Aim/Purpose: The aim of this study is to examine empirically the effects of certain key Critical Success Factors (CSFs) for the implementation of Enterprise Resource Planning (ERP) Systems on the comprehensive achievement of the crucial roles of Computer-Based Information Systems (CBISs) Background: The effects of the CSFSs were examined in the higher education sector in the Kingdom of Saudi Arabia (KSA) using a case study of the ERP adoption in Prince Sattam Bin Abdulaziz University. Methodology: A theoretical model was proposed based on the literature written on the CSFs and the roles of CBISs in business. The model encompasses six key CSFs and their associations with the realization of the crucial roles of CBISs. To test the proposed model, a questionnaire was developed by considering the most frequently used measurements items in the ERP’s literature. The data were collect-ed from 219 key stakeholders. Contribution: This study acts as one of the few empirical studies in assessing the effects of the important CSFs for ERP implementation upon its successful implementation. Its outcomes provide more insights and clarifications about the effects of six key CSFs on the comprehensive achievement of the crucial CBIS’s roles. Particularly, the uniqueness of this study lies in addressing the effects of these CSFs on the achievement of the vital CBIS’s roles collectively rather than the achievement of each role individually. Moreover, the study examined these effects in the higher education environment, which is characterized by its own special business processes and services. Findings: The results reveal that the six key CSFs have a positive relationship with the comprehensive achievement of the crucial roles of CBISs. These findings are consistent with many previous studies on the effects of the CSFs on the realization of the expected benefits of the enterprise systems. Recommendations for Practitioners: The managers and other key stakeholders should carefully manage the vital aspects of the CSFs in order to realize the promised ERP’s benefits, including the CBIS’s roles. Future Research: Additional empirical examinations are needed to investigate the effects of the rest of the CSFs on realizing the roles of information systems.

Aim/Purpose: This study aims to identify the main factors influencing consumers’ adoption of social commerce (s-commerce). Based on the socio-technical theory, the study suggests a research model that investigates the key social and technical factors driving consumers’ decision to purchase from social commerce websites. In addition, the research model explores the interactive relationship among these factors. Background: The phenomenon of social commerce (s-commerce) has emerged due to the increased penetration of social media and the rapid development of Web 2.0 technologies. Electronic commerce (e-commerce) companies have made significant efforts to shift their operations to s-commerce. Therefore, to facilitate their efforts to transform, various research has been conducted to investigate the main factor influencing the adoption of s-commerce. Most of these studies have emphasised the social aspects related to s-commerce design features to understand how the use of advanced web technologies influence how customers interact with each other in s-commerce environments. However, s-commerce is viewed as a socio-technical system that requires the investigation of both social and technical factors to help in the design of effective s-commerce platforms. Methodology: To validate the proposed research model, 418 paper-based and online questionnaires were collected from online shoppers in Jordan. The Structure Equation Modelling (SEM) approach was used to test the proposed hypotheses. Contribution: This study offers a research model that serves as a theoretical framework for investigating customers’ behaviour in s-commerce environment. It represents a strong context-specific model that includes both the technical and social facilitators of s-commerce. The research model participates in gaining an improved understanding of how customers’ intention, actual purchase and post-purchase experience are formed in the s-commerce environment. Findings: The results of Structure Equation Modelling (SEM) reveal that s-commerce constructs, familiarity and user experience have a positive influence on the perceived usefulness and perceived ease of use of s-commerce. In addition, perceptions of its usefulness and ease of use have a positive influence on trust, which in turn influences the purchase intention and the actual purchase. Finally, the post-purchase experience significantly influences both trust and purchase intention. Recommendations for Practitioners: This study shows that social commerce constructs strengthen customers’ perceptions of usefulness. S-commerce service providers are required to provide their customers with various channels to seek social support. Both familiarity and user experience are key enablers of customers’ perceived ease of use. S-commerce service providers consider the variation in customers’ familiarity and experience with s-commerce websites because this has a significant influence on purchase intentions and behaviour. Consequently, system designers should offer useful and sufficient information and tutorials that effectively guide customers in their searching, decision-making and purchasing activities throughout the shopping process. S-commerce service providers should understand the importance of providing secure payment systems and make their privacy policies clear to customers. Post-purchase experience has an influential role in reinforcing customers’ trust and purchase intention. The findings confirm the important role of post-purchase experience in retaining customers by improving their trust and repurchase intention. Therefore, making a customer’s post-purchase experience pleasant should be a key priority for s-commerce service providers because it has a significant influence on customers’ trust and repurchase intentions. Recommendation for Researchers: This study offers a unidimensional conceptualisation of the design features of s-commerce. These features include three main forms: recommendations and referrals, communities and forums, and reviews and ratings. Such conceptualisation provides additional insights and an understanding of the activities of information sharing in s-commerce. The significance of the technical side of s-commerce is highlighted and empirical proof is provided that social interactions guided by social technologies enhance customers’ perceived usefulness of an s-commerce website, thus increasing their trust and intention to purchase which leads to an actual purchase. This offers insights into the various types of s-commerce characteristics that contribute to facilitating customers’ purchase behaviour on s-commerce websites. Impact on Society: The findings offer insights which have important implications for research and practice to help facilitate the adoption of s-commerce. Future Research: This study considered the s-commerce websites as a homogenous online environment. Additional research could collect data from diverse online communities, such as professional groups, to provide a comprehensive understanding of how a wider variety of user behaviour is affected. Second, this was a quantitative study based on data collected in a questionnaire. Further studies may consider using qualitative or mixed methodologies (i.e. focus groups and interviews) to explore other technical and social factors that influence the use of s-commerce.

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

Aim/Purpose: This study 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: 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: 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: This paper presents a study of Virtual Communities of Practice (VCoP) evaluation methods that aims to identify their current status and impact on knowledge sharing. The purposes of the study are as follows: (i) to identify trends and research gaps in VCoP evaluation methods; and, (ii) to assist researchers to position new research activities in this domain. Background: VCoP have become a popular knowledge sharing mechanism for both individuals and organizations. Their evaluation process is complex; however, it is recognized as an essential means to provide evidences of community effectiveness. Moreover, VCoP have introduced additional features to face to face Communities of Practice (CoP) that need to be taken into account in evaluation processes, such as geographical dispersion. The fact that VCoP rely on Information and Communication Technologies (ICT) to execute their practices as well as storing artifacts virtually makes more consistent data analysis possible; thus, the evaluation process can apply automatic data gathering and analysis. Methodology: A systematic mapping study, based on five research questions, was carried out in order to analyze existing studies about VCoP evaluation methods and frameworks. The mapping included searching five research databases resulting in the selection of 1,417 papers over which a formal analysis process was applied. This process led to the preliminary selection of 39 primary studies for complete reading. After reading them, we select 28 relevant primary studies from which data was extracted and synthesized to answer the proposed research questions. Contribution: The authors of the primary studies analyzed along this systematic mapping propose a set of methods and strategies for evaluating VCoP, such as frameworks, processes and maturity models. Our main contribution is the identification of some research gaps present in the body of studies, in order to stimulate projects that can improve VCoP evaluation methods and support its important role in social learning. Findings: The systematic mapping led to the conclusion that most of the approaches for VCoP evaluation do not consider the combination of data structured and unstructured metrics. In addition, there is a lack of guidelines to support community operators’ actions based on evaluation metrics.

