing in manufacturing.

Efficient knowledge and information management is essential for companies to prosper in the rapidly changing global environment. This article presents challenges of a large Finnish multinational company relating to their current knowledge and information management practices and systems. The focus is on New Product Introduction (NPI) process. The study is based on interviews and facilitated workshops in the Research and Development (R&D) and Production departments. Furthermore, the identified challenges are reflected to the findings presented in knowledge and information management literature. The results gained from the company case study were well in line with the findings in the literature. Three main topics, which can be generalized to cause challenges for knowledge and information management in most companies, were recognized: 1) Issues related to human behavior, individual characteristics and capabilities, different backgrounds, and professional vocabulary; 2) Codifying tacit knowledge into explicit information, which can be saved to company information system; 3) Lack of interoperability between different information systems. The study provides the management of the case company, and other similar organizations, focus points while seeking for better knowledge and information management. From a scientific perspective, the main contribution of this article is to give practical examples of how the theoretical findings presented in literature manifest themselves in real industrial practices.

In order to reduce cost, improve functionality and gain competitive advantages, organizations resort to reengineering projects by developing and making changes to organizational processes. The absence of a unified methodology and appropriate analytic approaches prior to the implementation of reengineering projects has made authorities not to adopt correct decision making approaches in this respect. The objective of this paper is to propose a methodology that has to be adopted prior to the implementation of reengineering projects. The statistical population here consists of 25 expert analysts with MA and PhD degrees who are subject to answering a questionnaire. In this proposed methodology the Multi Criterion Decision Making model is applied to allow the analysts to select appropriate models for better and accurate implementation through the least failure coefficient. The Neyriz White Cement Corporation is selected as the subject and the obtained results are compared with the results obtained from similar implemented projects.

Aim/Purpose: Facebook has made it possible for organisation to embrace social and network centric knowledge processes by creating opportunities to connect, interact, and collaborate with stakeholders. We have witnessed a significant increase in the popularity and use of this tool in many organisations, especially in the private sector. But the utilisation of Facebook in public organisations is at its infancy, with many also believing that the use of Facebook is not a common practice in many public organisations in Nigeria. In spite of this fact, our discernment on the implications of Facebook usage in public organisations in Nigeria, especially organisations at the local level, seem to be remarkably limited. This paper specifically sought to ascertain if Facebook usage influenced inward and outward knowledge sharing in the selected local government councils in Delta State, Nigeria Methodology: The qualitative method was adopted. The study used interview as the primary means of data gathering. The study purposively sampled thirty-six employees as interviewees, twenty from Oshimili South and sixteen from Oshimili North local government councils respectively. The thematic content analysis method was used to analyse interview transcripts. Contribution: This research made distinct contributions to the available literature in social knowledge management, specifically bringing to the fore the intricacies surrounding the use of Facebook for knowledge sharing purposes in the public sector. Findings: The local government councils were yet to appreciate and utilise the interactive and collaborative nature of Facebook in improving stakeholders’ engagement, feedback, and cooperation. Facebook was used for outward knowledge sharing but not for inward knowledge sharing. Recommendations for Practitioners: Local government councils should encourage interaction via Facebook, show willingness to capture knowledge from identifiable sources, and effectively manage critical knowledge assets in order to build trust, cooperation, and confidence in the system. To gain strategic benefits from the use of Facebook for synchronous communication of knowledge, local government councils should ensure that the use of such technology is aligned with strategic plans and that directional change is in line with the new knowledge economy, where interaction and collaboration through technology are seen as strategic imperatives for continued success and sustainability. In addition, local government councils need to train stakeholders on effective use of Facebook for knowledge sharing, with special emphasis on how, why, who, when, and where to use such tool for knowledge sharing activities.

