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: The main purpose of this paper is to identify prosumers’ engagement in business process innovation through knowledge sharing. Background: In the increasingly competitive knowledge-based economy, companies must seek innovative methods of doing business, quickly react to consumer demand, and provide superior value to consumers. Simultaneously, contemporary consumers, named “prosumers”, want to be active co-creators of value and satisfy their consumption needs through collaboration with companies for co-creation, co-design, co-production, co-promotion, co-pricing, co-distribution, co-consumption, and co-maintenance. Consequently, consumer involvement in development and improvement of products and business process must be widely analyzed in various contexts. Methodology: The research is a questionnaire survey study of 388 prosumers in Poland and 76 in the UK. Contribution The contribution of this research is twofold. First, it identifies how prosumers can be engaged in business processes through knowledge sharing. Second, it investigates the differences between Poland- and UK-based prosumers in engagement in business process. Findings: The study found that prosumers are engaged in knowledge sharing at each stage of the business process innovation framework. However, there are differences in the types of processes that draw on prosumers’ engagement. Prosumers in Poland are found to engage mostly in the business process of developing and managing products, whereas prosumers in the UK engage mostly in the business process of managing customer services. Recommendations for Practitioners: This study provides practitioners with guidelines for engaging prosumers and their knowledge sharing to improve process innovation. Companies gain new insight from these findings about prosumers’ knowledge sharing for process innovation, which may help them make better decisions about which projects and activities they can engage with prosumers for future knowledge sharing and creating prospective innovations. Recommendations for Researchers: Researchers may use this methodology and do similar analysis with different samples in Poland, the UK, and other countries, for many additional comparisons between different groups and countries. Moreover, a different methodology may be used for identifying prosumers’ engagement and knowledge sharing for processes improvement. Future Research: This study examined prosumers’ engagement from the prosumers’ standpoint. Therefore prosumers’ engagement from the company perspective should be explored in future research.

Aim/Purpose: This study forms part of the World IT Project, which aims to gain a deeper understanding of individual, personal and organisational factors influencing IT staff in a modern, work environment. The project also aims to provide a global view that complements the traditional American/Western view. The purpose of this study is to investigate and report on some of these factors, in particular, the role that job satisfaction has in turnover intention (i.e., changing jobs within the IT industry) and turn-away intention (i.e., moving to another industry other than IT) in South Africa. Background: Several studies have reported on the importance of an employee’s job satisfaction to organisation success, and the various factors that influence it. Most studies on job satisfaction adopted a Westernised and not a global view. Very few empirical studies have been conducted on job satisfaction of IT workers in South Africa. This paper reports on the individual, personal and organisational factors that influence the job satisfaction of IT staff in South Africa. Methodology: The study uses statistical analysis of survey data acquired through the World IT Project. Both online and paper based questionnaires were used. A sample size of 301 respondents was obtained from the survey, which was conducted over a period of 6 months during 2017. The factors that influence IT job satisfaction were analysed using correlation analysis, multiple regression analysis and discriminant analysis. The factors investigated were employee and organisational demographics, aspects of occupational culture, and various job-related individual issues. Contribution: This paper presents the only study focused specifically on turnover and turn-away intention amongst IT staff in South Africa. The final proposed model, grounded in the empirical dataset, clearly shows job satisfaction as a strong mediating construct explaining most of the variance in the IT professional’s intention to leave the organisation (i.e. their turnover intention) and the industry (i.e. their turn-away intention). Findings: The findings revealed that there was a significant correlation between job satisfaction and turnover intention as well as between job satisfaction and turn-away intention of IT staff. Perceived professional self-efficacy, strain and experience were also highly correlated with turnover intention. Professional self-efficacy was also significantly correlated with turn-away intention. Based on the analyses that were conducted, a research model is presented that shows the relationships between the various antecedents of turnover and turn-away intention. Recommendations for Practitioners: Managers in organisations dealing with the shortage of IT skills can use the model to plan interventions to reduce IT staff turnover rates by focussing on addressing the identified individual issues such as strain, job (in)security and work load as well as the personal value and IT occupational culture issues. Recommendation for Researchers: Researchers in the field of IT staff recruitment and management can find value for their research in the proposed refined model of IT job satisfaction and turnover intention. Future research could possibly replicate the study in other countries or could focus on different factors. Impact on Society: IT skills play a crucial role in society today and are therefore in high demand. However, this demand is not being satisfied by the current rate of supply. Research into what factors influence IT staff to leave the organisation or the industry can assist managers with improving their employee relations and job conditions so as to reduce this turnover and increase organisations’ and society’s competitiveness and economic growth. Future Research: It would be interesting to determine if the findings are similar for a sample of smaller organisations and/or younger IT employees since this study focussed on larger organisations and more experienced staff. Future research could also compare the findings of South African organisations with those in other countries.

Aim/Purpose: In this article, we provide a better solution to Webpage access prediction. In particularly, our core proposed approach is to increase accuracy and efficiency by reducing the sequence space with integration of PageRank into CPT+. Background: The problem of predicting the next page on a web site has become significant because of the non-stop growth of Internet in terms of the volume of contents and the mass of users. The webpage prediction is complex because we should consider multiple kinds of information such as the webpage name, the contents of the webpage, the user profile, the time between webpage visits, differences among users, and the time spent on a page or on each part of the page. Therefore, webpage access prediction draws substantial effort of the web mining research community in order to obtain valuable information and improve user experience as well. Methodology: CPT+ is a complex prediction algorithm that dramatically offers more accurate predictions than other state-of-the-art models. The integration of the importance of every particular page on a website (i.e., the PageRank) regarding to its associations with other pages into CPT+ model can improve the performance of the existing model. Contribution: In this paper, we propose an approach to reduce prediction space while improving accuracy through combining CPT+ and PageRank algorithms. Experimental results on several real datasets indicate the space reduced by up to between 15% and 30%. As a result, the run-time is quicker. Furthermore, the prediction accuracy is improved. It is convenient that researchers go on using CPT+ to predict Webpage access. Findings: Our experimental results indicate that PageRank algorithm is a good solution to improve CPT+ prediction. An amount of though approximately 15 % to 30% of redundant data is removed from datasets while improving the accuracy. Recommendations for Practitioners: The result of the article could be used in developing relevant applications such as Webpage and product recommendation systems. Recommendation for Researchers: The paper provides a prediction model that integrates CPT+ and PageRank algorithms to tackle the problem of complexity and accuracy. The model has been experimented against several real datasets in order to show its performance. Impact on Society: Given an improving model to predict Webpage access using in several fields such as e-learning, product recommendation, link prediction, and user behavior prediction, the society can enjoy a better experience and more efficient environment while surfing the Web. Future Research: We intend to further improve the accuracy of webpage access prediction by using the combination of CPT+ and other algorithms.

Aim/Purpose: This research aims to examine the role of Knowledge Management (KM) infrastructure (technological, structural, and cultural) in enhancing job satisfaction in the context of developing countries, as exemplified by Jordan. Background: Despite the presence of job satisfaction studies conducted in educational institutions across the world, knowledge management issues have not been taken into consideration as influencing factors. Methodology: A total of 168 responses to a questionnaire survey were collected from the academic staff at Zarqa University in Jordan. Multiple regression analysis was conducted to test the research hypotheses. Contribution: This study offers deeper understanding about the role that knowledge management infrastructure plays in enhancing job satisfaction from a developing country perspective. The proposed model is tested the first time in Jordan. Findings: Results of the current study revealed that there are significant positive impacts of technological and cultural KM infrastructures on job satisfaction, whereas structural KM infrastructure does not have a significant impact on job satisfaction. Also, the results revealed significant gender difference in perception of the impact of knowledge management infrastructure on job satisfaction. On the other hand, an ANOVA test found no significant difference in the impact of knowledge management infrastructure on job satisfaction among groups by age, experience, and academic rank. Recommendation for Researchers: Our findings can be used as a base of knowledge for further studies about knowledge management infrastructure and job satisfaction following different criteria and research procedures. Future Research: The current model can be applied and assessed further in other sectors, including public universities and other services sectors in developed and developing countries.

Aim/Purpose: This study describes a conceptual model, based on the principles of concept algebra that can provide intelligent academic advice using adaptive, knowledge-based feedback. The proposed model advises students based on their traits and academic history. The system aims to deliver adaptive advice to students using historical data from previous and current students. This data-driven approach utilizes a cognitive knowledge-based (CKB) model to update the weights (values that indicate the strength of relationships between concepts) that exist between student’s performances and recommended courses. Background: A research study conducted at the Public Authority for Applied Education and Training (PAAET), a higher education institution in Kuwait, indicates that students’ have positive perceptions of the e-Advising system. Most students believe that PAAET’s e-Advising system is effective because it allows them to check their academic status, provides a clear vision of their academic timeline, and is a convenient, user-friendly, and attractive online service. Student advising can be a tedious element of academic life but is necessary to fill the gap between student performance and degree requirements. Higher education institutions have prioritized assisting undecided students with career decisions for decades. An important feature of e-Advising systems is personalized feedback, where tailored advice is provided based on students' characteristics and other external parameters. Previous e-Advising systems provide students with advice without taking into consideration their different attributes and goals. Methodology: This research describes a model for an e-Advising system that enables students to select courses recommended based on their personalities and academic performance. Three algorithms are used to provide students with adaptive course selection advice: the knowledge elicitation algorithm that represents students' personalities and academic information, the knowledge bonding algorithm that combines related concepts or ideas within the knowledge base, and the adaptive e-Advising model that recommends relevant courses. The knowledge elicitation algorithm acquires student and academic characteristics from data provided, while the knowledge bonding algorithm fuses the newly acquired features with existing information in the database. The adaptive e-Advising algorithm provides recommended courses to students based on existing cognitive knowledge to overcome the issues associated with traditional knowledge representation methods. Contribution: The design and implementation of an adaptive e-Advising system are challenging because it relies on both academic and student traits. A model that incorporates the conceptual interaction between the various academic and student-specific components is needed to manage these challenges. While other e-Advising systems provide students with general advice, these earlier models are too rudimentary to take student characteristics (e.g., knowledge level, learning style, performance, demographics) into consideration. For the online systems that have replaced face-to-face academic advising to be effective, they need to take into consideration the dynamic nature of contemporary students and academic settings. Findings: The proposed algorithms can accommodate a highly diverse student body by providing information tailored to each student. The academic and student elements are represented as an Object-Attribute-Relationship (OAR) model. Recommendations for Practitioners: The model proposed here provides insight into the potential relationships between students’ characteristics and their academic standing. Furthermore, this novel e-Advising system provides large quantities of data and a platform through which to query students, which should enable developing more effective, knowledge-based approaches to academic advising. Recommendation for Researchers: The proposed model provides researches with a framework to incorporate various academic and student characteristics to determine the optimal advisory factors that affect a student’s performance. Impact on Society: The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advice to students. The proposed approach can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to learning. Future Research: In future studies, the proposed algorithms will be implemented, and the adaptive e-Advising model will be tested on real-world data and then further improved to cater to specific academic settings. The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advisory to students. The approach proposed can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to course recommendation.