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 impact of knowledge management on firm innovativeness of multinational enterprises (MNEs) via the mediating role of innovative culture in Malaysia. Background: Inadequate management practices and growing competition among MNEs operating in developing nations, notably in Malaysia, have hindered their organizational success. Although several studies have shown that knowledge management has a substantial impact on MNEs’ success, it is not apparent if innovation at the company level has a direct impact on their performance. Thus, there is no definitive evidence between knowledge management with business innovativeness and organizational success. 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 select 296 respondents from Malaysia-dependent MNEs of different industries. One of the advantages of this study methodology is that the sample targeted many fields. Afterward, SPSS AMOS 24.0 software package analysis was performed to test the hypotheses. Contribution: The study contributes to knowledge management and firm innovativeness literature through advancing innovative culture as a mediating factor that accounts for the link between these two constructs, especially from an emerging economy perspective. The research findings also offer managerial implications for organizations in their quest to improve firm innovativeness. Findings: The results support that innovative culture significantly affects MNEs’ performance. Innovative culture enhances the capability of MNEs to be innovative that finally leads to the superior performance of firm innovativeness. Recommendations for Practitioners: According to this research, companies that exhibit an innovative culture, the acquisition of new information, the conversion of tacit knowledge into explicit knowledge, the application of knowledge, and the safeguarding of knowledge, all have a positive effect on their innovativeness. This means that for organizations to run an innovative MNE in Malaysia, a creative culture must be fostered since the current study has shown how it is seen as a catalyst that facilitates learning, transformation, and implementation of relevant knowledge. Recommendation for Researchers: Future studies should be carried out in other sectors aside from the manufacturing sector using the same scales used to measure knowledge management. Furthermore, a comparative analysis of knowledge management and firm innovativeness using innovative culture as a mediator should be researched in other developing economies. Impact on Society: While the main aim of this study was to better understand how and why MNEs operate the way they do, it had an indirect impact on the business and political tactics taken by CEOs and managers working in MNEs in developing countries, as this research has shown. Future Research: Future research should employ the methodology presented in this study and pursue this in other sectors, such as emerging and developed nations’ major businesses, to validate the results and further generalize the conclusions. Other methods should also be incorporated to investigate the other dimensions of MNEs’ performance, including market orientation, technology orientation, and entrepreneurial orientation.

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

Aim/Purpose: 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: 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: 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: 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: 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: 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: In this study, we aim to investigate the impact of an important characteristic of textual reviews – the diversity of the review content on review helpfulness. Background: Consumer-generated reviews are an essential format of online Word-of-Month that help customers reduce uncertainty and information asymmetry. However, not all reviews are equally helpful as reflected by the varying number of helpfulness votes received by reviews. From consumers’ perspective, what kind of content is more effective and useful for making purchase decisions is unclear. Methodology: We use a data set consisting of consumer reviews for laptop products on Amazon from 2014 to 2018. A topic modeling technique is implemented to unveil the hidden topics embedded in the reviews. Based on the extracted topics, we compute the text diversity score of each review. The diversity score measures how diverse the content in a review is compared to other reviews. Contribution: In the literature, studies have examined various factors that can influence review helpfulness. However, studies that emphasized the information value of textual reviews are limited. Our study contributes to the extant literature of online word-of-mouth by establishing the connection between the diversity of the review content and consumer perceived helpfulness. Findings: Empirical results show that text diversity plays an important role in consumers’ evaluation of whether the review is helpful. Reviews that contain more diverse content tend to be more helpful to consumers. Moreover, we find a negative interaction effect between text diversity and the text depth. This result suggests that text depth and text diversity have a substitution effect. When a review contains more in-depth content, the impact of text diversity is weakened. Recommendations for Practitioners: For consumers to quickly find the informative reviews, platforms should incorporate measures such as text diversity in the ranking algorithms to rank consumer reviews. Future Research: Future study can extend the current research by examine the impact of text diversity for experienced goods and compare the results with search goods.

Aim/Purpose: The aim of this paper is to examine the influences of KM-centred strategies on innovation capability among Malaysian R&D firms. It also deepens understanding of the pathways and conditions to improve the innovation capability by assessing the mediating role of both KM practices, i.e., knowledge exploration practices, and knowledge exploitation practices. Background: Knowledge is the main organisational resource that is able to generate a competitive advantage through innovation. It is a critical success driver for both knowledge exploration and exploitation for firms to achieve sustainable competitive advantages. Methodology: A total of 320 questionnaires were disseminated to Malaysian R&D firms and the response rate was 47 percent. The paper utilised structural equation modelling and cross-sectional design to test hypotheses in the proposed research model. Contribution: This paper provides useful information and valuable initiatives in exploring the mediating role of knowledge exploration and knowledge exploitation in influencing innovation in Malaysian R&D firms. It helps R&D firms to frame their KM activities to drive the capability of creating and retaining a greater value onto their core business competencies. Findings: The findings indicate that all three KM-centred strategies (leadership, HR practices, and culture) have a direct effect on innovation. In addition, KM exploration practices mediate HR practices on innovation while KM exploitation mediates both leadership and HR practices on innovation. Recommendations for Practitioners: This paper serves as a guide for R&D managers to determine the gaps and appropriate actions to collectively achieve the desired R&D results and national innovation. It helps R&D firms frame their KM activities to enhance the capability of creating and retaining a greater value to their core business competencies. Recommendation for Researchers: This paper contributes significantly to knowledge management and innovation research by establishing new associations among KM-centred strategies, i.e., leadership, HR practices, and culture, both KM practices (knowledge exploration and knowledge exploitation), and innovation. Impact on Society: This paper highlights the important role of knowledge leaders and the practice of effective HR practices to help R&D firms to create a positive environment that facilitates both knowledge exploration and knowledge exploitation in enhancing innovation capabilities. Future Research: Further research could use a longitudinal sample to examine relationships of causality, offering a more comprehensive view of the effect of KM factors on innovation over the long term. Future research should also try to incorporate information from new external sources, such as customers or suppliers.