Aim/Purpose: This paper explored the factors (enablers and barriers) that affect Bitcoin adoption in South Africa, a Sub-Saharan country with the high potential for Bitcoin adoption. Background: In recent years, Bitcoin has seen a rapid growth as a virtual cryptocurrency throughout the world. Bitcoin is a protocol which allows value to be exchanged over the internet without a central bank or intermediary. Cryptocurrencies such as Bitcoin are technological tools that arguably can contribute to reducing transactions costs. This paper explored the factors that affect Bitcoin adoption in South Africa, a Sub-Saharan country with the high potential for Bitcoin adoption, as little is known about the factors that affect Bitcoin adoption and the barriers to adoption. Methodology: A quantitative questionnaire was distributed to South African virtual communities where Bitcoin is a topic of interest, and 237 quantitative responses were received, along with 212 open-ended comments. Contribution: This research contributes to the body of knowledge in information systems by providing insights into factors that affect Bitcoin adoption in South Africa. It raises awareness of incentives and barriers to Bitcoin adoption at a time when financial literacy is a crucial issue both in South Africa and worldwide. Findings: The results indicate that perceived benefit, attitude towards Bitcoin, subjective norm, and perceived behavioral control directly affected the participants’ intentions to use Bitcoin. Perceived benefit, usefulness, ease of use, and trust-related risk were found to indirectly affect intention to use Bitcoin. Further, it emerges that the barriers to Bitcoin adoption in South Africa consist of the complex nature of Bitcoin and its high degree of volatility. Recommendations for Practitioners: Bitcoin can contribute to reducing transactions costs, but factors that affect adoption and the barriers to adoption should be taken into consideration. These findings can inform systems and software developers to develop applications that make managing Bitcoin keys and transacting using Bitcoin less complex and more intuitive for end users. Recommendation for Researchers: Bitcoin adoption in South Africa is a topic that has not been previously researched. Researchers could research similarities or differences in the various constructs that were used in this research model. Impact on Society: South African Bitcoin users consider it as a universal currency that makes cross-border payments cheaper. A large number of refugees and workers in South Africa make regular payments across borders. Bitcoin could reduce the costs of these transfers. Future Research: Future research could explore Bitcoin (and other cryptocurrencies) adoption in other developing countries. Researchers could look at factors that influence cryptocurrency adoption in general. The factors affecting adoption of other cryptocurrencies can be compared to the results of this study, and similarities and differences can thus be identified.

Aim/Purpose: The main purpose of this paper is to answer the research question whether the ways in which prosumers share their knowledge with enterprises and public organizations are in line with the ways in which enterprises and public organizations expect them to get engaged in knowledge sharing. Background: Contemporary consumers do not wish to be passive consumers anymore. They want to satisfy their consumption needs by products’ evaluation, co-designing, co-creation and co-reconfiguration. They can do that by sharing their knowledge with enterprises and public organizations. Such consumers are referred as ‘prosumers’. Methodology: The research process consisted of a survey among prosumers and online observations of enterprises and public organizations. A final research sample includes 388 prosumers and 90 organizations. Contribution: This work contributes to existing research on utilizing consumers’ knowledge in business and public organizations by identifying and examining ways of consumers’ knowledge sharing with such organizations. Findings: It was found that there are differences between the ways in which prosumers share knowledge with organizations in comparison with the ways in which enterprises and public organizations expect them to get engaged in knowledge sharing. Prosumers mainly share their knowledge by evaluating products, whereas organizations mainly expect prosumers to get engaged in knowledge sharing by creating and designing products. In addition, it was found that enterprises have bigger expectations as to prosumers’ engagement in knowledge sharing than public organizations. Recommendations for Practitioners: This study provides practitioners with guidelines for prosumers’ knowledge utilization, especially helping them understand which ways prosumers use to share knowledge. Recommendation for Researchers: Researchers may consider the findings of the current study useful to conduct further research on customer knowledge sharing with organizations using our approach and developing own research contexts. Future Research: This study examines Polish prosumers and organizations operating in the Polish market. It is advisable to extend the research to other countries and compare the results.