Aim/Purpose: This study aimed to examine the effect of marketing knowledge management (MKM) on bank performance via the mediating role of the Fintech innovation in Jordanian commercial banks. Background: An extensive number of studies found a significant relationship between Marketing knowledge management and bank performance (e.g., Akroush & Al-Mohammad, 2010; Hou & Chien 2010; Rezaee & Jafari, 2015; Veismoradi et al., 2013). However, there remains a lack of clarity regarding the relationship between marketing knowledge management (MKM) and bank performance (BP). Furthermore, the linkage between MKM and BP is not straightforward but, instead, includes a more complicated relationship. Therefore, it is argued that managing marketing knowledge management assets and capabilities can enhance performance via the role of financial innovation as a mediating factor on commercial banks; to date, however, there is no empirical evidence. Methodology: Based on a literature review, knowledge-based theory, and financial innovation theory, an integrated conceptual framework has been developed to guide the study. A quantitative approach was used, and the data was collected from 336 managers and employees in all 13 Jordanian commercial banks using online and in hand instruments. Structural equation modeling (SEM) was used to analyze and verify the study variables. Contribution: This article contributes to theory by filling a gap in the literature regarding the role of marketing knowledge management assets and capabilities in commercial banks operating in a developing country like Jordan. It empirically examined and validated the role of Fintech innovation as mediators between marketing knowledge management and bank performance Findings: The main findings revealed that marketing knowledge management had a significant favorable influence on bank performance. Fintech innovation acted as partial mediators in this relationship. Recommendations for Practitioners: Commercial banks should be fully aware of the importance of knowledge management practices to enhance their financial innovation and bank performance. They should also consider promoting a culture of practicing knowledge management processes among their managers and employees by motivating and training to promote innovations. Recommendation for Researchers: The result endorsed Fintech innovation’s mediating effect on the relationship between the independent variable, marketing knowledge management (assets and capabilities), and the dependent variable bank performance, which was not addressed before; thus, it needs further validation. Future Research: The current designed research model can be applied and assessed further in other sectors, including banking and industrial sectors across developed and developing countries. It would also be of interest to introduce other variables in the study model that can act as consequences of MKM capabilities, such as financial and non-financial performance measures

Aim/Purpose: The purpose of this paper is to identify Critical Success Factors (CSFs) for Business Intelligence (BI) implementation projects by studying the existing BI project implementation methodologies and to compare these methodologies based on the identified CSFs. Background: The implementation of BI project has become one of the most important technological and organizational innovations in modern organizations. The BI project implementation methodology provides a framework for demonstrating knowledge, ideas and structural techniques. It is defined as a set of instructions and rules for implementing BI projects. Identifying CSFs of BI implementation project can help the project team to concentrate on solving prior issues and needed resources. Methodology: Firstly, the literature review was conducted to find the existing BI project implementation methodologies. Secondly, the content of the 13 BI project implementation methodologies was analyzed by using thematic analysis method. Thirdly, for examining the validation of the 20 identified CSFs, two questionnaires were distributed among BI experts. The gathered data of the first questionnaire was analyzed by content validity ratio (CVR) and 11 of 20 CSFs were accepted as a result. The gathered data of the second questionnaire was analyzed by fuzzy Delphi method and the results were the same as CVR. Finally, 13 raised BI project implementation methodologies were compared based on the 11 validated CSFs. Contribution: This paper contributes to the current theory and practice by identifying a complete list of CSFs for BI projects implementation; comparison of existing BI project implementation methodologies; determining the completeness degree of existing BI project implementation methodologies and introducing more complete ones; and finding the new CSF “Expert assessment of business readiness for successful implementation of BI project” that was not expressed in previous studies. Findings: The CSFs that should be considered in a BI project implementation include: “Obvious BI strategy and vision”, “Business requirements definition”, “Business readiness assessment”, “BI performance assessment”, “Establishing BI alignment with business goals”, “Management support”, “IT support for BI”, “Creating data resources and source data quality”, “Installation and integration BI programs”, “BI system testing”, and “BI system support and maintenance”. Also, all the 13 BI project implementation methodologies can be divided into four groups based on their completeness degree. Recommendations for Practitioners: The results can be used to plan BI project implementation and help improve the way of BI project implementation in the organizations. It can be used to reduce the failure rate of BI implementation projects. Furthermore, the 11 identified CSFs can give a better understanding of the BI project implementation methodologies. Recommendation for Researchers: The results of this research helped researchers and practitioners in the field of business intelligence to better understand the methodology and approaches available for the implementation and deployment of BI systems and thus use them. Some methodologies are more complete than other studied methodologies. Therefore, organizations that intend to implement BI in their organization can select these methodologies according to their goals. Thus, Findings of the study can lead to reduce the failure rate of implementation projects. Future Research: Future researchers may add other BI project implementation methodologies and repeat this research. Also, they can divide CSFs into three categories including required before BI project implementation, required during BI project implementation and required after BI project implementation. Moreover, researchers can rank the BI project implementation CSFs. As well, Critical Failure Factors (CFFs) need to be explored by studying the failed implementations of BI projects. The identified CSFs probably affect each other. So, studying the relationship between them can be a topic for future research.

Aim/Purpose: Drawing on theories of organizational learning, this study analyzes the mechanism of Internet integration capability affecting knowledge generation by 399 Chinese enterprises. This paper will further explore whether there is a moderating role of learning orientation in the mechanism of Internet integration capability affecting enterprise knowledge generation. Background: The Internet has gradually integrated into the enterprise innovation system and penetrated into all aspects of technological innovation, which has promoted the integration and optimization of resources inside and outside the organization. However, there is limited understanding of how the combination of the Internet and integration capability can drive enterprise knowledge generation. Methodology: The study uses survey data from 399 organizations in China. Through structural equation modeling, this study assesses the relationship between Internet integration capability, organizational learning, knowledge generation, and uses PROCESS macro program to test the mediated moderation effect of learning orientation. Contribution: First, this study provides empirical evidence for managers to better build Internet integration capability and ambidextrous learning to promote enterprise knowledge generation. Second, this study highlights the important moderating role of learning orientation in the mediating role of ambidextrous learning. Findings: First, the study confirms the mediating role of exploratory learning and exploitative learning in knowledge generation driven by Internet integration capability. Second, the results show that when organizations have a strong learning orientation, the indirect path of Internet integration capability influencing knowledge generation through exploratory learning will be enhanced. Recommendations for Practitioners: Enterprises should pay full attention to the improvement of internet integration capability and ambidextrous learning to promote knowledge generation. In addition, enterprises should establish a good learning atmosphere within the organization to strengthen the bridge role of exploratory learning between Internet integration capability and knowledge generation. Recommendation for Researchers: Researchers could collect data from countries with different levels of economic development to verify the universal applicability of the proposed theoretical model. Impact on Society: This study provides references for enterprises using Internet integration capability to promote their knowledge generation capability under the internet background. Future Research: Future research can compare the impact of Internet integration capability on knowledge generation in different industries.

Aim/Purpose: This paper examines the behavior of financial firm employees with regard to information security procedures instituted within their organization. Furthermore, the effect of information security awareness and its importance within a firm is explored. Background: The study focuses on employees’ attitude toward compliance with information security policies (ISP), combined with various norms and personal abilities. Methodology: A self-reported questionnaire was distributed among 202 employees of a large financial Corporation Contribution: As far as we know, this is the first paper to thoroughly explore employees’ awareness of information system procedures, among financial organizations in Israel, and also the first to develop operative recommendations for these organizations aimed at increasing ISP compliance behavior. The main contribution of this study is that it investigates compliance with information security practices among employees of a defined financial corporation operating under rigid regulatory governance, confidentiality and privacy of data, and stringent requirements for compliance with information security procedures. Findings: Our results indicate that employees’ attitudes, normative beliefs and personal capabilities to comply with firm’s ISP, have positive effects on the firm’s ISP compliance. Also, employees’ general awareness of IS, as well as awareness to ISP within the firm, positively affect employees’ ISP compliance. Recommendations for Practitioners: This study can help information security managers identify the motivating factors for employee behavior to maintain information security procedures, properly channel information security resources, and manage appropriate information security behavior. Recommendation for Researchers: Researchers can see that corporate rewards and sanctions have significant effects on employee security behavior, but other motivational factors also reinforce the ISP’s compliance behavior. Distinguishing between types of corporations and organizations is essential to understanding employee compliance with information security procedures. Impact on Society: This study offers another level of understanding of employee behavior with regard to information security in organizations and comprises a significant contribution to the growing knowledge in this area. The research results form an important basis for IS policymakers, culture designers, managers, and those directly responsible for IS in the organization. Future Research: Future work should sample employees from another type of corporation from other fields and should apply qualitative analysis to explore other aspects of behavioral patterns related to the subject matter.

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

Aim/Purpose: This study 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.

Table of Contents for Volume 15, 2020, of the Interdisciplinary Journal of Information, Knowledge, and Management

Aim/Purpose: The purpose of this study is to investigate the mechanism of the front/back-office structure affecting new service development (NSD) performance and examine the role of knowledge transfer in the relationship between front/back-office structure and NSD. Background: The separation of front and back-office has become the prevailing trend of the organizational transformation of modern service enterprises in the digital era. Yet, the influence of front and back-office separation dealing with new service development has not been widely researched. Methodology: Building on the internal social capital perspective, a multivariate regression analysis was conducted to investigate the impact of front/back-office structure on the NSD performance through knowledge transfer as an intermediate variable. The data was collected through a survey questionnaire from 198 project-level officers in the commercial banking industry of China. Contribution: This study advances the understanding of front/back-office structure’s influence mechanism on new service development activity. It reveals that knowledge transfer plays a critical role in bridging the impact of front and back-office separation to NSD performance under the trend of digitalization of service organizations. Findings: This study verified the positive effects of front/back-office social capital on NSD performance. Moreover, knowledge transfer predicted the variation in NSD performance and fully mediated the effect of front/back-office social capital on NSD performance. Recommendations for Practitioners: Service organizations should optimize knowledge transfer by promoting the social capital between front and back-office to overcome the negative effect organizational separation brings to NSD. Service and other organizations could explore developing an internal social network management platform, by which the internal social network could be visualized and dynamically managed. Recommendation for Researchers: The introduction of information and communications technology not only divides the organization into front and back-office, but also reduces the face-to-face customer contact. The impacts of new forms of customer contact to new service development and knowledge transfer between customer and service organizations call for further research. Along with the digital servitization, some manufacturing organizations also separate front and back-offices. The current model can be applied and assessed further in manufacturing and other service sectors. Impact on Society: The conclusion of this study guides us to pay attention to the construction of social capital inside organizations with front/back-office structure and implicates introducing and developing sociotechnical theory in front/back-office issue undergoing technological revolution. Future Research: As this study is based on the retail banking industry, similar studies are called upon in other service sectors to identify differences and draw more general conclusions. In addition, as the front and back-offices are being replaced increasingly by information technology such as artificial intelligence (AI), it is necessary to advance the research on front/back-office research with a new theoretical perspective, such as sociotechnical theory.