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.

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

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

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

Aim/Purpose: This study utilized a comprehensive framework to investigate the adoption of Business Analytics (BA) and its effects on performance in commercial banks in Jordan. The framework integrated the Technological-Organizational-Environmental (TOE) model, the Diffusion of Innovation (DOI) theory, and the Resource-Based View (RBV). Background: The recent trend of utilizing data for business operations and decision-making has positively impacted organizations. Business analytics (BA) is a leading technique that generates valuable insights from data. It has gained considerable attention from scholars and practitioners across various industries. However, guidance is lacking for organizations to implement BA effectively specific to their business contexts. This research aims to evaluate factors influencing BA adoption by Jordanian commercial banks and examine how its implementation impacts bank performance. The goal is to provide needed empirical evidence surrounding BA adoption and outcomes in the Jordanian banking sector. Methodology: The study gathered empirical data by conducting an online questionnaire survey with senior and middle managers from 13 commercial banks in Jordan. The participants were purposefully selected, and the questionnaire was designed based on relevant and well-established literature. A total of 307 valid questionnaires were collected and considered for data analysis. Contribution: This study makes a dual contribution to the BA domain. Firstly, it introduces a research model that comprehensively examines the factors that influence the adoption of BA. The proposed model integrates the TOE framework, DOI theory, and RBV theory. Combining these frameworks allows for a comprehensive examination of BA adoption in the banking industry. By analyzing the technological, organizational, and environmental factors through the TOE framework, understanding the diffusion process through the DOI theory, and assessing the role of resources and capabilities through the RBV theory, researchers and practitioners can better understand the complex dynamics involved. This integrated approach enables a more nuanced assessment of the factors that shape BA adoption and its subsequent impact on business performance within the banking industry. Secondly, it uncovers the effects of BA adoption on business performance. These noteworthy findings stem from a rigorous analysis of primary data collected from commercial banks in Jordan. By presenting a holistic model and delving into the implications for business performance, this research offers valuable insights to researchers and practitioners alike in the field of BA. Findings: The findings revealed that various technological (data quality, complexity, compatibility, relative advantage), organizational (top management support, organizational readiness), and environmental (external support) factors are crucial in shaping the decision to adopt BA. Furthermore, the study findings demonstrated a positive relationship between BA adoption and performance outcomes in Jordanian commercial banks. Recommendations for Practitioners: The findings suggest that Jordanian commercial banks should enforce data quality practices, provide clear standards, invest in data quality tools and technologies, and conduct regular data audits. Top management support is crucial for fostering a data-driven decision-making culture. Organizational readiness involves having the necessary resources and skilled personnel, as well as promoting continuous learning and improvement. Highlighting the benefits of BA helps overcome resistance to technological innovation and encourages adoption by demonstrating improved decision-making processes and operational efficiency. Furthermore, external support is crucial for banks to adopt Business Analytics (BA). Banks should partner with experienced vendors to gain expertise and incorporate best practices. Vendors also provide training and technical support to overcome technological barriers. Compatibility is essential for optimal performance, requiring managers to modify workflows and IT infrastructure. Complexity, including data, organizational, and technical complexities, is a major obstacle to BA adoption. Banks should take a holistic approach, focusing on people, processes, and technology, and prioritize data quality and governance. Building a skilled team, fostering a data-driven culture, and investing in technology and infrastructure are essential. Recommendation for Researchers: The integration of the TOE framework, the DOI theory, and the RBV theory can prove to be a powerful approach for comprehensively analyzing the various factors that influence BA adoption within the dynamic banking industry. Furthermore, this combined framework enables us to gain deeper insights into the subsequent impact of BA adoption on overall business performance. Impact on Society: Examining the factors influencing BA adoption in the banking industry and its subsequent impact on business performance can have wide-ranging societal implications. It can promote data-driven decision-making, enhance customer experiences, strengthen fraud detection, foster financial inclusion, contribute to economic growth, and trigger discussions on ethical considerations. Future Research: To further advance future research, there are several avenues to consider. One option is to broaden the scope by including a larger sample size, allowing for a more comprehensive analysis. Another possibility is to investigate the impact of BA adoption on various performance indicators beyond the ones already examined. Additionally, incorporating qualitative research methods would provide a more holistic understanding of the organizational dynamics and challenges associated with the adoption of BA in Jordanian commercial banks.

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

Aim/Purpose: This study aims to evaluate the success of ERP post-implementation and the factors that affect the overall success of the ERP system by integrating the Task Technology Fit (TTF) model into the Information System Success Model (ISSM). Background: Not all ERP implementations provide the expected benefits, as post-implementation challenges can include inflexible ERP systems and ongoing costs. Therefore, it is necessary to evaluate the success after ERP implementation, and this research integrates the Task Technology Fit (TTF) model into the Information System Success Model (ISSM). Methodology: For data analysis and the proposed model, the authors used SmartPLS 3 by applying the PLS-SEM test and one-tailed bootstrapping. The researchers distributed questionnaires online to 115 ERP users at a construction company in Indonesia and successfully got responses from 95 ERP users. Contribution: The results obtained will be helpful and essential for future researchers and Information System practitioners – considering the high failure rate in the use of ERP in a company, as well as the inability of organizations and companies to exploit the benefits and potential that ERP can provide fully. Findings: The results show that Perceived Usefulness, User Satisfaction, and Task-Technology Fit positively affect the Organizational Impact of ERP implementation. Recommendations for Practitioners: The findings can help policymakers and CEOs of businesses in Indonesia’s construction sector create better business strategies and use limited resources more effectively and efficiently to provide a considerably higher probability of ERP deployment. The findings of this study were also beneficial for ERP vendors and consultants. The construction of the industry has specific characteristics that ERP vendors should consider. Construction is a highly fragmented sector, with specialized segments demanding specialist technologies. Several projects also influence it. They can use them to identify and establish several alternative strategies to deal with challenges and obstacles that can arise during the installation of ERP in a firm. Vendors and consultants can supply solutions, architecture, or customization support by the standard operating criteria, implement the ERP system and train critical users. The ERP system vendors and consultants can also collaborate with experts from the construction sector to develop customized alternatives for construction companies. That would be the most outstanding solution for implementing ERP in this industry. Recommendation for Researchers: Future researchers can use this combined model to study ERP post-implementation success on organizational impact with ERP systems in other company information systems fields, especially the construction sector. Future integration of different models can be used to improve the proposed model. Integration with models that assess the level of Information System acceptance, such as Technology Acceptance Model 3 (TAM3) or Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), can be used in future research to deepen the exploration of factors that influence ERP post-implementation success in an organization. Impact on Society: This study can guide companies, particularly in the construction sector, to maintain ERP performance, conduct training for new users, and regularly survey user satisfaction to ensure the ERP system’s reliability, security, and performance are maintained and measurable. Future Research: It is increasing the sample size with a larger population at other loci (private and state-owned) that use ERP to see the factors influencing ERP post-implementation success and using mixed methods to produce a better understanding. With varied modes, it is possible to get better results by adding unique factors to the research, and future integration of other models can be used to improve the proposed model.