Aim/Purpose: Despite the fact that the plethora of studies demonstrate the positive impact of information technology (IT) capabilities on SMEs performance, the understanding of underlying mechanisms through which IT capabilities affect the firm performance is not yet clear. This study fills these gaps by explaining the roles of absorptive capacity and corporate entrepreneurship. The study also elaborates the effect of IT capability dimensions (IT integration and IT alignment) upon the SMEs performance outcomes through the mediating sequential process of absorptive capacity and corporate entrepreneurship. Methodology: This study empirically tests a theoretical model based on the Dynamic Capability View (DCV), by using the partial least square (PLS) technique with a sample of 489 manufacturing SMEs in Pakistan. A survey is employed for the data collection by following the cluster sampling approach. Contribution: This research contributes to the literature of IT by bifurcating the IT capability into two dimensions, IT integration and IT alignment, which allows us to distinguish between different sources of IT capabilities. Additionally, our findings shed the light on the dynamic capability view by theoretically and empirically demonstrating how absorptive capacity and corporate entrepreneurship sequentially affect the firms' performance outcomes. At last, this study contributes to the literature of SMEs by measuring the two levels of performance: innovation performance and firm performance. Findings: The results of the analysis show that the absorptive capacity and the corporate entrepreneurship significantly mediate the relationship between both dimensions of IT capability and performance outcomes.

Aim/Purpose: This study investigates the relationship between knowledge sharing process and innovation success with specific emphasis on tacit knowledge. Based on the literature review, we hypothesised that knowledge donating and collecting have a positive relationship with innovation success. Methodology: The hypotheses were empirically tested using the partial least square path modelling with data collected from twelve state-owned public organisations operating in Southern Nigeria. Contribution: The research made distinct empirical contributions to the burgeoning literature on knowledge sharing and innovation from the public sector and developing country context. Findings: Knowledge donating and collecting contribute to innovation success positively and significantly. Knowledge donating effect on innovation success was found to be more significantly positive than the effect of knowledge collecting on innovation success. Recommendations for Practitioners: Public organisations should promote a supportive culture to spur innovation through the frequent share of experiences, information and skills among the various knowledge actors. Public managers should convey the importance of knowledge sharing and its value to knowledge users in clear terms and attend to creating conditions or contexts that encourage people to share knowledge freely and willingly with others. It is apt to improve organisational commitment and support for knowledge sharing activities such as mentorship programs, workshops, conferences, seminars and other related training and development programs in order to provide opportunities for employees to develop innovation competencies from the transfer of tacit knowledge developed over time from experience. To optimise innovation outcomes from knowledge sharing practices, knowledge sharing should be in tandem with the industry or global best practices. Future Research: Future studies should add interviews to provide depth in terms of insights and substance to the questionnaire, and may extend to public organisation with different ownership structure.

Aim/Purpose: This study examines the influence of ambidextrous knowledge sharing in industrial clusters on innovation performance from the perspective of knowledge-based dynamic capabilities. Background: The key factor to improving innovation performance in an enterprise is to share knowledge with other enterprises in the same cluster and use dynamic capabilities to absorb, integrate, and create knowledge. However, the relationships among these concepts remain unclear. Based on the dynamic capability theory, this study empirically reveals how enterprises drive innovation performance through knowledge sharing. Methodology: Survey data from 238 cluster enterprises were used in this study. The sample was collected from industrial clusters in China’s Fujian province that belong to the automobile, optoelectronic, and microwave communications industries. Through structural equation modeling, this study assessed the relationships among ambidextrous knowledge sharing, dynamic capabilities, and innovation performance. Contribution: This study contributes to the burgeoning literature on knowledge management in China, an important emerging economy. It also enriches the exploration of innovation performance in the cluster context and expands research on the dynamic mechanism from a knowledge perspective. Findings: Significant relationships are found between ambidextrous knowledge sharing and innovation performance. First, ambidextrous knowledge sharing positively influences the innovation performance of cluster enterprises. Further, knowledge absorption and knowledge generation capabilities play a mediating role in this relationship, which confirms that dynamic capabilities are a partial mediator in the relationship between ambidextrous knowledge sharing and innovation performance. Recommendations for Practitioners: The results highlight the crucial role of knowledge management in contributing to cluster innovation and management practices. They indicate that cluster enterprises should consider the importance of knowledge sharing and dynamic capabilities for improving innovation performance and establish a multi-agent knowledge sharing platform. Recommendation for Researchers: Researchers could further explore the role of other mediating variables (e.g., organizational agility, industry growth) as well as moderating variables (e.g., environmental uncertainty, learning orientation). Impact on Society: This study provides a reference for enterprises in industrial clusters to use knowledge-based capabilities to enhance their competitive advantage. Future Research: Future research could collect data from various countries and regions to test the research model and conduct a comparative analysis of industrial clusters.