Aim/Purpose: This paper reports a case study of organizational transition from a non-competitive selection method to a novel bidding method for the selection of consultants in the Architectural and Engineering (A/E) industry. Background: Public procurement agencies are increasingly relying on external consultants for the design of construction projects. Consultant selection can be based on either competitive bidding, or quality-based criteria, or some combination between these two approaches. Methodology: Different sources of information were reviewed: internal documents, and quantitative data from the enterprise software platform (ERP). In addition, informal and unstructured interviews were conducted with relevant officials. Contribution: As there are mixed opinions in the scientific literature regarding the use of competitive bidding for the selection of consultants in the A/E industry, this paper contributes a detailed review of a transition to a competitive selection method and provides a financial and qualitative comparison between the two methods. In addition, the method implemented is novel, as it delegates most of the responsibility of hiring and managing consultants to one main contractor. Findings: While the new selection method was intended to reduce bureaucratic overload, it has unexpectedly also succeeded to reduce costs as well. Recommendations for Practitioners: It may be more efficient and profitable to adopt the selection method described in this study. Recommendation for Researchers: Similar methods can be applied to other industries successfully. Impact on Society: Our method was applied in a public organization and resulted in a better outcome, both financial and managerial. Adopting this approach can benefit public budgets. Future Research: The selection, data storage, and analysis methods are interrelated components. Future analysis of these components can help better shape the consultant selection process.

Aim/Purpose: The primary purpose of this study is to provide a cost-effective and artificial intelligence enabled security solution for IoT enabled healthcare ecosystem. It helps to implement, improve, and add new attributes to healthcare services. The paper aims to develop a method based on an artificial neural network technique to predict suspicious devices based on bandwidth usage. Background: COVID has made it mandatory to make medical services available online to every remote place. However, services in the healthcare ecosystem require fast, uninterrupted facilities while securing the data flowing through them. The solution in this paper addresses both the security and uninterrupted services issue. This paper proposes a neural network based solution to detect and disable suspicious devices without interrupting critical and life-saving services. Methodology: This paper is an advancement on our previous research, where we performed manual knowledge-based intrusion detection. In this research, all the experiments were executed in the healthcare domain. The mobility pattern of the devices was divided into six parts, and each one is assigned a dedicated slice. The security module regularly monitored all the clients connected to slices, and machine learning was used to detect and disable the problematic or suspicious devices. We have used MATLAB’s neural network to train the dataset and automatically detect and disable suspicious devices. The different network architectures and different training algorithms (Levenberg–Marquardt and Bayesian Framework) in MATLAB software have attempted to achieve more precise values with different properties. Five iterations of training were executed and compared to get the best result of R=99971. We configured the application to handle the four most applicable use cases. We also performed an experimental application simulation for the assessment and validation of predictions. Contribution: This paper provides a security solution for the IoT enabled healthcare system. The architectures discussed suggest an end-to-end solution on the sliced network. Efficient use of artificial neural networks detects and block suspicious devices. Moreover, the solution can be modified, configured and deployed in many other ecosystems like home automation. Findings: This simulation is a subset of the more extensive simulation previously performed on the sliced network to enhance its security. This paper trained the data using a neural network to make the application intelligent and robust. This enhancement helps detect suspicious devices and isolate them before any harm is caused on the network. The solution works both for an intrusion detection and prevention system by detecting and blocking them from using network resources. The result concludes that using multiple hidden layers and a non-linear transfer function, logsig improved the learning and results. Recommendations for Practitioners: Everything from offices, schools, colleges, and e-consultation is currently happening remotely. It has caused extensive pressure on the network where the data flowing through it has increased multifold. Therefore, it becomes our joint responsibility to provide a cost-effective and sustainable security solution for IoT enabled healthcare services. Practitioners can efficiently use this affordable solution compared to the expensive security options available in the commercial market and deploy it over a sliced network. The solution can be implemented by NGOs and federal governments to provide secure and affordable healthcare monitoring services to patients in remote locations. Recommendation for Researchers: Research can take this solution to the next level by integrating artificial intelligence into all the modules. They can augment this solution by making it compatible with the federal government’s data privacy laws. Authentication and encryption modules can be integrated to enhance it further. Impact on Society: COVID has given massive exposure to the healthcare sector since last year. With everything online, data security and privacy is the next most significant concern. This research can be of great support to those working for the security of health care services. This paper provides “Security as a Solution”, which can enhance the security of an otherwise less secure ecosystem. The healthcare use cases discussed in this paper address the most common security issues in the IoT enabled healthcare ecosystem. Future Research: We can enhance this application by including data privacy modules like authentication and authorisation, data encryption and help to abide by the federal privacy laws. In addition, machine learning and artificial intelligence can be extended to other modules of this application. Moreover, this experiment can be easily applicable to many other domains like e-homes, e-offices and many others. For example, e-homes can have devices like kitchen equipment, rooms, dining, cars, bicycles, and smartwatches. Therefore, one can use this application to monitor these devices and detect any suspicious activity.

Aim/Purpose: The aim of this paper is to propose a new information security controls framework for blockchain technology, which is currently absent from the National and International Information Security Standards. Background: Blockchain technology is a secure and relatively new technology of distributed digital ledgers, which is based on inter-linked blocks of transactions, providing great benefits such as decentralization, transparency, immutability, and automation. There is a rapid growth in the adoption of blockchain technology in different solutions and applications and within different industries throughout the world, such as finance, supply chain, digital identity, energy, healthcare, real estate, and the government sector. Methodology: Risk assessment and treatments were performed on five blockchain use cases to determine their associated risks with respect to security controls. Contribution: The significance of the proposed security controls is manifested in complementing the frameworks that were already established by the International and National Information Security Standards in order to keep pace with the emerging blockchain technology and prevent/reduce its associated information security risks. Findings: The analysis results showed that the proposed security controls herein can mitigate relevant information security risks in blockchain-based solutions and applications and, consequently, protect information and assets from unauthorized disclosure, modification, and destruction. Recommendations for Practitioners: The performed risk assessment on the blockchain use cases herein demonstrates that blockchain can involve security risks that require the establishment of certain measures in order to avoid them. As such, practitioners should not blindly assume that through the use of blockchain all security threats are mitigated. Recommendation for Researchers: The results from our study show that some security risks not covered by existing Standards can be mitigated and reduced when applying our proposed security controls. In addition, researchers should further justify the need for such additional controls and encourage the standardization bodies to incorporate them in their future editions. Impact on Society: Similar to any other emerging technology, blockchain has several drawbacks that, in turn, could have negative impacts on society (e.g., individuals, entities and/or countries). This is mainly due to the lack of a solid national and international standards for managing and mitigating risks associated with such technology. Future Research: The majority of the blockchain use cases in this study are publicly published papers. Therefore, one limitation of this study is the lack of technical details about these respective solutions, resulting in the inability to perform a comprehensive risk identification properly. Hence, this area will be expanded upon in our future work. In addition, covering other standardization bodies in the area of distributed ledger in blockchain technology would also prove fruitful, along with respective future design of relevant security architectures.

Aim/Purpose: The study attempts to analyse the influences of knowledge management capacity on company performance and supply chain practices. It also examines whether supply chain practices significantly and positively impact company performance. Background: Knowledge management capacity is an essential tactical resource that enables the integration and coordination among supply chain stakeholders, but research examining the link between knowledge management capacity and supply chain practices and their impacts on company performance remains scarce. Methodology: The study uses correlation analysis and factor analysis to confirm the theoretical framework’s validity and structural equation modelling to test hypotheses. The data are obtained from 115 halal food firms in China (with a response rate of 82.7%). Contribution: This study’s findings contribute to the Social Capital Theory by presenting the impacts of different supply chain practices on company performance. The findings also suggest the impact of intangible resources on enhancing company performance, contributing to the Resource-based View Theory. These results are a crucial contribution to both academicians and corporate managers working in the Halal food industry. Managers can apply these findings to discover and adopt knowledge management capacity with practical anticipation that these concepts will align with their company strategies. Also, the research motivates managers to concentrate their knowledge management on enhancing companies’ supply chain practices to achieve improved company performance. Findings: This study is an initial effort that provides empirical evidence regarding the relationships among supply chain, knowledge management, and company performance from the perspective of China’s halal food industry. The results prove that knowledge management capacity is the supply chains’ primary success determinant and influencer. Besides, knowledge management capacity positively influences company performance, and supply chain practices directly influence company performance. Recommendations for Practitioners: Managers can apply these study findings to determine and increase knowledge management capacity with practical anticipation that these concepts will align with their company strategies. Also, the research motivates managers to concentrate their knowledge management on enhancing companies’ supply chain practices to achieve improved company performance. Recommendation for Researchers: The study presents a new theoretical framework and empirical evidence for surveying halal food businesses in China. Impact on Society: These results are a significant contribution to the research field and industry focusing on halal foods. Future Research: First, this research focuses only on halal food businesses in China; thus, it is essential to re-examine the hypothesized relations between the constructs in other Chinese business segments and regions. Next, the effect of variables and practices on the theorized framework should be taken into account and examined in other industries and nations.

Aim/Purpose: This research investigates the influence of soft skills on graduates’ employability in the technology industry, using the technology industry sector in Malaysia as a case. Background: Organizations are looking for appropriate mechanisms to hire qualified employees with strong soft skills and hard skills. This requires that job candidates possess a set of qualifications and skills which impact their employability. Methodology: Fuzzy Delphi analysis was conducted as preliminary study to identify the critical soft skills required by technology industry sector. The preliminary study produced ten critical soft skills to form a conceptual model of their influence on employability. Then, an online questionnaire survey was distributed in two industry companies in Malaysia to collect research data, and regression analysis was conducted to validate the conceptual model. Contribution: This research focuses on the influence of soft skills on graduate employability in the technology industry sector, since the selection of the best candidate in the industry will improve employee performance and lead to business success. Findings: The results of regression analysis confirmed that Communication skills, Attitude, Integrity, Learnability, Motivation, and Teamwork are significantly correlated with employability, which means that these soft skills are the critical factors for employability in Malaysian technology companies. Recommendations for Practitioners: The model proposed in this article can be used by employers to give better assessment of candidates’ compatibility with the jobs available. Impact on Society: This research highlights the critical soft skills required by technology industry sector, which will reduce the unemployment percentages among graduates. Future Research: More studies are required to examine the soft skills found in the literature and to define the most important skills from a general perspective of the industry. Future research should assess the moderating role of other variables, such as skills gap, employee performance, and employee knowledge. Furthermore, it is recommended to conduct similar studies of soft skills for employability in other countries.