Aim/Purpose: The UAE and other Middle Eastern countries suffer from various cybersecurity vulnerabilities that are widespread and go undetected. Still, many UAE government organizations rely on human-centric approaches to combat the growing cybersecurity threats. These approaches are ineffective due to the rapid increase in the amount of data in cyberspace, hence necessitating the employment of intelligent technologies such as AI cybersecurity systems. In this regard, this study investigates factors influencing users’ intention to adopt AI-based cybersecurity systems in the UAE. Background: Even though UAE is ranked among the top countries in embracing emerging technologies such as digital identity, robotic process automation (RPA), intelligent automation, and blockchain technologies, among others, it has experienced sluggish adoption of AI cybersecurity systems. This selectiveness in adopting technology begs the question of what factors could make the UAE embrace or accept new technologies, including AI-based cybersecurity systems. One of the probable reasons for the slow adoption and use of AI in cybersecurity systems in UAE organizations is the employee’s perception and attitudes towards such intelligent technologies. Methodology: The study utilized a quantitative approach whereby web-based questionnaires were used to collect data from 370 participants working in UAE government organizations considering or intending to adopt AI-based cybersecurity systems. The data was analyzed using the PLS-SEM approach. Contribution: The study is based on the Protection Motivation Theory (PMT) framework, widely used in information security research. However, it extends this model by including two more variables, job insecurity and resistance to change, to enhance its predictive/exploratory power. Thus, this research improves PMT and contributes to the body of knowledge on technology acceptance, especially in intelligent cybersecurity technology. Findings: This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. All the hypotheses were accepted. The relationship between the six constructs (perceived vulnerability (PV), perceived severity (PS), perceived response efficacy (PRE), perceived self-efficacy (PSE), job insecurity (JI), and resistance to change (RC)) and the intention to adopt AI cybersecurity systems in the UAE was found to be statistically significant. This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. Recommendations for Practitioners: All practitioners must be able to take steps and strategies that focus on factors that have a significant impact on increasing usage intentions. PSE and PRE were found to be positively related to the intention to adopt AI-based cybersecurity systems, suggesting the need for practitioners to focus on them. The government can enact legislation that emphasizes the simplicity and awareness of the benefits of cybersecurity systems in organizations. Recommendation for Researchers: Further research is needed to include other variables such as facilitating conditions, AI knowledge, social influence, and effort efficacy as well as other frameworks such as UTAUT, to better explain individuals’ behavioral intentions to use cybersecurity systems in the UAE. Impact on Society: This study can help all stakeholders understand what factors can increase users’ interest in investing in the applications that are embedded with security. As a result, they have an impact on economic recovery following the COVID-19 pandemic. Future Research: Future research is expected to investigate additional factors that can influence individuals’ behavioral intention to use cybersecurity systems such as facilitating conditions, AI knowledge, social influence, effort efficacy, as well other variables from UTAUT. International research across nations is also required to build a larger sample size to examine the behavior of users.

Aim/Purpose: This study investigates the relationship between dual network embedding, dual entrepreneurial bricolage, and knowledge-creation performance. Background: The importance of new ventures for innovation and economic growth has been fully endorsed. Establishing incubation organizations to help new startups overcome constraints and dilemmas has become the consensus of various countries. In particular, the number of Chinese makerspaces has rapidly increased. Startups in the makerspaces form a loosely coupled dual network to cooperate and share resources, especially knowledge. Methodology: By convenience sampling, 400 startups in the makerspaces in Fujian Province, China were selected for the questionnaire survey study. In total, 307 valid responses were collected, yielding a response rate of 76.8%. The survey data were analyzed for hypothesis testing, using the PL-SEM technique with the AMOS20.0 software. Contribution: At the theoretical level, this research supplements the exploration of the influencing factors of the entrepreneurial bricolage of startups at the network level. It deepens the research on the internal mechanism of the dual network embeddedness affecting the knowledge-creation performance. In practice, it provides a theoretical basis and management inspiration for startups in makerspaces to overcome the inherent disadvantage of being too small and weak to explore innovative paths. Findings: First, relational embedding of startups in makerspaces directly affects knowledge-creation performance. Second, dual entrepreneurial bricolage plays a mediating role in diversity. Selective entrepreneurial bricolage plays a partial mediating role between relationship embedding and knowledge-creation performance. Parallel entrepreneurial bricolage plays a complete intermediary role between structural embedding and knowledge-creation performance. Dual entrepreneurial bricolage plays a complete intermediary role between knowledge embedding and knowledge-creation performance. Recommendations for Practitioners: Enterprises in the makerspaces should make dynamic adjustments to the network embedded state and dual entrepreneurial bricolage to improve knowledge-creation performance. When startups conduct selective entrepreneurship bricolage, they should strengthen relational and knowledge embeddedness to improve their relationship strength and tacit knowledge acquisition. When startups conduct parallel entrepreneurship bricolage, structural and knowledge embedding should be strengthened to improve the position of enterprises in the network to acquire diversified knowledge to explore and discover new business opportunities and project resources. Recommendation for Researchers: The heterogeneity of industries and regions may impact the dual network embedding mechanism of startups. Researchers can choose a wider range of regions and industries for sampling. Impact on Society: This study provides a theoretical basis and management inspiration for startups to overcome the inherent disadvantage of being too small and weak to explore innovative paths. It provides a basis to support startups in unleashing innovation vitality and achieving healthy growth. Future Research: Previous studies have shown that network relationships and bricolage behavior have a certain relationship with the enterprise life cycle. Future research can adopt a longitudinal research design across time points, which will increase the explanatory power of research conclusions.