Aim/Purpose: This article proposes a methodology for selecting the initial sets for clustering categorical data. The main idea is to combine all the different values of every single criterion or attribute, to form the first proposal of the so-called multiclusters, obtaining in this way the maximum number of clusters for the whole dataset. The multiclusters thus obtained, are themselves clustered in a second step, according to the desired final number of clusters. Background: Popular cluster methods for categorical data, such as the well-known K-Modes, usually select the initial sets by means of some random process. This fact introduces some randomness in the final results of the algorithms. We explore a different application of the clustering methodology for categorical data that overcomes the instability problems and ultimately provides a greater clustering efficiency. Methodology: For assessing the performance of the proposed algorithm and its comparison with K-Modes, we apply both of them to categorical databases where the response variable is known but not used in the analysis. In our examples, that response variable can be identified to the real clusters or classes to which the observations belong. With every data set, we perform a two-step analysis. In the first step we perform the clustering analysis on data where the response variable (the real clusters) has been omitted, and in the second step we use that omitted information to check the efficiency of the clustering algorithm (by comparing the real clusters to those given by the algorithm). Contribution: Simplicity, efficiency and stability are the main advantages of the multicluster method. Findings: The experimental results attained with real databases show that the multicluster algorithm has greater precision and a better grouping effect than the classical K-modes algorithm. Recommendations for Practitioners: The method can be useful for those researchers working with small and medium size datasets, allowing them to detect the underlying structure of the data in an intuitive and reasonable way. Recommendation for Researchers: The proposed algorithm is slower than K-Modes, since it devotes a lot of time to the calculation of the initial combinations of attributes. The reduction of the computing time is therefore an important research topic. Future Research: We are concerned with the scalability of the algorithm to large and complex data sets, as well as the application to mixed data sets with both quantitative and qualitative attributes.

Aim/Purpose: The clustering techniques are normally considered to determine the significant and meaningful subclasses purposed in datasets. It is an unsupervised type of Machine Learning (ML) where the objective is to form groups from objects based on their similarity and used to determine the implicit relationships between the different features of the data. Cluster Analysis is considered a significant problem area in data exploration when dealing with arbitrary shape problems in different datasets. Clustering on large data sets has the following challenges: (1) clusters with arbitrary shapes; (2) less knowledge discovery process to decide the possible input features; (3) scalability for large data sizes. Density-based clustering has been known as a dominant method for determining the arbitrary-shape clusters. Background: Existing density-based clustering methods commonly cited in the literature have been examined in terms of their behavior with data sets that contain nested clusters of varying density. The existing methods are not enough or ideal for such data sets, because they typically partition the data into clusters that cannot be nested. Methodology: A density-based approach on traditional center-based clustering is introduced that assigns a weight to each cluster. The weights are then utilized in calculating the distances from data vectors to centroids by multiplying the distance by the centroid weight. Contribution: In this paper, we have examined different density-based clustering methods for data sets with nested clusters of varying density. Two such data sets were used to evaluate some of the commonly cited algorithms found in the literature. Nested clusters were found to be challenging for the existing algorithms. In utmost cases, the targeted algorithms either did not detect the largest clusters or simply divided large clusters into non-overlapping regions. But, it may be possible to detect all clusters by doing multiple runs of the algorithm with different inputs and then combining the results. This work considered three challenges of clustering methods. Findings: As a result, a center with a low weight will attract objects from further away than a centroid with higher weight. This allows dense clusters inside larger clusters to be recognized. The methods are tested experimentally using the K-means, DBSCAN, TURN*, and IDCUP algorithms. The experimental results with different data sets showed that IDCUP is more robust and produces better clusters than DBSCAN, TURN*, and K-means. Finally, we compare K-means, DBSCAN, TURN*, and to deal with arbitrary shapes problems at different datasets. IDCUP shows better scalability compared to TURN*. Future Research: As future recommendations of this research, we are concerned with the exploration of further available challenges of the knowledge discovery process in clustering along with complex data sets with more time. A hybrid approach based on density-based and model-based clustering algorithms needs to compare to achieve maximum performance accuracy and avoid the arbitrary shapes related problems including optimization. It is anticipated that the comparable kind of the future suggested process will attain improved performance with analogous precision in identification of clustering shapes.