Aim/Purpose: The aim of this study is to determine the variables which affect the intention to use Near Field Communication (NFC)-enabled smart wearables (e.g., smartwatches, rings, wristbands) payments. Background: Despite the enormous potential of wearable payments, studies investigating the adoption of this technology are scarce. Methodology: This study extends the Technology Acceptance Model (TAM) with four additional variables (Perceived Security, Trust, Perceived Cost, and Attractiveness of Alternatives) to investigate behavioral intentions to adopt wearable payments. The moderating role of gender was also examined. Data collected from 311 Kuwaiti respondents were analyzed using Structural Equation Modeling (SEM) and multi-group analysis (MGA). Contribution: The research model provided in this study may be useful for academics and scholars conducting further research into m-payments adoption, specifically in the case of wearable payments where studies are scarce and still in the nascent stage; hence, addressing the gap in existing literature. Further, this study is the first to have specifically investigated wearable payments in the State of Kuwait; therefore, enriching Kuwaiti context literature. Findings: This study empirically demonstrated that behavioral intention to adopt wearable payments is mainly predicted by attractiveness of alternatives, perceived usefulness, perceived ease of use, perceived security and trust, while the role of perceived cost was found to be insignificant. Recommendations for Practitioners: This study draws attention to the importance of cognitive factors, such as perceived usefulness and ease of use, in inducing users’ behavioral intention to adopt wearable payments. As such, in the case of perceived usefulness, smart wearable devices manufacturers and banks enhance the functionalities and features of these devices, expand on the financial services provided through them, and maintain the availability, performance, effectiveness, and efficiency of these tools. In relation to ease of use, smart wearable devices should be designed with an easy to use, high quality and customizable user interface. The findings of this study demonstrated the influence of trust and perceived security in motivating users to adopt wearable payments, Hence, banks are advised to focus on a relationship based on trust, especially during the early stages of acceptance and adoption of wearable payments. Recommendation for Researchers: The current study validated the role of attractiveness of alternatives, which was never examined in the context of wearable payments. This, in turn, provides a new dimension about a determinant factor considered by customers in predicting their behavioral intention to adopt wearable payments. Impact on Society: This study could be used in other countries to compare and verify the results. Additionally, the research model of this study could also be used to investigate other m-payments methods, such as m-wallets and P2P payments. Future Research: Future studies should investigate the proposed model in a cross-country and cross-cultural perspective with additional economic, environmental, and technological factors. Also, future research may conduct a longitudinal study to explain how temporal changes and usage experience affect users’ behavioral intentions to adopt wearable payments. Finally, while this study included both influencing factors and inhibiting factors, other factors such as social influence, perceived compatibility, personal innovativeness, mobility, and customization could be considered in future research.

Aim/Purpose: This paper aimed to examine the impact of learning orientation on organizational performance of small and medium enterprises (SMEs) via the mediating role of total quality management (TQM) practices and the moderating role of innovation culture. Background: SMEs’ organizational performance in developing countries, particularly in Kuwait, remains below expectation due to increasing competition and inadequate managerial practices that negatively impact their performance. Although several studies had revealed a significant effect of learning orientation on SMEs’ performance, the direct impact of learning orientation on their performance is still unclear. Thus, the link between learning orientation and organizational performance remains inconclusive and requires further examination. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather the data in a specific period. The data were collected by distributing a survey questionnaire to the owners and Chief Executive Officers (CEOs) of Kuwaiti SMEs using online and on-hand instruments with 384 useable data obtained. Furthermore, the partial least square-structural equation modeling (PLS-SEM) analysis was performed to test the hypotheses. Contribution: This study bridged the significant gap in the role of learning orientation on SMEs’ performance in developing countries, specifically Kuwait. In this sense, a conceptual model was introduced, comprising a learning orientation, TQM practices, innovation culture, and organizational performance. In addition, this study confirmed the significant influence of TQM practices and innovation culture as intermediate variables in strengthening the relationship between learning orientation and organizational performance, which has not yet been verified in Kuwait. Findings: The results in this study revealed that learning orientation had a significant impact on organizational performance of SMEs in Kuwait. It could be observed that TQM practices play an important role in mediating the relationship between learning orientation and performance of SMEs, as well as that innovation culture plays an important moderating role in the same relation. Recommendations for Practitioners: This study provided a framework for the decision-makers of SMEs on the significant impact of the antecedents that enhanced the level of organizational performance. Hence, owners/CEOs of SMEs should improve their awareness and knowledge of the importance of learning orientation, TQM practices, and innovation culture since it could significantly influence their performance to achieve success and sustainability when adopted and managed systematically. The CEOs should also consider building an innovation culture in the internal environment, which enables them to transform new knowledge and ideas into innovative methods and practices. Recommendation for Researchers: The results in this study highlighted the mediating effect of TQM practices on the relationship between learning orientation (the independent variable) and organizational performance (the dependent variable) of SMEs and the moderating effect of innovation culture in the same nexus. These relationships were not extensively addressed in SMEs and thus required further validation. Impact on Society: This study also influenced the management strategies and practices adopted by entrepreneurs and policymakers working in SMEs in developing countries, which is reflected in their development and the national economy. Future Research: Future studies should apply the conceptual framework of this study and assess it further in other sectors, including large firms in developing and developed countries, to generalize the results. Additionally, other mechanisms should be introduced as significant antecedents of SMEs’ performance, such as market orientation, technological orientation, and entrepreneurial orientation, which could function with learning orientation to influence organizational performance effectively.

Aim/Purpose: The aim of this study is to develop a research model derived from relevant literature to guide empirical efforts. Background: Companies struggle to innovate, which is essential for improving their performance, surviving in competition, and growing. A number of studies have discussed company innovation capability, stating that innovation capability is influenced by several variables such as cooperation and knowledge management. Therefore, further research is necessary to identify factors playing a role in enhancing innovation capability. Methodology: This study is based on systematic literature review. The stages are: (1) research scope review, (2) comprehensive online research, (3) journal quality assessment, (4) data extraction from journals, (5) journal synthesis, and (6) comprehensive report. The online research used Google Scholar database, by browsing titles, abstracts, and keywords to locate empirical research studies in peer-reviewed journals published in 2010-2020. Furthermore, 62 related articles were found, of which 38 articles were excluded from further analysis and 24 articles were selected because they were more related to the topic. Contribution: The results of this study enrich the research in the field of knowledge management, cooperation, and innovation capability by developing a conceptual framework of innovation capability. The proposed theoretical model may be fundamental in addressing the need of a research model to guide further empirical efforts. Findings: This study provides a research model derived from systematically reviewing relevant literature. The proposed theoretical model was done by incorporating the aspects of knowledge management, cooperation, and innovation capability. The model shows that knowledge management and cooperation are essential aspects of innovation capability. Furthermore, this study also provides the dimensions and sub dimensions of each variable that was established after synthesizing the literature review. Recommendations for Practitioners: Business practitioners can use the identified predictors of innovation capability and the dimensions of each variable to explore their company’s innovation capability. They can also take the relevant variables into consideration when making policies regarding innovation. Recommendation for Researchers: The theoretical model proposed in this study needs validation with further empirical investigation. Impact on Society: Readers of this paper can obtain an understanding that knowledge management and cooperation are essential aspects to consider in enhancing innovation capability. Future Research: Future studies should explore other dimensions of knowledge management and cooperation through alternative approaches and perspectives.

Aim/Purpose: The paper’s objective is to examine the challenges of using the mobile phone to mine location data for effective contact tracing of symptomatic, pre-symptomatic, and asymptomatic individuals and the implications of this technology for public health governance. Background: The COVID-19 crisis has created an unprecedented need for contact tracing across South Africa, requiring thousands of people to be traced and their details captured in government health databases as part of public health efforts aimed at breaking the chains of transmission. Contact tracing for COVID-19 requires the identification of persons who may have been exposed to the virus and following them up daily for 14 days from the last point of exposure. Mining mobile phone location data can play a critical role in locating people from the time they were identified as contacts to the time they access medical assistance. In this case, it aids data flow to various databases designated for COVID-19 work. Methodology: The researchers conducted a review of the available literature on this subject drawing from academic articles published in peer-reviewed journals, research reports, and other relevant national and international government documents reporting on public health and COVID-19. Document analysis was used as the primary research method, drawing on the case studies. Contribution: Contact tracing remains a critical strategy in curbing the deadly COVID-19 pandemic in South Africa and elsewhere in the world. However, given increasing concern regarding its invasive nature and possible infringement of individual liberties, it is imperative to interrogate the challenges related to its implementation to ensure a balance with public governance. The research findings can thus be used to inform policies and practices associated with contact tracing in South Africa. Findings: The study found that contact tracing using mobile phone location data mining can be used to enforce quarantine measures such as lockdowns aimed at mitigating a public health emergency such as COVID-19. However, the use of technology can expose the public to criminal activities by exposing their locations. From a public governance point of view, any exposure of the public to social ills is highly undesirable. Recommendations for Practitioners: In using contact tracing apps to provide pertinent data location caution needs to be exercised to ensure that sensitive private information is not made public to the extent that it compromises citizens’ safety and security. The study recommends the development and implementation of data use protocols to support the use of this technology, in order to mitigate against infringement of individual privacy and other civil liberties. Recommendation for Researchers: Researchers should explore ways of improving digital applications in order to improve the acceptability of the use of contact tracing technology to manage pandemics such as COVID-19, paying attention to ethical considerations. Impact on Society: Since contact tracing has implications for privacy and confidentiality it must be conducted with caution. This research highlights the challenges that the authorities must address to ensure that the right to privacy and confidentiality is upheld. Future Research: Future research could focus on collecting primary data to provide insight on contact tracing through mining mobile phone location data. Research could also be conducted on how app-based technology can enhance the effectiveness of contact tracing in order to optimize testing and tracing coverage. This has the potential to minimize transmission whilst also minimizing tracing delays. Moreover, it is important to develop contact tracing apps that are universally inter-operable and privacy-preserving.