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

Aim/Purpose: This paper aims to empirically quantify the financial distress caused by the COVID-19 pandemic on companies listed on Amman Stock Exchange (ASE). The paper also aims to identify the most important predictors of financial distress pre- and mid-pandemic. Background: The COVID-19 pandemic has had a huge toll, not only on human lives but also on many businesses. This provided the impetus to assess the impact of the pandemic on the financial status of Jordanian companies. Methodology: The initial sample comprised 165 companies, which was cleansed and reduced to 84 companies as per data availability. Financial data pertaining to the 84 companies were collected over a two-year period, 2019 and 2020, to empirically quantify the impact of the pandemic on companies in the dataset. Two approaches were employed. The first approach involved using Multiple Discriminant Analysis (MDA) based on Altman’s (1968) model to obtain the Z-score of each company over the investigation period. The second approach involved developing models using Artificial Neural Networks (ANNs) with 15 standard financial ratios to find out the most important variables in predicting financial distress and create an accurate Financial Distress Prediction (FDP) model. Contribution: This research contributes by providing a better understanding of how financial distress predictors perform during dynamic and risky times. The research confirmed that in spite of the negative impact of COVID-19 on the financial health of companies, the main predictors of financial distress remained relatively steadfast. This indicates that standard financial distress predictors can be regarded as being impervious to extraneous financial and/or health calamities. Findings: Results using MDA indicated that more than 63% of companies in the dataset have a lower Z-score in 2020 when compared to 2019. There was also an 8% increase in distressed companies in 2020, and around 6% of companies came to be no longer healthy. As for the models built using ANNs, results show that the most important variable in predicting financial distress is the Return on Capital. The predictive accuracy for the 2019 and 2020 models measured using the area under the Receiver Operating Characteristic (ROC) graph was 87.5% and 97.6%, respectively. Recommendations for Practitioners: Decision makers and top management are encouraged to focus on the identified highly liquid ratios to make thoughtful decisions and initiate preemptive actions to avoid organizational failure. Recommendation for Researchers: This research can be considered a stepping stone to investigating the impact of COVID-19 on the financial status of companies. Researchers are recommended to replicate the methods used in this research across various business sectors to understand the financial dynamics of companies during uncertain times. Impact on Society: Stakeholders in Jordanian-listed companies should concentrate on the list of most important predictors of financial distress as presented in this study. Future Research: Future research may focus on expanding the scope of this study by including other geographical locations to check for the generalisability of the results. Future research may also include post-COVID-19 data to check for changes in results.

Aim/Purpose: Given the increasingly important role of knowledge and human resources for firms in developing and emerging countries to pursue innovation, this paper aims to study and explore the potential intermediating roles of knowledge donation and collection in linking high-involvement human resource management (HRM) practice and innovation capability. The paper also explores possible moderators of market turbulence in fostering the influences of knowledge-sharing (KS) behaviors on innovation competence in terms of incremental and radical innovation. Background: The fitness of HRM practice is critical for organizations to foster knowledge capital and internal resources for improving innovation and sustaining competitive advantage. Methodology: The study sample is 309 respondents and Structural Equation Model (SEM) was used for the analysis of the data obtained through a questionnaire survey with the aid of AMOS version 22. Contribution: This paper increases the understanding of the precursor role of high-involvement HRM practices, intermediating mechanism of KS activities, and the regulating influence of market turbulence in predicting and fostering innovation capability, thereby pushing forward the theory of HRM and innovation management. Findings: The empirical findings support the proposed hypotheses relating to the intermediating role of KS in the HRM practices-innovation relationship. It spotlights the crucial character of market turbulence in driving the domination of knowledge-sharing behaviors on incremental innovation. Recommendations for Practitioners: The proposed research model can be applied by leaders and directors to foster their organizational innovation competence. Recommendation for Researchers: Researchers are recommended to explore the influence of different models of HRM practices on innovation to identify the most effective pathway leading to innovation for firms in developing and emerging nations. Impact on Society: This paper provides valuable initiatives for firms in developing and emerging markets on how to leverage the strategic and internal resources of an organization for enhancing innovation. Future Research: Future studies should investigate the influence of HRM practices and knowledge resources to promote frugal innovation models for dealing with resource scarcity.

Aim/Purpose: Using the Agile Adoption Framework (AAF), this study aims to examine the agile potential of software development companies in Nepal based on their agile maturity level. In addition, this study also examines the impact of various basic agile practices in determining the maturity level of the agile processes being implemented in the software industry of Nepal. Background: Even if most organizations in the software sector utilize agile development strategies, it is essential to evaluate their performance. Nepal’s software industry did not adopt agile techniques till 2014. The Nepalese industry must always adapt to new developments and discover ways to make software development more efficient and beneficial. The population of the study consists of 1,500 and 2,000 employees of software companies in Nepal implementing agile techniques. Methodology: The sample size considered was 150 employees working in software companies in Nepal. However, only 106 respondents responded after three follow-ups. The sample was collected with purposive sampling. A questionnaire was developed to gain information on Customer Adaptive, Customer Collaboration, Continuous Delivery, Human Centric, and Technical Excellence related to agile practices along with the Agile Maturity Level. Contribution: This research contributes to the understanding of agile practices adopted in software companies in developing countries like Nepal. It also reveals the determinants of the agility of software companies in developing countries. Findings: The results suggest that some of the basic principles of agile have a very significant role in Agile Maturity Level in the Nepali context. In the context of Nepal, human-centered practices have a very high level of correlation, which plays a vital role as a major predictor of the agile maturity level. In addition, Technical Excellence is the variable that has the highest level of association with the Agile Maturity Level, making it the most significant predictor of this quality. Recommendations for Practitioners: As Nepali software companies are mostly offshore or serve outsourcing companies, there is a very thin probability of Nepali developers being able to interact with actual clients and this might be one of the reasons for the Nepali industry not relying on Customer Adaptation and Collaboration as major factors of the Agile methodologies. Continuous Delivery, on the other hand, has a significant degree of correlation with Agile Maturity Level. Human-centric practices have a very high level of correlation as well as being a major predictor in determining the Agile Maturity Level in the context of Nepal. Technical Excellence is the most significant predictor and the variable which has the highest level of correlation with Agile Maturity Level. Practitioners should mainly focus on technical excellence as well as human-centric practices to achieve a higher level of Agile Maturity. Recommendation for Researchers: There has not been any such research in the Nepali context that anyone could rely on, to deep dive into their organizational concerns regarding agile strategies and plans. Researchers will need to focus on a more statistical approach with data-driven solutions to the issues related to people and processes. Researchers will need to cover freelancers as well as academics to get a different perspective on what can be the better practices to achieve a higher level of agile maturity. Impact on Society: This study on Agile work is accessible not only to the software industry but also to the general public. The Agile technique has had a huge impact on society’s project management. It has revolutionized how teams approach project planning, development, and execution. The paper’s findings will further information regarding the Agile methodology, which emphasizes collaboration and communication, fosters teamwork and higher quality work, and promotes the exchange of knowledge, ideas, and the pursuit of common goals. Future Research: Owing to the limitations of this study, it is necessary to analyze agile practices in the Nepalese software sector using additional factors that influence agile maturity. The conclusion that years of agile experience do not serve as a balancing factor for both agile practices and the Agile Maturity Level requires additional research. Whether a software outsourcing firm or not, the organization type had no bearing on the degree of maturity of agile methods; this leaves space for further research.