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: Based on the social exchange theory, this study aimed to explore the underlying mechanisms and boundary conditions between organizational socialization and knowledge sharing. Background: With the advent of the era of the knowledge economy, knowledge has been replacing traditional resources such as capital, labor, and land to become the critical resources of enterprises. The competitiveness of an organization depends much on the effectiveness of its knowledge management; the success of its knowledge management largely relies upon employees’ motivation and willingness to engage in knowledge sharing. Methodology: This study is a longitudinal analysis of data collected from 281 newcomers in Chinese enterprises at two-time points with a one-month interval. Structural equation modeling (SEM) was conducted to test hypotheses by calculating standardized path coefficients and their significance levels. Contribution: The study examined models linking organizational socialization and knowledge sharing that included organizational links and sacrifice as mediators and trust as a moderator. Findings: Results show that the influences of organizational socialization on knowledge sharing change regularly over time. In the role management stage, coworker support and prospects for the future impact the practices of knowledge sharing through links and sacrifice. Moreover, the findings show that trust moderates the effect of links and sacrifice on employees’ knowledge sharing. Recommendations for Practitioners: This study can help enterprises develop targeted human resource management strategies, improve the degree of job embeddedness within the organization, and thus encourage more knowledge sharing among employees. Recommendation for Researchers: First, researchers could pay attention to more underlying mechanisms and boundary conditions in the relationship between organizational socialization and knowledge sharing. Second, focusing on specific cultural context and dimension of concepts may provide a new insight for the future study and help add greater theoretical precision to knowledge sharing. Impact on Society: First, this study suggests that coworker support and prospects for the future improve knowledge sharing within the organization. Second, understanding how job embeddedness (organizational links and organizational sacrifice) acts as a mediator enhancing knowledge sharing, managers should consider raising their attachment relationship to organizations from two aspects: links and sacrifice. Third, knowledge sharing takes place in a team-oriented context, where the success of the team requires high-quality relationships among individual team members within the team as a whole. Future Research: Researchers in the future should employ experimental research design or utilize longitudinal data to ensure that the findings reveal causation. In addition, future research can investigate how the initial level and later changes of organizational socialization are associated with knowledge sharing beyond the observational scope of traditional cross-sectional and lagged research designs.