Aim/Purpose: In this work, the authors propose an augmented model for human-centered Unified Communications & Collaboration (UC&C) product design and evaluation, which is supported by previous theoretical work. Background: Although the goal of implementing UC&C in an organization is to promote and mediate group dynamics, increasing overall productivity and collaboration; it does not seem to provide a solution for effective communication. It is clear that there is still a lack of consideration for human communication processes in the development of such products. Methodology: This paper is sustained by existing research to propose and test the application of an augmented model capable of supporting the design, development and evaluation of UC&C services that can be driven by the human communication process. To test the application of the augmented model in UC&C service development, a proof-of-concept mobile prototype was elaborated upon and evaluated, making use of User Experience (UX) and user-centred methods and techniques. A total of nine testing sessions were carried out in an organizational communication setup and recorded with eye tracking technology. Contribution: The authors argue that UC&C services should look at the user’s (human) natural processes to improve effective infocommunication and thus enhance collaboration. Authors believe this augmented version of the model will pave the way improving the research and development of useful and practical infocommunication products, capable of truly serving users’ needs. Findings: On evaluation of the prototype, qualitative data analysis uncovered structural problems in the proposed prototype which hindered the augmented model’s elements and subsequently, the user experience. Five out of eighteen identified interaction issues are highlighted in this paper to demonstrate the proposed augmented model’s validity, applied in UC&C services evaluation. Recommendations for Practitioners: Considering and respecting the user’s natural communication processes, practitioners should be able to propose and develop innovative solutions that truly enable and empower effective organizational collaboration. UC&C functionalities should be designed, taking the augmented model’s proposed elements and their pertinence in representing the human interpersonal communication phenomena into consideration, namely: Social Presence; Immediacy of Communication; Concurrency and Synchronicity. Recommendation for Researchers: This paper intends to demonstrate that the adoption and use of UTAUT technology characteristics, in conjunction with Synchronicity proposition, can be considered as a reference for human-centric design and the evaluation of UC&C systems. Impact on Society: To highlight the need to develop further research on this important topic of human collaboration mediated by technology inside organizations. Future Research: This research focused its attention on communication functionalities. However, collaboration can potentially be affected by other services that may be included in a UC&C system, such as scheduling, meetings or task management. Future research could consider employing this augmented model to evaluate such systems or proof-of-concept prototypes.

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.

Table of Contents for Volume 16, 2021, of the Interdisciplinary Journal of Information, Knowledge, and Management

Aim/Purpose: This study investigated a model of mobile esports acceptance among urban citizens based on an extended Technology Acceptance Model (TAM). Background: Currently, esports are increasingly popular and in demand by the public. Supported by the widespread development of mobile devices, it has become an interactive market trend to play games in a new model, mobile esports. Methodology: This study collected data from 400 respondents and analyzed it using partial least squares-structural equation modeling (PLS-SEM). Contribution: This study addresses two research gaps. The first gap is limited esports information systems studies, particularly in mobile esports acceptance studies. The second gap is limited exploration of external variables in online gaming acceptance studies. Thus, this study proposed a TAM extended model by integrating the TAM native variables with other external variables such as visual appeal, enjoyment, social interaction, and competition to explore mobile esports acceptance by urban citizens. Findings: Nine hypotheses were accepted, and four were rejected. The visual appeal did not affect the acceptance. Meanwhile, social interaction and enjoyment significantly affected both perceived ease of use and usefulness. However, perceived ease of use surprisingly had an insignificant effect on attitude toward using mobile esports. Moreover, competition significantly affected the acceptance, particularly on perceived usefulness. Recommendations for Practitioners: Fresh and innovative features, such as new game items or themes, should be frequently introduced to enhance players’ continued enjoyment. Moreover, mobile esports providers should offer a solid platform to excite players’ interactions to increase the likelihood that users feel content. On the other hand, the national sports ministry/agency or responsible authorities should organize many esports competitions, big or small, to search for new talents. Recommendation for Researchers: Visual appeal in this study did not influence the perceived ease of use or usefulness. However, it could affect enjoyment. Thus, it would be worth revisiting the relationship between visual appeal and enjoyment. At the same time, perceived ease of use is a strong driver for the continued use of most online games, but not in this study. It could indicate significant differences between mobile esports and typical online games, one of which is the different purposes. Users might play online games for recreational intention, but players would use mobile esports to compete, win, or even get monetary rewards. Therefore, although users might find mobile esports challenging and hard to use, they tend to keep playing it. Thus, monetary rewards could be considered a determinant of the continuation of use. Impact on Society: Nowadays, users are being paid for playing games. It also would be an excel-lent job if they become professional esports athletes. This study investigated factors that could affect the continued use of mobile esports. Like other jobs, playing games professionally in the long term could make the players tedious and tired. Therefore, responsible parties, like mobile esports providers or governments, could use the recommendations of this study to promote positive behavior among the players. They will not feel like working and still con-sider playing mobile esports a hobby if they happily do the job. In the long run, the players could also make a nation’s society proud if they can be a champion in prestigious competitions. Future Research: A larger sample size will be needed to generalize the results, such as for a nation. It is also preferable if the sample is randomized systematically. Future works should also investigate whether the same results are acquired in other mobile esports. Furthermore, to extend our knowledge and deepen our understanding of the variables that influence mobile esports adoption, the subsequent research could look at other mobile esports acceptability based on characteristics of system functionality and moderator effects. Finally, longitudinal data-collecting approaches are suggested for future studies since behavior can change over time.

Aim/Purpose: This study focuses on the connection between IT-producing firms’ digital service capabilities and the digital service performance of IT-consuming firms, especially online shop operators. Background: The acquisition and integration of knowledge regarding digital service capabilities and performance can increase the level at which employees assimilate information, organize with IT-consuming firms, and cooperate with them to develop the delivery of services and customize services to fill their needs. Exploring capabilities that may enable this process is a prerequisite for all businesses offering digital services and, thus, an engrossing and ongoing interest of practitioners and scholars. However, there is a lack of research on the relationship between IT-producing firms’ digital service capabilities and the digital service performance of IT-consuming firms in the business-to-business (B2B) context. Methodology: The study builds on a survey conducted among small firms that have an online shop in use and are located in Finland. Contribution: The study offers empirical evidence for the capabilities valued by IT-consuming firms, providing a model for IT-producing firms to use when deciding on a future focus. The study was executed in a B2B setting from the viewpoint of online shop operators, presenting a novel understanding of influential digital service capabilities. Findings: Adaptability, determined by capabilities related to utilizing information gained via the integration of a digital product into other digital tools (e.g., marketing, personalization, and analytics), statistically significantly affects all three aspects of an IT-consuming firm’s digital service performance (financial, operational, and sales). Another product capability, availability, which includes aspects such as security, different aspects of functioning, and mobile adaptation, affects one aspect of digital performance, namely operational. The results also suggest that the role of service process-related capabilities in determining service comprehensiveness significantly influences two aspects of IT-consuming firms’ digital service performance: financial (negative effect) and operational (positive effect). The results show that the capabilities associated with the relationship between the producing firm and the consuming firm do not affect IT-consuming firms’ performance to the same extent. Recommendations for Practitioners: The study results suggest that IT-producing firms should concentrate on leveraging service comprehensiveness, as there has been a shift in the B2B context from merely selling a digital product and associated services. It seems that usability-related issues are now taken for granted, and the emphasis is on features that support the use of information to create value. Recommendation for Researchers: The results contribute to the capabilities literature by showing that the shift in focus from technical product-related capabilities to relationship-related capabilities is not yet evident among small online store operators. Impact on Society: In addition to offering tools with different integration possibilities, supporting IT-consuming firms in making the most of the possibilities would be very helpful. Future Research: The comprehension of the relationship between digital service capabilities and digital service performance would benefit from future research that takes into account additional control variables. The theoretical model of this study can be further studied by using other performance measures, such as market performance, as dependent variables.

Aim/Purpose: The aim of this study is to identify Critical Success Factors (CSF) of Business Intelligence (BI) and provide a framework to classify CSF into layers or perspectives using an enterprise architecture approach, then rank CSF within each perspective and evaluate the importance of each perspective at different BI maturity levels as well. Background: Although the implementation of the BI project has a significant impact on creating analytical and competitive capabilities, the lack of evaluation of CSF holistically is still a challenge. Moreover, the BI maturity level of the organization has not been considered in the BI implementation project. Identifying BI critical success factors and their importance can help the project team to move to a higher maturity level in the organization. Methodology: First, a list of distinct CSF is identified through a literature review. Second, a framework is provided for categorizing these CSF using enterprise architecture. Interviewing is the research method used to evaluate the importance of CSF and framework layers with two questionnaires among experts. The first questionnaire was done by Analytical Hierarchy Process (AHP), a quantitative method of decision-making to calculate the weight of the CSF according to the importance of CSF in each of the framework layers. The second one was conducted to evaluate framework layers at different BI maturity levels using a Likert scale. Contribution: This paper contributes to the implementation of BI projects by identifying a comprehensive list of CSF in the form of a holistic multi-layered framework and ranking the importance of CSF and layers at BI maturity levels. Findings: The most important CSF in BI implementation projects include senior management support, process identification, data quality, analytics quality, hardware quality, security standards, scope management, documentation, project team skills, and customer needs transformation, which received the highest scores in framework layers. In addition, it was observed that as the organization moves to higher levels of maturity, the average importance of strategic business and security perspectives or layers increases. But the average importance of data, applications, infrastructure, and network, the project management layers in the proposed framework is the same regardless of the level of business intelligence maturity. Recommendations for Practitioners: The results of this paper can be used by academicians and practitioners to improve BI project implementation through understanding a comprehensive list of CSF and their importance. This awareness causes us to focus on the most important CSF and have better planning to reach higher levels of maturity according to the maturity level of the organization. Future Research: For future research, the interaction of critical success factors of business intelligence and framework layers can be examined with different methods.

Aim/Purpose: The main goal of this systematic literature review was to look for studies that provide information relevant to business intelligence’s (BI) framework development and implementation in the tourism sector. This paper tries to classify the tourism sectors where BI is implemented, group various BI functionalities, and identify common problems encountered by previous research. Background: There has been an increased need for BI implementation to support decision-making in the tourism sector. Tourism stakeholders such as management of destination, accommodation, transportation, and public administration need a guideline to understand functional requirements before implementation. This paper addresses the problem by comprehensively reviewing the functionalities and issues that need to be considered based on previous business intelligence framework development and implementation in tourism sectors. Methodology: We have conducted a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Guidelines for Meta-Analysis (PRISMA) method. The search is conducted using online academic database platforms, resulting in 543 initial articles published from 2002 to 2022. Contribution: The paper could be of interest to relevant stakeholders in the tourism industry because it provides an overview of the capabilities and limitations of business intelligence for tourism. To our knowledge, this is the first study to identify and classify the BI functionalities needed for tourism sectors and implementation issues related to organizations, people, and technologies that need to be considered. Findings: BI functionalities identified in this study include basic functions such as data analysis, reports, dashboards, data visualization, performance metrics, and key performance indicator, and advanced functions such as predictive analytics, trend indicators, strategic planning tools, profitability analysis, benchmarking, budgeting, and forecasting. When implementing BI, the issues that need to be considered include organizational, people and process, and technological issues. Recommendations for Practitioners: As data is a major issue in BI implementation, tourism stakeholders, especially in developing countries, may need to build a tourism data center or centralized coordination regulated by the government. They can implement basic functions first before implementing more advanced features later. Recommendation for Researchers: We recommend further studying the BI implementation barriers by employing a perspective of an adoption framework such as the technology, organization, and environment (TOE) framework. Impact on Society: This research has a potential impact on improving the tourism industry’s performance by providing insight to stakeholders about what is needed to help them make more accurate decisions using business intelligence. Future Research: Future research may involve collaboration between practitioners and academics in developing various BI architectures specific to each tourism industry, such as destination management, hospitality, or transportation.