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

Aim/Purpose: The rise of modern artificial intelligence (AI), in particular, machine learning (ML), has provided new opportunities and directions for knowledge management (KM). A central question for the future of KM is whether it will be dominated by an automation strategy that replaces knowledge work or whether it will support a knowledge-enablement strategy that enhances knowledge work and uplifts knowledge workers. This paper addresses this question by re-examining and updating a critical argument against KM by the sociologist of science Steve Fuller (2002), who held that KM was extractive and exploitative from its origins. Background: This paper re-examines Fuller’s argument in light of current developments in artificial intelligence and knowledge management technologies. It reviews Fuller’s arguments in its original context wherein expert systems and knowledge engineering were influential paradigms in KM, and it then considers how the arguments put forward are given new life in light of current developments in AI and efforts to incorporate AI in the KM technical stack. The paper shows that conceptions of tacit knowledge play a key role in answering the question of whether an automating or enabling strategy will dominate. It shows that a better understanding of tacit knowledge, as reflected in more recent literature, supports an enabling vision. Methodology: The paper uses a conceptual analysis methodology grounded in epistemology and knowledge studies. It reviews a set of historically important works in the field of knowledge management and identifies and analyzes their core concepts and conceptual structure. Contribution: The paper shows that KM has had a faulty conception of tacit knowledge from its origins and that this conception lends credibility to an extractive vision supportive of replacement automation strategies. The paper then shows that recent scholarship on tacit knowledge and related forms of reasoning, in particular, abduction, provide a more theoretically robust conception of tacit knowledge that supports the centrality of human knowledge and knowledge workers against replacement automation strategies. The paper provides new insights into tacit knowledge and human reasoning vis-à-vis knowledge work. It lays the foundation for KM as a field with an independent, ethically defensible approach to technology-based business strategies that can leverage AI without becoming a merely supporting field for AI. Findings: Fuller’s argument is forceful when updated with examples from current AI technologies such as deep learning (DL) (e.g., image recognition algorithms) and large language models (LLMs) such as ChatGPT. Fuller’s view that KM presupposed a specific epistemology in which knowledge can be extracted into embodied (computerized) but disembedded (decontextualized) information applies to current forms of AI, such as machine learning, as much as it does to expert systems. Fuller’s concept of expertise is narrower than necessary for the context of KM but can be expanded to other forms of knowledge work. His account of the social dynamics of expertise as professionalism can be expanded as well and fits more plausibly in corporate contexts. The concept of tacit knowledge that has dominated the KM literature from its origins is overly simplistic and outdated. As such, it supports an extractive view of KM. More recent scholarship on tacit knowledge shows it is a complex and variegated concept. In particular, current work on tacit knowledge is developing a more theoretically robust and detailed conception of human knowledge that shows its centrality in organizations as a driver of innovation and higher-order thinking. These new understandings of tacit knowledge support a non-extractive, human enabling view of KM in relation to AI. Recommendations for Practitioners: Practitioners can use the findings of the paper to consider ways to implement KM technologies in ways that do not neglect the importance of tacit knowledge in automation projects (which neglect often leads to failure). They should also consider how to enhance and fully leverage tacit knowledge through AI technologies and augment human knowledge. Recommendation for Researchers: Researchers can use these findings as a conceptual framework in research concerning the impact of AI on knowledge work. In particular, the distinction between replacement and enabling technologies, and the analysis of tacit knowledge as a structural concept, can be used to categorize and analyze AI technologies relative to KM research objectives. Impact on Society: The potential of AI on employment in the knowledge economy is a major issue in the ethics of AI literature and is widely recognized in the popular press as one of the pressing societal risks created by AI and specific types such as generative AI. This paper shows that KM, as a field of research and practice, does not need to and should not add to the risks created by automation-replacement strategies. Rather, KM has the conceptual resources to pursue a (human) knowledge enablement approach that can stand as a viable alternative to the automation-replacement vision. Future Research: The findings of the paper suggest a number of research trajectories. They include: Further study of tacit knowledge and its underlying cognitive mechanisms and structures in relation to knowledge work and KM objectives. Research into different types of knowledge work and knowledge processes and the role that tacit and explicit knowledge play. Research into the relation between KM and automation in terms of KM’s history and current technical developments. Research into how AI arguments knowledge works and how KM can provide an enabling framework.

Aim/Purpose: This conceptual review analyzes the designs of global health virtual communities of practice (VCoPs) programming reported in the empirical literature and proposes a new typology of their functioning. The purpose of this review is to provide clarity on VCoP learning stages of (co)evolution and insight into VCoP (re)development efforts to best meet member, organization, and network needs against an ever-evolving landscape of complexity in global health. Background: Since the COVID-19 pandemic, the field of global health has seen an uptick in the use of VCoPs to support continuous learning and improve health outcomes. However, evidence of how different combinations of programmatic designs impact opportunities for learning and development is lacking, and how VCoPs evolve as learning networks has yet to be explored. Methodology: Following an extensive search for literature in six databases, thematic analysis was conducted on 13 articles meeting the inclusion criteria. This led to the development and discussion of a new typology of VCoP phases of learning (co)evolution. Contribution: Knowledge gained from this review and the new categorization of VCoPs can support the functioning and evaluation of global health training programs. It can also provide a foundation for future research on how VCoPs influence the culture of learning organizations and networks. Findings: Synthesis of findings resulted in the categorization of global health VCoPs into five stages (slightly evolving, somewhat revolving, moderately revolving, highly revolving, and coevolving) across four design domains (network development, general member engagement before/after sessions, general member engagement during sessions, and session leadership). All global health VCoPs reviewed showed signs of adaptation and recommended future evolution. Recommendations for Practitioners: VCoP practitioners should pay close attention to how the structured flexibility of partnerships, design, and relationship development/accountability may promote or hinder VcoP’s continued evolution. Practitioners should shift perspective from short to mid- and long-term VCoP planning. Recommendation for Researchers: The new typology can stimulate further research to strengthen the clarity of language and findings related to VCoP functioning. Impact on Society: VCoPs are utilized by academic institutions, the private sector, non-profit organizations, the government, and other entities to fill gaps in adult learning at scale. The contextual implementation of findings from this study may impact VCoP design and drive improvements in opportunities for learning, global health, and well-being. Future Research: Moving forward, future research could explore how VCoP evaluations relate to different stages of learning, consider evaluation stages across the totality of VCoP programming design, and explore how best to capture VCoP (long-term) impact attributed to health outcomes and the culture of learning organizations and networks.