Aim/Purpose: The need to explore leaders’ role as a mediating factor between knowledge sharing and firms’ competitiveness was the focus of this paper. Further, gaps related to knowledge sharing influence on firms’ competitiveness from an emerging economy perspective was a major driver of this study. Background: The relevance of knowledge sharing is today crucial for firms that seek to harness internal resource innovation towards ensuring increased competitiveness. The link between the actions of leaders and outcomes from sharing knowledge towards increased competitiveness would further advance theory on knowledge sharing and provide managerial implication that is instrumental for an improved organisational outcome. Methodology: The study sample was 282 participants and Partial least square structural equation model was used for the analysis of the data obtained through a questionnaire survey with the aid of SmartPLSv3.9. Contribution: The study contributes to knowledge management literature through advancing leadership as a mediating factor that accounts for the link between knowledge sharing and firms’ competitiveness, most especially from an emerging economy perspective. Findings: Knowledge sharing was found to have a positive effect on firms’ competitiveness. The study found that leadership behaviour mediates the relationship between knowledge sharing and a firm’s competitiveness. Recommendations for Practitioners: The study recommends that, when supported with the right attitude from leaders in the organisation, knowledge sharing will be beneficial towards the firm gaining competitiveness most especially. Future Research: Future studies should be carried out in other sectors aside from the manufacturing sector using the same measures used to measure knowledge sharing. Also, a comparative analysis of knowledge sharing and firms’ competitiveness using leaders’ behaviour as a mediator should be researched in other developing economies.

Aim/Purpose: Acquisitions play a pivotal role in the growth strategy of a firm. Extensive resources and time are dedicated by a firm toward the identification of prospective acquisition candidates. The Indian manufacturing sector is currently experiencing significant growth, organically and inorganically, through acquisitions. The principal aim of this study is to explore models that can predict acquisitions and compare their performance in the Indian manufacturing sector. Background: Mergers and Acquisitions (M&A) have been integral to a firm’s growth strategy. Over the years, academic research has investigated multiple models for predicting acquisitions. In the context of the Indian manufacturing industry, the research is limited to prediction models. This research paper explores three models, namely Logistic Regression, Decision Tree, and Multilayer Perceptron, to predict acquisitions. Methodology: The methodology includes defining the accounting variables to be used in the model which have been selected based on strong theoretical foundations. The Indian manufacturing industry was selected as the focus, specifically, data for firms listed in the Bombay Stock Exchange (BSE) between 2010 and 2022 from the Prowess database. There were multiple techniques, such as data transformation and data scrubbing, that were used to mitigate bias and enhance the data reliability. The dataset was split into 70% training and 30% test data. The performance of the three models was compared using standard metrics. Contribution: The research contributes to the existing body of knowledge in multiple dimensions. First, a prediction model customized to the Indian manufacturing sector has been developed. Second, there are accounting variables identified specific to the Indian manufacturing sector. Third, the paper contributes to prediction modeling in the Indian manufacturing sector where there is limited research. Findings: The study found significant supporting evidence for four of the proposed hypotheses indicating that accounting variables can be used to predict acquisitions. It has been ascertained that statistically significant variables influence acquisition likelihood: Quick Ratio, Equity Turnover, Pretax Margin, and Total Sales. These variables are intrinsically linked with the theories of liquidity, growth-resource mismatch, profitability, and firm size. Furthermore, comparing performance metrics reveals that the Decision Tree model exhibits the highest accuracy rate of 62.3%, specificity rate of 66.4%, and the lowest false positive ratio of 33.6%. In contrast, the Multilayer Perceptron model exhibits the highest precision rate of 61.4% and recall rate of 64.3%. Recommendations for Practitioners: The study findings can help practitioners build custom prediction models for their firms. The model can be developed as a live reference model, which is continually updated based on a firm’s results. In addition, there is an opportunity for industry practitioners to establish a benchmark score that provides a reference for acquisitions. Recommendation for Researchers: Researchers can expand the scope of research by including additional classification modeling techniques. The data quality can be enhanced by cross-validation with other databases. Textual commentary about the target firms, including management and analyst quotes, provides additional insight that can enhance the predictive power of the models. Impact on Society: The research provides insights into leveraging emerging technologies to predict acquisitions. The theoretical basis and modeling attributes provide a foundation that can be further expanded to suit specific industries and firms. Future Research: There are opportunities to expand the scope of research in various dimensions by comparing acquisition prediction models across industries and cross-border and domestic acquisitions. Additionally, it is plausible to explore further research by incorporating non-financial data, such as management commentary, to augment the acquisition prediction model.