Aim/Purpose: The aim of this study was to identify the critical predictors affecting project desertion in Blockchain projects. Background: Blockchain is one of the innovations that disrupt a broad range of industries and has attracted the interest of software developers. However, despite being an open-source software (OSS) project, the maintenance of the project ultimately relies on small core developers, and it is still uncertain whether the technology will continue to attract a sufficient number of developers. Methodology: The study utilized a systematic literature review (SLR) and an expert review method. The SLR identified 21 primary studies related to project desertion published in Scopus databases from the year 2010 to 2020. Then, Blockchain experts were asked to rank the importance of the identified predictors of project desertion in Blockchain. Contribution: A theoretical framework was constructed based on Social Cognitive Theory (SCT) constructs; personal, behavior, and environmental predictors and related theories. Findings: The findings indicate that the 12 predictors affecting Blockchain project desertion identified through SLR were important and significant. Recommendations for Practitioners: The framework proposed in this paper can be used by the Blockchain development community as a basis to identify developers who might have the tendency to abandon a Blockchain project. Recommendation for Researchers: The results show that some predictors, such as code testing tasks, contributed code decoupling, system integration and expert heterogeneity that are not covered in the existing developer turnover models can be integrated into future research efforts. Impact on Society: This study highlights how an individual’s design choices could determine the success or failure of IS projects. It could direct Blockchain crypto-currency investors and cyber-security managers to pay attention to the developer’s behavior while ensuring secure investments, especially for crypto-currencies projects. Future Research: Future research may employ additional methods, such as a meta-analysis, to provide a comprehensive picture of the main predictors that can predict project desertion in Blockchain.

Aim/Purpose: This study examined the relationship between critical success factors (CSFs), perceived benefits, and usage intention of Mobile Knowledge Management Systems (MKMS) via an integrated Technology Acceptance Model (TAM) and Information Systems Success Model (ISSM). Background: This study investigates the CSFs (i.e., Strategic Leadership, Employee Training, System Quality, and Information Quality) that impact the usage intention of KMS in mobile contexts which have been neglected. Since users normally consider the usefulness belief in a system before usage, this study examines the role of perceived benefits as a mediator between the CSFs and usage intention. Methodology: A survey-based research approach in the Malaysian semiconductor industry was employed via an integrated model of TAM and ISSM. At a response rate of 59.52%, the findings of this study were based on 375 usable responses. The data collected was analyzed using the Partial Least Squares with SmartPLS 3.0. Contribution: This study contributes to the body of knowledge in the areas of mobile technology acceptance and knowledge management. Specifically, it helps to validate the integrated model of TAM and ISSM with the CSFs from knowledge management and information system. In addition, it provides the would-be adopters of MKMS with valuable guidelines and insights to consider before embarking on the adoption stage. Findings: The findings suggest that Employee Training and Information Quality have a positive significant relationship with Perceived MKMS Benefits. On the contrary, Strategic Leadership, System Quality, and Perceived User-friendliness showed an insignificant relationship with Perceived MKMS Benefits. Additionally, Employee Training and Information Quality have an indirect relationship with MKMS Usage Intention which is mediated by Perceived MKMS Benefits. Recommendations for Practitioners: The findings are valuable for managers, engineers, KM practitioners, KM consultants, MKMS developers, and mobile device producers to enhance MKMS usage intention. Recommendation for Researchers: Researchers would be able to conduct more inter-disciplinary studies to better understand the relevant issues concerning both fields – knowledge management and mobile computing disciplines. Additionally, the mediation effect of TAM via Perceived Usefulness (i.e., perceived MKMS benefits) on usage intention of MKMS should be further investigated with other CSFs. Future Research: Future studies could perhaps include other critical factors from both KM and IS as part of the external variables. Furthermore, Perceived Ease of Use (i.e., Perceived User-friendly) should be tested as a mediator in the future, together with Perceived Usefulness (i.e., perceived MKMS Benefits) to compare which would be a more powerful predictor of usage intention. Moreover, it may prove interesting to find out how the research framework would fit into other industries to verify the findings of this study for better accuracy and generalizability.

Aim/Purpose: Currently, the world faces unprecedented challenges due to COVID-19, particularly concerning individuals’ health and livelihood and organizations and industrial performance. Indeed, the pandemic has caused rapid intensifying socio-economic effects. For instance, organizations are shifting from traditional working patterns toward telecommuting. By adopting remote working, organizations might mitigate the impact of COVID-19 on their workforce, explicitly concerning their safety, wellbeing, mobility, work-life balance, and self-efficiency. From this perceptive, this study examines the factors that influence employees’ behavioral intention to adopt telecommuting in the banking industry. Background: The study’s relevance stems from the fact that telecommuting and its benefits have been assumed rather than demonstrated in the banking sector. However, the pandemic has driven the implementation of remote working, thereby revealing possible advantages of working from home in the banking industry. The study investigated the effect of COVID-19 in driving organizations to shift from traditional working patterns toward telecommuting. Thereby, the study investigates the banking sector employees’ behavioral intention to adopt telecommuting. Methodology: The study employed a survey-based questionnaire, which entails gathering data from employees of twelve banks in Jordan, as the banking sector in Jordan was the first to transform from traditional working to telecommuting. The sample for this research was 675 respondents; convenience sampling was employed as a sampling technique. Subsequently, the data were analyzed with the partial least square structural equation modeling (PLS-SEM) to statistically test the research model. Contribution: Firstly, this study provides a deep examination and understanding of facilitators of telecommuting in a single comprehensive model. Secondly, the study pro-vides a deeper insight into the factors affecting behavioral intention towards telecommuting from the employees’ perspective in the banking sector. Finally, this study is the first to examine telecommuting in the emerging market of Jordan. Thereby, this study provides critical recommendations for managers to facilitate the implementation of telecommuting. Findings: Using the Technology Acceptance Model (TAM), this study highlights significant relationships between telecommuting systems, quality, organizational support, and the perceived usefulness and ease of use in telecommuting. Employees who perceive telecommuting systems to be easy and receive supervision and training for using these systems are likely to adopt this work scheme. The results present critical theoretical and managerial implications regarding employees’ behavioral intentions toward telecommuting. Recommendations for Practitioners: This study suggests the importance of work-life balance for employees when telecommuting. Working from home while managing household duties can create complications for employees, particularly parents. Therefore, flexibility in terms of working hours is needed to increase employees’ acceptance of telecommuting as they will have more control over their life. These increase employees’ perceived self-efficacy with telecommuting, which smooths the transition toward remote working in the future. In addition, training will allow employees to solve technical issues that can arise from using online systems. Recommendation for Researchers: This study focused on the context of the banking sector. The sensitivity of data and transactions in this sector may influence employers’ and employees’ willingness to work remotely. In addition, the job descriptions of employees in banks moderate specific factors outlined in this model, including work-life balance. For instance, executive managers may have a higher overload in banks in contrast to front-line employees. Thus, future studies should explore different contexts, including manufacturing and consultation, to understand the industry’s effect on remote working. Similarly, future research should concentrate on the influence of job descriptions on employees’ intentions toward telecommuting. Impact on Society: The COVID-19 pandemic created a sudden shift towards telecommuting, which made employees struggle to adopt new work schemes. Therefore, managers had to provide training for their employees to be well prepared and increase their acceptance of telecommuting. Furthermore, telecommuting has a positive effect on work-life balance, it provides employees with the flexibility to organize their daily schedule into more activities. Along the same line, the study highlighted the correlation between work-life balance and telecommuting. Such a relationship provides further evidence for the need to understand employees’ lifestyles in facilitating the adoption of telecommuting. Moreover, the study extends the stream of literature by outlining critical factors affecting employees’ acceptance of telecommuting. Future Research: Future studies should explore different contexts, including manufacturing and consultation, to understand the industry’s effect on remote working. Similarly, future research should concentrate on the influence of job descriptions on employees’ intentions toward telecommuting. Furthermore, the research team conducted the study by surveying 12 banks. Future research recommends surveying the whole banking industry to add more validation to the model.

Aim/Purpose: This study examines the impact of decision-making, crisis management, and decision-making on sustainability through the mediation of open innovation in the energy sector. Background: Public companies study high-performance practices, requiring overcoming basic obstacles such as financial crises that prevent the adoption and development of sustainability programs. Methodology: Due to the COVID-19 pandemic, which has led to the closure of businesses in Iraq, a survey was distributed. To facilitate responses, free consultations were offered to help complete the questionnaire quickly. Of the 435 questionnaires answered, 397 were used for further analysis. Contribution: The impact of crises that impede the energy sector from adopting sustainable environmental regulations is investigated in this study. Its identification of specific constraints to open innovation leads to the effectiveness of adopting environmentally friendly policies and reaching high levels of sustainable performance. Findings: The impacts of risk-taking, crisis management, and decision-making on sustainability have been explored. Results show that open innovation fully mediates the relationship between the factors of risk-taking, crisis management, decision-making, and sustainability. Recommendations for Practitioners: The proposed model can be used by practitioners to develop and improve sustainable innovation practices and achieve superior performance. Recommendation for Researchers: Researchers are recommended to conduct in-depth studies of the phenomenon based on theoretical and empirical foundations, especially in light of the relationship between crisis management, decision-making, and risk-taking and their impact on sustainability based on linear and non-compensatory relationships. Impact on Society: This study provides a reference for organizations with similar cultural backgrounds in adopting sustainable practices to minimize pollution in the Iraqi context. Future Research: A more in-depth study can be performed using a larger sample, which not only includes the energy industry but also other industries.