Aim/Purpose: This study aims to investigate the influence of e-government public services on public trust at the local government level, addressing the pressing need to understand the factors shaping citizen perceptions and trust in government institutions. Background: With the proliferation of e-government initiatives worldwide, governments are increasingly turning to digital solutions to enhance public service delivery and promote transparency. However, despite the potential benefits, there remains a gap in understanding how these initiatives impact public trust in government institutions, particularly at the local level. This study seeks to address this gap by examining the relationship between e-government service quality, individual perceptions, and public trust, providing valuable insights into the complexities of citizen-government interactions in the digital age. Methodology: Employing a quantitative approach, this study utilises surveys distributed to users of e-government services in one of the regencies in Indonesia. The sample consists of 278 individuals. Data analysis is conducted using Partial Least Squares Structural Equation Modelling, allowing for the exploration of relationships among variables and their influence on public trust. Contribution: This study provides insights into the factors influencing public trust in e-government services at the local government level, offering a nuanced understanding of the relationship between service quality, individual perceptions, and public trust. Findings: This study emphasises information quality and service quality in e-government-based public services as crucial determinants of individual perception in rural areas. Interestingly, system quality in e-government services has no influence on individual perception. In the individual perception, perceived security and privacy emerge as the strongest antecedent of public trust, highlighting the need to guarantee secure and private services for citizens in rural areas. These findings emphasise the importance of prioritising high-quality information, excellent service delivery, and robust security measures to foster and sustain public trust in e-government services. Recommendations for Practitioners: Practitioners must prioritise enhancing the quality of e-government services due to their significant impact on individual perception, leading to higher public trust. Government agencies must ensure reliability, responsiveness, and the effective fulfilment of user needs. Additionally, upholding high standards of information quality in e-government services by delivering accurate, relevant, and timely information remains crucial. Strengthening security measures through robust protocols such as data encryption and secure authentication becomes essential for protecting user data. With that in mind, the authors believe that public trust in government would escalate. Recommendation for Researchers: Researchers could investigate the relation between system quality in e-government services and individual perception in different rural settings. Longitudinal studies could also elucidate how evolving service quality, information quality, and security measures impact user satisfaction and trust over time. Comparative studies across regions or countries can reveal cultural and contextual differences in individual perceptions, identifying both universal principles and region-specific strategies for e-government platforms. Analysing user behaviour and preferences across various demographic groups can inform targeted interventions. Furthermore, examining the potential of emerging technologies such as blockchain or artificial intelligence in enhancing e-government service delivery, security, and user engagement remains an interesting topic. Impact on Society: This study’s findings have significant implications for fostering public trust in government institutions, ultimately strengthening democracy and citizen-government relations. By understanding how e-government initiatives influence public trust, policymakers can make informed decisions to improve service delivery, enhance citizen engagement, and promote transparency, thus contributing to more resilient and accountable governance structures. Future Research: Future research could opt for longitudinal studies to evaluate the long-term effects of enhancements in service quality, information quality, and security. Cross-cultural investigations can uncover universal principles and contextual differences in user experiences, supporting global e-government strategies in rural areas. Future research could also improve the research model by adding more variables, such as risk aversion or fear of job loss, to gauge individual perceptions.

Aim/Purpose: This paper investigates the user acceptability of blockchain technology in the healthcare sector, with a specific focus on healthcare professionals in Jordan. Background: The study seeks to identify the factors that affect healthcare professionals’ use and acceptance of blockchain technology in Jordan. Methodology: The study’s research framework integrates factors from the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). A questionnaire was distributed to collect data from 372 healthcare professionals in Jordan, and the results were analyzed using structural equation modeling based on the Partial Least Square (PLS) technique. Contribution: While only a few previous studies have explored blockchain technology acceptance in the healthcare sector using either the TAM or the UTAUT, this study uniquely integrates elements from both models, offering a novel approach that provides a comprehensive understanding of the factors that influence the acceptance of blockchain technology among healthcare professionals in Jordan. The findings can assist decision-makers in developing strategies to enhance the adoption rate of blockchain technology in the Jordanian healthcare sector. Findings: The study revealed that usability, convenience, privacy and security, cost, and trust significantly impact the perceived usefulness of blockchain technology. The findings also suggest that healthcare professionals are more likely to have a positive attitude towards blockchain-based healthcare systems if they perceive them as useful and easy to use. Attitude, social influence, and facilitating conditions were found to significantly impact behavioral intention to use. Recommendations for Practitioners: Stakeholders should focus on developing blockchain-based healthcare systems that are easy to use, convenient, efficient, and effort-free. Recommendation for Researchers: Researchers may compare the acceptance of blockchain technology in the healthcare sector with other industries to identify industry-specific factors that may influence adoption. This comparative analysis can contribute to a broader understanding of technology acceptance. Impact on Society: Successful adoption of blockchain technology in the healthcare sector can lead to improved efficiency, enhanced protection of healthcare data, and reduced administrative burdens. This, in turn, can positively impact patient care and lead to cost savings, which contributes to more sustainable and accessible healthcare services. Future Research: Future research may explore integrating blockchain technology with other emerging technologies, such as artificial intelligence and sidechain, to create more comprehensive and innovative healthcare solutions.