Aim/Purpose: The main aim of this study was to investigate the impact of knowledge-based Human Resources Management (HRM) practices on inbound and outbound open innovation in Jordanian small and medium enterprises (SMEs). Background: SMEs in Jordan lack tangible resources. This insufficiency can be remedied by using knowledge as a resource. According to the Knowledge-Based View (KBV) theory, which posits knowledge as the most valuable resource, SMEs can achieve open innovation by implementing knowledge-based HRM practices that enhance the utilization of knowledge and yield competitiveness. Methodology: This study adopted the quantitative method employing descriptive and exploratory approaches. A total of 500 Jordanian manufacturing SMEs were selected from 2,310 manufacturing SMEs registered lists, according to the Jordan Social Security, by using random sampling. The study’s instrument was a questionnaire that was applied to these SMEs. There were 335 responses that were deemed useful for analysis after filtering out the replies with missing values; this corresponded to a response rate of 67%. The paper utilized structural equation modeling and cross-sectional design to test hypotheses in the proposed research model. Contribution: This study advocates the assumption of the role of KBV in improving innovation practices. This study contributes to the existing strategic HRM research by extending the understanding of knowledge-based HRM practices in the context of SMEs. Thus, this study contributes to the understanding of innovation management by demonstrating the role of knowledge-based HRM practices in boosting inbound and outbound OI practices, thereby enhancing innovation as an essential component of firm competitiveness. Findings: The findings revealed the positive impact of four knowledge-based HRM practices on inbound and outbound open innovation in Jordanian manufacturing SMEs. These practices were knowledge-based recruitment and selection, knowledge-based training and development, knowledge-based compensation and reward, as well as knowledge-based performance assessment. Recommendations for Practitioners: This study is expected to help the stakeholders of SMEs to re-shape the traditional HRM practices into knowledge-based practices which improve managerial skills, innovation practices, and the level of the firm’s competitiveness. Recommendation for Researchers: This study serves as a significant contribution to the research field of innovation practices by building a new association between knowledge-based HRM practices and inbound and outbound open innovation. Impact on Society: The study emphasizes the vital role of knowledge-based HRM practices in enhancing the knowledge and social skills of the human capital in SMEs in Jordan, thus improving the country’s social and economic development. Future Research: Future research could build on this study to include service SMEs. It could also employ a longitudinal study over the long run which would allow for a deeper analysis of the relationships of causality, offering a more comprehensive view of the effect of knowledge-based HRM on open innovation. Furthermore, future research could examine the sample of investigation before and after implementing the knowledge-based HRM practices to provide stronger evidence of their influence on inbound and outbound innovation.