Aim/Purpose: Although the significance of data provenance has been recognized in a variety of sectors, there is currently no standardized technique or approach for gathering data provenance. The present automated technique mostly employs workflow-based strategies. Unfortunately, the majority of current information systems do not embrace the strategy, particularly biodiversity information systems in which data is acquired by a variety of persons using a wide range of equipment, tools, and protocols. Background: This article presents an automated technique for producing temporal data provenance that is independent of biodiversity information systems. The approach is dependent on the changes in contextual information of data items. By mapping the modifications to a schema, a standardized representation of data provenance may be created. Consequently, temporal information may be automatically inferred. Methodology: The research methodology consists of three main activities: database event detection, event-schema mapping, and temporal information inference. First, a list of events will be detected from databases. After that, the detected events will be mapped to an ontology, so a common representation of data provenance will be obtained. Based on the derived data provenance, rule-based reasoning will be automatically used to infer temporal information. Consequently, a temporal provenance will be produced. Contribution: This paper provides a new method for generating data provenance automatically without interfering with the existing biodiversity information system. In addition to this, it does not mandate that any information system adheres to any particular form. Ontology and the rule-based system as the core components of the solution have been confirmed to be highly valuable in biodiversity science. Findings: Detaching the solution from any biodiversity information system provides scalability in the implementation. Based on the evaluation of a typical biodiversity information system for species traits of plants, a high number of temporal information can be generated to the highest degree possible. Using rules to encode different types of knowledge provides high flexibility to generate temporal information, enabling different temporal-based analyses and reasoning. Recommendations for Practitioners: The strategy is based on the contextual information of data items, yet most information systems simply save the most recent ones. As a result, in order for the solution to function properly, database snapshots must be stored on a frequent basis. Furthermore, a more practical technique for recording changes in contextual information would be preferable. Recommendation for Researchers: The capability to uniformly represent events using a schema has paved the way for automatic inference of temporal information. Therefore, a richer representation of temporal information should be investigated further. Also, this work demonstrates that rule-based inference provides flexibility to encode different types of knowledge from experts. Consequently, a variety of temporal-based data analyses and reasoning can be performed. Therefore, it will be better to investigate multiple domain-oriented knowledge using the solution. Impact on Society: Using a typical information system to store and manage biodiversity data has not prohibited us from generating data provenance. Since there is no restriction on the type of information system, our solution has a high potential to be widely adopted. Future Research: The data analysis of this work was limited to species traits data. However, there are other types of biodiversity data, including genetic composition, species population, and community composition. In the future, this work will be expanded to cover all those types of biodiversity data. The ultimate goal is to have a standard methodology or strategy for collecting provenance from any biodiversity data regardless of how the data was stored or managed.

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

Aim/Purpose: This study aims to examine the roles of key traits of m-university services and their users in promoting two crucial post-adoption outcomes of these services; namely, continuance usage intention and perceived value. Background: M-university (i.e., a university providing services via mobile technologies) has gained a great interest in the higher education sector as a driver of new business models and innovative service offerings. However, its assessment has been greatly overlooked, especially in evaluating the factors that drive the stakeholders’ continuance intention to use it and the determinants of its post-adoption perceived value. Consequently, research efforts undertaking such assessment facets empirically are highly required. Methodology: An integrated research model that enables such assessment was developed and evaluated using a quantitative research methodology. Accordingly, data were collected using a formulated closed-ended survey questionnaire. The target population consisted of the academic staff of a Saudi public university that has witnessed an extensive adoption of m-university services. The obtained data (i.e., 207 fully completed responses) were evaluated using the structural equation modeling approach. Contribution: To the best of our knowledge, this is the first study that gains the chance to provide the research community and m-service providers with new knowledge and understanding about the predictors that drive the continuance usage intention and value of m-university services. Findings: The findings showed that all of the examined traits of m-university services and their users (i.e., reliability, usability, customization, self-efficacy, and involvement) are having positive roles in promoting the continuance intention to use these services, while only two traits (i.e., reliability and involvement) contribute significantly to augmenting the perceived value. Recommendations for Practitioners: The study recommends developing effective design and implementation specifications that strengthen the contributions of the examined traits in the post-adoption stage of m-university services. Recommendation for Researchers: Further studies should be devoted to addressing the notable need to assess the factors influencing the adoption of m-university services, as well as to explore which ones are having significant roles in the attainment of post-adoption outcomes. Impact on Society: The empirical insights provided by the present study are essential for both university stakeholders and mobile service providers in their endeavors to improve the key aspects of the anticipated post-adoption outcomes of the provided services. Future Research: Further empirical investigations are needed to examine the roles of more m-university services and user traits in achieving a broad range of post-adoption outcomes of such services.

Aim/Purpose: Mobile commerce adoption is low in developing countries; hence, public servants may not consider mobile commerce and mobile payments. Understanding the factors that influence mobile commerce and mobile payments in their context will aid in promoting those services. Background: The study investigates the factors that influence public servants’ mobile commerce and mobile payments in Ghana. Hence, it provides some understanding of the various aspects of mobile commerce and mobile payments adoption, such as acceptance, use, and eventual adoption into the user’s daily life, and how that affects their behaviour. Methodology: The research was conducted by surveying the factors influencing public servants’ adoption of mobile commerce and payments in Ghana. A cross-sectional survey was undertaken to put the research model to the test to measure the constructs and their relationships. Contribution: The study confirmed previous findings and created a new conceptual model for mobile commerce and mobile payment adoption and usage in the Ghanaian context. Findings: The variables of performance expectancy, trust, and facilitating conditions have a significant positive influence on behavioural intention. The factors of effort expectation and social influence have a significant negative impact. Price value and perceived reliability are latent variables that do not affect behavioural intention. Behavioural intention and facilitating conditions significantly influence the actual use behaviour of mobile commerce and mobile payment users. Recommendations for Practitioners: Mobile commerce is emerging as a new mode of transactions, with firms providing enabling platforms for users. Mobile commerce could become the most acceptable application for the next generation of mobile platform applications. This study offers insights into the fluidity of the mobile environment, with implications that spell out what will be effective mobile commerce services that will continue to be relevant. Mobile applications are attractive to people because they provide a better user experience. These mobile applications have been optimised to provide a fast, easy and delightful experience. Mobile commerce and mobile payment service providers can attract and retain more users if attention is paid to performance expectancy, trust, and facilitating conditions since they influence individuals’ decisions to adopt. Mobile technology is almost ubiquitous, influencing both online sales and in-store sales. With the right mobile commerce platform and features, businesses can expect to increase in-store and online sales, catering to a more extensive clientele. Mobile devices are the primary means that most customers use to look up information about products they see in stores, such as product reviews and pricing options. This study indicates that mobile commerce service providers can achieve a more extensive customer base by promoting performance expectancy, trust, and behavioural intentions. Recommendation for Researchers: Despite the numerous studies in the mobile commerce literature, few have used integrated models of perceived reliability, trust, and price value or methods to evaluate these factors in the emerging mobile commerce industry. Also, it combines mobile commerce and mobile payments, which very few that we know of have done. Impact on Society: Ghana is already in a cash-lite economy. Thus, the study is appropriate with the result of trust being a significant factor. It implies that people will begin using mobile commerce and mobile payments with a bit of drive to bring about this drive quickly. Future Research: Future research could further test the adapted model with moderating factors of age, gender, and education to delve deeper into the complexities of mobile commerce and mobile payments.

Aim/Purpose: This paper identified and explored the factors influencing Bitcoin adoption and use in South Africa. Background: Since its introduction in 2008, the value and popularity of Bitcoin has risen exponentially. Captivating the eyes of the world, from regulators to economists, Bitcoin promises to revolutionize the digital currency space. Despite being over 10 years old, the concept of cryptocurrency is fairly new in South Africa, a developing country. South African’s interest in Bitcoin continues to grow with the country constantly ranking within the top 10 in online searches for “Bitcoin” and “cryptocurrency” on Google. The primary objective of this research was to identify adoption factors amongst South African citizens, an area that has not received much research focus in the past. In addition to this, the study aimed to identify how Bitcoin is primarily used in South Africa. Methodology: A survey-based questionnaire was utilized to obtain responses from adopters of Bitcoin in South Africa. The quantitative survey was completed by 204 respondents. Contribution: This research contributes to the body of knowledge relating to Bitcoin adoption, specifically from a developing country. Adoption factors are identified that can be utilized by businesses that intend to adopt cryptocurrency, to strategically prepare for the potential risks or opportunities brought about by Bitcoin and cryptocurrency in general. Findings: The findings of this study indicate that while perceived usefulness, perceived ease of use, subjective norms, and facilitating conditions positively influence intention to adopt Bitcoin, trust was the only construct that is statistically significant and hence is the greatest driver of adoption in South Africa. In terms of its primary use in South Africa, the study revealed that Bitcoin is used as a speculative instrument for short-term trading in South Africa followed by being used as a long-term investment in the crypto-asset class. No respondent indicated that they utilize Bitcoin as a payment method in South Africa. Recommendations for Practitioners: When developing crypto-based investment products, custodians of assets must ensure that a minimum-security protocol is followed to safeguard these assets. This will enhance the trust that potential investors and customers have in their systems and products. Recommendation for Researchers: This study focused on adoption factors for South African citizens. Future studies should be conducted to identify adoption factors by businesses in South Africa. Impact on Society: Bitcoin offers an alternate trading instrument and investment option, with the possibility of large gains over a relatively short period. Bitcoin also presents the possibility of cross-border transactions at a significantly lower cost compared to traditional cross-border transfers of funds. Future Research: Studies should be conducted to explore the factors influencing the adoption of altcoins to determine if the technological differences influence the adoption of one currency over the other. Research should also be conducted comparing the taxation of cryptocurrency in various countries around the world.

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

Aim/Purpose: This paper aims to analyze how artisans in Ghana are incorporating mobile commerce into their everyday business and how perceived usefulness, perceived ease of use, subjective norms, age, gender, expertise, and educational level affected the adoption and usage of m-commerce. Background: This study integrates well-established theoretical models to create a new conceptual model that ensures a comprehensive mobile commerce adoption survey. Methodology: A cross-sectional survey was conducted to measure the constructs and their relations to test the research model. Contribution: The study’s findings confirmed previous results and produced a new conceptual model for mobile commerce adoption and usage. Findings: Except for gender, perceived ease of use, and subjective norms that did not have specific effects on mobile commerce adoption, age, educational level, perceived usefulness, expertise, attitude, and behavioral intention showed significant effects. Recommendations for Practitioners: First of all, mobile commerce service providers should strategically pay critical attention to customer-centered factors that positively affect the adoption of mobile commerce innovations than focusing exclusively on technology-related issues. Mobile service providers can attract more users if they carefully consider promoting elements like perceived usefulness and perceived ease of use which directly or indirectly affect the individuals’ decision to adopt information technology from consumer perspectives. Second, mobile commerce service providers should strategically focus more on younger individuals since, per the research findings, they are more likely to adopt mobile commerce innovations than the older folks in Ghana. Third, service providers should also devise strategies to retain actual users of m-commerce by promoting elements like behavioral intentions and attitude, which according to the research findings, have a higher predictive power on actual usage of m-commerce. Recommendation for Researchers: The conceptual model developed can be employed by researchers worldwide to analyze technology acceptance research. Impact on Society: The study’s findings suggested that mobile commerce adoption could promote a cashless society that is convenient for making buying things quicker and easier. Future Research: The research sample size could be increased, and also the study could all sixteen regions in Ghana or any other country for a broader representation.