Aim/Purpose: This study aims to identify the characteristics of YouTube video reviews that consumers utilize to evaluate review helpfulness and explores how they process such information. This study aims to investigate the effect of argument quality, review popularity, number of likes, and source credibility on consumers’ perception of YouTube’s video review helpfulness. Background: Video reviews posted on YouTube are an emerging form of online reviews, which have the potential to be more helpful than textual reviews due to their visual and audible cues that deliver more vivid information about product features and specifications. With the availability of an enormous number of video reviews with unpredictable quality, it becomes challenging for consumers to find helpful reviews without consuming significant time and effort. In addition, YouTube does not provide a specific feature that indicates a review helpfulness similar to the one found on e-commerce websites. Consequently, consumers have to examine the characteristics of video reviews that are readily available on YouTube, evaluate them, and form a perception of whether a review is helpful or not. Despite the increasing popularity of YouTube’s video reviews, video reviews’ helpfulness received inadequate attention in the literature. The antecedents of the helpfulness of online video reviews are still underinvestigated, and more research is needed to identify the characteristics that consumers depend upon to assess video review helpfulness. Furthermore, it is important to understand how consumers process the information they gain from these characteristics to form a perception of their helpfulness. Methodology: Following an extended investigation of the relevant literature, we identified four key video characteristics that consumers presumably utilize to evaluate review helpfulness on YouTube (i.e., review popularity, number of likes, source credibility, and argument quality). By employing the Elaboration Likelihood Model (ELM), we classified these characteristics along the central and peripheral routes. The central route characteristics require a high cognitive effort by consumers to process the review’s message and reach a logical decision. In contrast, the peripheral route assumes that consumers judge the review’s message based on superficial qualities without substantial cognitive effort. A research model is introduced to investigate the effect of central and peripheral cues and their corresponding video review characteristics on review helpfulness. Accordingly, argument quality is proposed in the central route of the model, while review popularity, number of likes, and source credibility are proposed in the peripheral route. Furthermore, the study investigates how consumers process the information they obtain from these routes jointly or independently. To empirically test the proposed model, a convenient sample of 361 YouTube users was obtained through an online survey. The partial least squares method was used to investigate the effect of the proposed characteristics on video review helpfulness. Contribution: This study contributes to the literature in several ways. First, it is one of the few studies that investigate online video reviews’ helpfulness. Second, this study identifies several unique characteristics of YouTube’s video reviews that span peripheral and central routes, which potentially contribute to review helpfulness. Third, this study proposes a conceptual model based on the ELM to explore the effect of central and peripheral cues and their corresponding review characteristics on review helpfulness. Fourth, the research findings provide implications for research and practice that advance the theoretical understanding of video reviews’ helpfulness and serve as guidelines to create more helpful video reviews by better understanding the consumer’s cognitive processes. Findings: The results show that among the four characteristics proposed in the research model, argument quality in the central route is the strongest determinant factor affecting video review helpfulness. Results also show that review popularity, source credibility, and the number of likes in the peripheral route have significant effects on video review helpfulness. Altogether, our results show that the effect of the peripheral route adds up to 0.463 compared to 0.430, which is the impact magnitude of the argument quality construct in the central route. Based on the comparable effect magnitude of the central and peripheral routes of the model on video review helpfulness, our results indicate that both peripheral and central cues significantly affect consumers’ perception of video review helpfulness. The two routes are not mutually exclusive, and their cues can be processed in parallel or consecutive ways. Recommendations for Practitioners: The study recommends creating a dedicated category for reviews on YouTube with a specific feature for consumers to indicate the helpfulness of a video review, similar to the helpful vote button in textual reviews. The study also recommends that reviewers deliver more appealing and convincing argument quality, work toward improving their credibility, and understand the factors that contribute to video popularity. Impact on Society: Identifying the characteristics that affect video review helpfulness on YouTube helps consumers access helpful reviews more efficiently and improves their purchase decisions. Future Research: Future research could look into different types of data that could be extracted from YouTube to investigate the helpfulness of online video reviews. Future studies could employ machine learning and sentiment analysis techniques to reach more insights. Future research could also investigate the effect of product types in the context of online video reviews.

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

Breast cancer is leading cause of mortality among women compared to other types of cancers. Hence, early breast cancer diagnosis is crucial to the success of treatment. Various pathological and imaging tests are available for the diagnosis of breast cancer. However, it may introduce errors during detection and interpretation, leading to false-negative and false-positive results due to lack of pre-processing of it. To overcome this issue, we proposed a effective image pre-processing technique-based on Otsu's thresholding and single-seeded region growing (SSRG) to remove artefacts and segment the pectoral muscle from breast mammograms. To validate the proposed method, a publicly available MIAS dataset was utilised. The experimental finding showed that proposed technique improved 18% breast cancer detection accuracy compared to existing methods. The proposed methodology works efficiently for artefact removal and pectoral segmentation at different shapes and nonlinear patterns.

Epidemiologists recommended contact-tracing as an effective control measure for the global infection like COVID-19 pandemic. Despite its effectiveness in infection containment, it has many limitations such as labour-intensive process, prone to human errors and most importantly, user privacy concerns. To address these shortcomings, we proposed location-aware blockchain-based hierarchical contact-tracing framework for anonymised data collection and processing. This infectious disease control framework serves both the infected users with localised alerts as well as stakeholders such as city officials and health workers with health statistics. Our proposed solution uses hierarchical network design that offloads individual infection block data to create hospital and city-level 'chains' for generating macro-level infection statistics. Results demonstrate that our system can represent the dynamic complexities of contract tracing in highly infection situations. Overall, our design emphasises on data processing and verification mechanism for large volume of infection data over a significant period of time for active risk assessment.

Recently, interest in the correlation between 'contract' in transaction governance and 'trust' in relational governance mechanisms has been growing. This study focuses on issues related to the evolution of contract and inter-organisational trust dynamics in transaction governance and uses mixed research method to investigate sectors related to transaction governance in Taiwan's electronics industry. The study finds higher flexibility in contract implementation to be a promoter of trust between two parties in a relationship, thereby promoting project execution efficiency in the case of Taiwanese firms. Organisational management differs between the East and West; therefore, Western firms should understand how various contractual provisions can be used to accommodate different transactions when cooperating with Taiwanese electronics companies.

The emergence of service ecosystems can accelerate the industrial renewal required because of urgent global challenges. However, existing research has not sufficiently grasped the social dynamics of coevolution in ecosystems that enhance industrial renewal. This study aimed to advance ecosystem research through a practice lens and to present the key characteristics of industrial service ecosystem practice involved in industrial renewal. Consequently, its three characteristics - <i>accomplishment</i>, <i>attractiveness</i> and <i>actionability</i> - were configured based on an abductive study derived from the ecosystem literature, three practice-oriented approaches to learning, and two case ecosystem examinations. These features created the logic for resource integration and enhanced ecosystems to evolve as units, thus exceeding the actors' independent avenues of renewal. The findings of this study provided a deeper understanding of the coevolution in ecosystems needed to accelerate industrial renewal as well as a novel conceptualisation of an <i>ecosystem-as-practice</i> for further studies.

This study aims to identify and understand the perspectives of automotive aftersales stakeholders regarding current challenges posed by decarbonisation strategies. It examines potential responses that the automotive aftersales business could undertake to address these challenges. Semi-structured interviews were undertaken with automotive industry experts from Europe and Latin America. This paper focuses primarily on impacts of decarbonisation upon automotive aftersales and the potential role of data in that business. Results show that investment in technology will be a condition for businesses that want to remain active in the industry. Furthermore, experts agree that incumbent manufacturers are not filling the technology gap that the energy transition is creating in the automotive sector, a consequence of which will be the entrance of new players from other sectors. The current aftersales businesses will potentially lose bargaining control. Moreover, policy makers are seen as unreliable leaders of the transition agenda.