Aim/Purpose: This study aims to devise a personalized solution for online healthcare platforms that can alleviate problems arising from information overload and data sparsity by providing personalized healthcare services to patients. The primary focus of this paper is to develop an effective medicine recommendation approach for recommending suitable medications to patients based on their specific medical conditions. Background: With a growing number of people becoming more conscious about their health, there has been a notable increase in the use of online healthcare platforms and e-services as a means of diagnosis. As the internet continues to evolve, these platforms and e-services are expected to play an even more significant role in the future of healthcare. For instance, WebMD and similar platforms offer valuable tools and information to help manage patients’ health, such as searching for medicines based on their medical conditions. Nonetheless, patients often find it arduous and time-consuming to sort through all the available medications to find the ones that match their specific medical conditions. To address this problem, personalized recommender systems have emerged as a practical solution for mitigating the burden of information overload and data sparsity-related issues that are frequently encountered on online healthcare platforms. Methodology: The study utilized a dataset of MC ratings obtained from WebMD, a popular healthcare website. Patients on this website can rate medications based on three criteria, including medication effectiveness, ease of use, and satisfaction, using a scale of 1 to 5. The WebMD MC rating dataset used in this study contains a total of 32,054 ratings provided by 2,136 patients for 845 different medicines. The proposed HSMCCF approach consists of two primary modules: a semantic filtering module and a multi-criteria filtering module. The semantic filtering module is designed to address the issues of data sparsity and new item problems by utilizing a medicine taxonomy that sorts medicines according to medical conditions and makes use of semantic relationships between them. This module identifies the medicines that are most likely to be relevant to patients based on their current medical conditions. The multi-criteria filtering module, on the other hand, enhances the approach’s ability to capture the complexity of patient preferences by considering multiple criteria and preferences through a unique similarity metric that incorporates both distance and structural similarities. This module ensures that patients receive more accurate and personalized medication recommendations. Moreover, a medicine reputation score is employed to ensure that the approach remains effective even when dealing with limited ratings or new items. Overall, the combination of these modules makes the proposed approach more robust and effective in providing personalized medicine recommendations for patients. Contribution: This study addresses the medicine recommendation problem by proposing a novel approach called Hybrid Semantic-based Multi-Criteria Collaborative Filtering (HSMCCF). This approach effectively recommends medications for patients based on their medical conditions and is specifically designed to overcome issues related to data sparsity and new item recommendations that are commonly encountered on online healthcare platforms. The proposed approach addresses data sparsity and new item issues by incorporating a semantic filtering module and a multi-criteria filtering module. The semantic filtering module sorts medicines based on medical conditions and uses semantic relationships to identify relevant ones. The multi-criteria filtering module accurately captures patient preferences and provides precise recommendations using a novel similarity metric. Additionally, a medicine reputation score is also employed to further expand potential neighbors, improving predictive accuracy and coverage, particularly in sparse datasets or new items with few ratings. With the HSMCCF approach, patients can receive more personalized recommendations that are tailored to their unique medical needs and conditions. By leveraging a combination of semantic-based and multi-criteria filtering techniques, the proposed approach can effectively address the challenges associated with medicine recommendations on online healthcare platforms. Findings: The proposed HSMCCF approach demonstrated superior effectiveness compared to benchmark recommendation methods in multi-criteria rating datasets in terms of enhancing both prediction accuracy and coverage while effectively addressing data sparsity and new item challenges. Recommendations for Practitioners: By applying the proposed medicine recommendation approach, practitioners can develop a medicine recommendation system that can be integrated into online healthcare platforms. Patients can then utilize this system to make better-informed decisions regarding the medications that are most suitable for their specific medical conditions. This personalized approach to medication recommendations can ultimately lead to improved patient satisfaction. Recommendation for Researchers: Integrating patient medicine reviews is a promising way for researchers to elevate the proposed medicine recommendation approach. By leveraging patient reviews, the approach can gain a more comprehensive understanding of how certain medications perform for specific medical conditions. Additionally, exploring the relationship between MC-based ratings using an improved aggregation function can potentially enhance the accuracy of medication predictions. This involves analyzing the relationship between different criteria, such as medication effectiveness, ease of use, and satisfaction of the patients, and determining the optimal weighting for each criterion based on patient feedback. A more holistic approach that incorporates patient reviews and an improved aggregation function can enable the proposed medicine recommendation approach to provide more personalized and accurate recommendations to patients. Impact on Society: To mitigate the risk of infection during the COVID-19 pandemic, the promotion of online healthcare services was actively encouraged. This allowed patients to continue accessing care and receiving treatment while adhering to physical distancing guidelines and shielding measures where necessary. As a result, the implementation of personalized healthcare services for patients is expected to be a major disruptive force in healthcare in the coming years. This study proposes a personalized medicine recommendation approach that can effectively address this issue and aid patients in making informed decisions about the medications that are most suitable for their specific medical conditions. Future Research: One way that may enhance the proposed medicine recommendation approach is to incorporate patient medicine reviews. Furthermore, the analysis of MC-based ratings using an improved aggregation function can also potentially enhance the accuracy of medication predictions.