Aim/Purpose: This paper aims to analyze the availability and pricing of perishable farm produce before and during the lockdown restrictions imposed due to Covid-19. This paper also proposes machine learning and deep learning models to help the farmers decide on an appropriate market to sell their farm produce and get a fair price for their product. Background: Developing countries like India have regulated agricultural markets governed by country-specific protective laws like the Essential Commodities Act and the Agricultural Produce Market Committee (APMC) Act. These regulations restrict the sale of agricultural produce to a predefined set of local markets. Covid-19 pandemic led to a lockdown during the first half of 2020 which resulted in supply disruption and demand-supply mismatch of agricultural commodities at these local markets. These demand-supply dynamics led to disruptions in the pricing of the farm produce leading to a lower price realization for farmers. Hence it is essential to analyze the impact of this disruption on the pricing of farm produce at a granular level. Moreover, the farmers need a tool that guides them with the most suitable market/city/town to sell their farm produce to get a fair price. Methodology: One hundred and fifty thousand samples from the agricultural dataset, released by the Government of India, were used to perform statistical analysis and identify the supply disruptions as well as price disruptions of perishable agricultural produce. In addition, more than seventeen thousand samples were used to implement and train machine learning and deep learning models that can predict and guide the farmers about the appropriate market to sell their farm produce. In essence, the paper uses descriptive analytics to analyze the impact of COVID-19 on agricultural produce pricing. The paper explores the usage of prescriptive analytics to recommend an appropriate market to sell agricultural produce. Contribution: Five machine learning models based on Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Random Forest, and Gradient Boosting, and three deep learning models based on Artificial Neural Networks were implemented. The performance of these models was compared using metrics like Precision, Recall, Accuracy, and F1-Score. Findings: Among the five classification models, the Gradient Boosting classifier was the optimal classifier that achieved precision, recall, accuracy, and F1 score of 99%. Out of the three deep learning models, the Adam optimizer-based deep neural network achieved precision, recall, accuracy, and F1 score of 99%. Recommendations for Practitioners: Gradient boosting technique and Adam-based deep learning model should be the preferred choice for analyzing agricultural pricing-related problems. Recommendation for Researchers: Ensemble learning techniques like Random Forest and Gradient boosting perform better than non-Ensemble classification techniques. Hyperparameter tuning is an essential step in developing these models and it improves the performance of the model. Impact on Society: Statistical analysis of the data revealed the true nature of demand and supply and price disruption. This analysis helps to assess the revenue impact borne by the farmers due to Covid-19. The machine learning and deep learning models help the farmers to get a better price for their crops. Though the da-taset used in this paper is related to India, the outcome of this research work applies to many developing countries that have similar regulated markets. Hence farmers from developing countries across the world can benefit from the outcome of this research work. Future Research: The machine learning and deep learning models were implemented and tested for markets in and around Bangalore. The model can be expanded to cover other markets within India.

Aim/Purpose: ************************************************************************ After its investigation, the Research Ethics, Integrity, and Governance team at RMIT University found that the primary author of this paper breached the Australian Code and/or RMIT Policy and requested that the article be retracted. ************************************************************************** This paper aimed to examine the influence of ethical and transformational leadership on employee creativity in Malaysia’s private higher education institutions (PHEIs) and the mediating role of organizational citizenship behavior. Background: To ensure their survival and success in today’s market, organizations need people who are creative and driven. Previous studies have demonstrated the importance of ethical leadership in fostering employee innovation and good corporate responsibility. Research on ethical leadership and transformational leadership, in particular, has played a significant role in elucidating the role of leadership in relation to organizational citizenship behavior (OCB). In this study, we have focused on ethical and transformational leadership as an antecedent for enhancing employee creativity. Despite an increase in leadership research, little is known about the underlying mechanisms that link ethical leadership and transformational leadership to OCB. Because it sheds light on factors other than ethical leadership and transformational leadership that influence employees’ extra-role activity, this research is relevant theoretically. OCB may have a mediating function between ethical leadership and transformational leadership style and employee creativity because it is associated with the greatest outcomes, but empirical research has yet to prove this. So, one of the study’s goals is to add to the hypotheses about how ethical leadership style and transformational leadership affect employee creativity by using an important mediating variable – OCB. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather the data in a specific period. A convenient sampling approach was used to gauge 275 employees from Malaysia’s PHEIs. To test the hypotheses and obtain a conclusion, the acquired data was analyzed using the partial least square technique (PLS-SEM). Contribution: The study contributes to leadership literature by advancing OCB as a mediating factor that accounts for the link between ethical and transformational leadership and employee creativity in the higher education sector. Findings: According to the research, OCB has a substantial influence on the creativity of employees. Furthermore, ethical leadership boosted OCB and boosted employee creativity, according to the research. OCB and employee creativity have both been demonstrated to benefit greatly from transformational leadership. Further research revealed that OCB is a mediating factor in the link between leadership styles and creative thinking among employees. Recommendations for Practitioners: Higher education institutions should focus on developing leaders who value transparency and self-awareness in their interactions with followers and who demonstrate an inner moral perspective in addition to balanced information processing to ensure positive outcomes at the individual and organizational levels. Higher education institutions should place a priority on hiring leaders that exhibit ethical and transformational traits to raise awareness of these leadership styles among employees. Recommendation for Researchers: The new study also adds significantly to the body of knowledge by examining the relationship between ethical and transformational leadership and the creativity of the workforce. It aimed to identify the relationship between transformational leadership style and individual creativity in higher education by examining the mediating influence of OCB. Impact on Society: Higher education institutions should devise strategies for developing ethical and transformative leaders who will assist boost OCB and creativity within their workforce. Students and faculty in higher education can benefit from these leadership methods by learning to think in more diverse ways and by developing thought processes that lead to a larger pool of innovative ideas and solutions. As a consequence, employees who show creative behavior may be effectively managed by leaders who utilize ethical and transformational leadership styles and motivate them to show OCB that allow them to solve creative problems creatively. Future Research: A mixed-methods approach should be used in future research, and this should be done in public institutions in developing and developed nations to put the findings to use and generalize them even further. Future research will be able to examine other mediators to learn more about how and why ethical and transformational leadership styles affect PHEI employees’ creativity.

Table of Contents for Volume 17, 2022, of the Interdisciplinary Journal of Information, Knowledge, and Management

Aim/Purpose: The study aims to explore the attributes of self-phubbing and partner-phubbing, as well as their impact on marital relationship satisfaction and the quality of communication. Furthermore, it aims to comprehend how these characteristics could impact an individual’s total level of life satisfaction. Background: The study aims to establish a clear association between specific mobile phone usage behaviors and their subsequent impact on relationship satisfaction and the quality of communication. This study investigates the effects of two types of behaviors on interpersonal relationships: self-phubbing, which refers to an individual being deeply absorbed in their own mobile phone use, and partner-phubbing, which refers to witnessing one’s partner being deeply absorbed in a mobile device. Methodology: This study utilizes a quantitative approach. The poll involved 150 smartphone users in Malaysia who are in relationships, and they participated by completing a questionnaire. The data analysis was performed using the Partial Least Squares-based Structural Equation Modeling method. Contribution: This research addresses the gap and gives insight into the consequences of self and partner phubbing and its impact on the relationship and life satisfaction among partners by providing a research model that was validated with primary data. Findings: The results of this survey show that smartphone conflicts harm relationship satisfaction but not communication quality. It was revealed that communication quality does not directly bring a negative impact on life satisfaction, but it directly affects relationship satisfaction, which, in turn, harms life satisfaction. Recommendations for Practitioners: The findings of this study can be used by practitioners to improve relationship counseling and therapy. Through the integration of the notion of phubbing and its impact on relationship happiness, couples can receive guidance on how to reduce the tension that arises from using smartphones. Recommendation for Researchers: Previous research was conducted exclusively on only an individual’s phubbing behavior, but limited work was done on the partner’s phubbing behavior. Future researchers can enhance this model by identifying more factors. Impact on Society: This study addresses broader societal ramifications in addition to the dynamics of particular relationships. This study promotes a more mindful use of smartphones by exposing the complex relationships between technology use, relationship happiness, and general life contentment. This will ultimately lead to healthier relationships and improved societal well-being. Future Research: In the future, we are going to implement an artificial neural network approach to test this data to predict the most important factors that influence phubbing.

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

Aim/Purpose: In this paper, we present an RFM model-based telecom customer churn system for better predicting and analyzing customer churn. Background: In the highly competitive telecom industry, customer churn is an important research topic in customer relationship management (CRM) for telecom companies that want to improve customer retention. Many researchers focus on a telecom customer churn analysis system to find out the customer churn factors for improving prediction accuracy. Methodology: The telecom customer churn analysis system consists of three main parts: customer segmentation, churn prediction, and churn factor identification. To segment the original dataset, we use the RFM model and K-means algorithm with an elbow method. We then use RFM-based feature construction for customer churn prediction, and the XGBoost algorithm with SHAP method to obtain a feature importance ranking. We chose an open-source customer churn dataset that contains 7,043 instances and 21 features. Contribution: We present a novel system for churn analysis in telecom companies, which encompasses customer churn prediction, customer segmentation, and churn factor analysis to enhance business strategies and services. In this system, we leverage customer segmentation techniques for feature construction, which enables the new features to improve the model performance significantly. Our experiments demonstrate that the proposed system outperforms current advanced customer churn prediction methods in the same dataset, with a higher prediction accuracy. The results further demonstrate that this churn analysis system can help telecom companies mine customer value from the features in a dataset, identify the primary factors contributing to customer churn, and propose suitable solution strategies. Findings: Simulation results show that the K-means algorithm gets better results when the original dataset is divided into four groups, so the K value is selected as 4. The XGBoost algorithm achieves 79.3% and 81.05% accuracy on the original dataset and new data with RFM, respectively. Additionally, each cluster has a unique feature importance ranking, allowing for specialized strategies to be provided to each cluster. Overall, our system can help telecom companies implement effective CRM and marketing strategies to reduce customer churn. Recommendations for Practitioners: More accurate churn prediction reduces misjudgment of customer churn. The acquisition of customer churn factors makes the company more convenient to analyze the reasons for churn and formulate relevant conservation strategies. Recommendation for Researchers: The research achieves 81.05% accuracy for customer churn prediction with the Xgboost and RFM algorithms. We believe that more enhancements algorithms can be attempted for data preprocessing for better prediction. Impact on Society: This study proposes a more accurate and competitive customer churn system to help telecom companies conserve the local markets and reduce capital outflows. Future Research: The research is also applicable to other fields, such as education, banking, and so forth. We will make more new attempts based on this system.