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Information technology changes rapidly, and the market trend flow changes even faster. The information systems (IS) department in a technological oriented environment has to ensure that the plans or solutions made by the IS department can align with organizational strategy to avoid resources waste, and adaptability is a crucial issue for an IS department too. This study believes that adaptability and alignment of the IS department are ambidexterity. The concept of knowledge use effectiveness (KUE), based on the human agency theory, proposed a research model mainly founded on intellectual capital, human agency theory, and contextual ambidexterity, and used intellectual capital (including human, structure and relational capital) as a framework to find the antecedents of knowledge usage.

This study conducts an empirical research method and collects 150 valid cases from the IS department employees in Taiwan.

The results of this study are: (1) KUE in an IS department significantly improves the ambidexterity; (2) intellectual capital has a positive influence on KUE; (3) despite human capital having no influence on iteration, iterational KUE has no influence on adaptability.

For academics, this study has developed KUE through a novel perspective and uses the concept of the human agency to articulate the characteristic of KUE, and thus has combined the intellectual capital, human agency and contextual ambidexterity into a research model. For managers, they should learn that KUE has a positive effect on the IS department ambidexterity, composed of alignment and adaptability. By knowing that, they can understand the concrete elaboration of KUE much better. Therefore, enhancing the process of knowledge usage can be a practical and useful way of improving an IS department performance.

This research aims to explore leadership approaches that foster deeper learning and facilitate the transition from traditional schooling to a model aligned with the demands of the post-industrial digital knowledge society.

Employing a mixed-methods approach, the authors conducted surveys among school principals within a network of schools embracing deeper learning based on ten distinct but interlocking criteria that define this particular model of deeper learning. Through in-depth follow-up interviews with school leaders, the authors investigated the factors and obstacles that support sustainable implementation and scalability of deeper learning, with a specific focus on the role of transformational leadership.

During the implementation of transformative practices like deeper learning, school leaders demonstrate diverse perspectives on the necessary changes for their successful integration. Leaders inclined toward a “transactional” leadership style concentrate on changes within individual classrooms. Conversely, leaders exemplifying “transformational leadership” possess a broader vision and address systemic factors such as teacher collaboration, assessment regulations and the effective utilization of time and space within schools. To achieve widespread adoption of deeper learning across schools and the education system, it is essential to recruit more transformational leaders for formal leadership positions and reorient leadership training toward transformational approaches.

The deeper learning model developed for this intervention encompasses a four-stage process: Teachers initially collaborate in small teams to co-design interdisciplinary, deeper learning units. The actual units consist of three sequences: knowledge acquisition, where students gain knowledge through direct instruction supplemented by personalized learning on digital platforms; team-based co-creative and co-constructive tasks facilitated by teachers once students have acquired a solid knowledge base and the completion of authentic tasks, products or performances in sequence III. While small groups of intrinsically motivated teachers have successfully implemented the model, achieving broader scalability and dissemination across schools requires significant “transformational leadership” to challenge traditional norms regarding teacher collaboration, assessment practices and the efficient use of time and space in schools.

This paper presents a structured model of deeper learning based on ten distinct but interlocking quality criteria tested within a network of 26 schools. The model has demonstrated transformative effects on participating schools, albeit primarily observed in smaller substructures of large secondary schools. Teachers who previously worked independently have begun to collaboratively design learning experiences, resulting in “hybrid” classrooms where physical and digital spaces merge and extend to include maker spaces and out-of-school learning environments. Traditional summative assessments have been replaced by various forms of embedded formative assessment. However, these innovations are currently driven by small groups of intrinsically motivated teachers. The research provides insights into the type of school leadership necessary for comprehensive scaling and system-wide dissemination of deeper learning.

The purpose of this paper is to establish a social-network sp.orts lottery system to support users in predicting and simulating sports lottery betting. The community data were generated to support user decision and featured instant game records and odds data synchronisation. Furthermore, the next development cycle were evaluated through a questionnaire.

An extended prototype website development methodology was applied to develop the system. An online sample was collected to evaluate the function, interface, operation, and prediction designs. The χ2 test and variance analysis were used to determine the association between facets and basic demographics. Finally, the regression model was used to identify the potentially essential predictors that influence the measurement facets.

The high frequency of Facebook users, sports lottery purchases, and sports game viewers prefer the ability to predict the results of future sports games as advanced decision-making functions. However, the agent-based virtual gift presentation function was the least preferred function.

The study sample was limited only to users: who used PTT and Facebook; were of uneven age, education, and gender; and none segment groups. The study sample primarily comprised Taiwanese respondents. These differences might influence the practicality and prediction bias of the designed website and related models.

The proposed method integrates social-network messages with real-time data access by using APIs, crawler schemes, and prediction mechanisms that enable developers to devise strategies for obtaining high system satisfaction. The system can be improved by adding the results of future sports games and excluding authorised Facebook message posts.

A social-network-based sports lottery and prediction prototyping website was evaluated through a user-preference survey regarding design functions. The measurement results indicated that users share their opinions, predictions, and personal betting results and interact with their friends.

The ecosystem concept has attracted attention in information system research to explain business competition, innovation and many other emerging phenomena. Existing studies focus more on a single ecosystem type or a single ecosystem goal and pay little attention to the ecosystem’s evolution. The objective of the study is to investigate the factors that impact the evolution of the information ecosystem (IE) to gain a better understanding of strategic thinking.

The IE involves many actors, so the multi-case study approach is conducted with purposeful sampling to recruit all the significant ecosystem actors. The collected qualitative data are analyzed by coding data, exploring data relationships and structuring pattern steps; institutional theory is used as a theoretical framework.

The results demonstrate that industry practices, laws and regulations, new actors and the mimetic pressure of outsourcers drive the growth of the ecosystem. Strategy intention, cost pressure and normative pressure all contribute to the IE’s evolution.

The concept of ecosystems has attracted attention in information system research. The study investigates the factors contributing to the evolution of the IE from an institutional theory perspective. Our suggestion is that new players can find a niche in offering information technology (IT)/ information services (IS)-related solutions to survive in the ecosystem; however, they need to pay attention to the normative pressure.

The purpose of this paper is to gain a clear understanding of the impact of uncommon use of knowledge (adaptation and augmentation) on the performance of information systems (IS) departments, and to explore the effects of human-resources management (HRM) practices on uncommon use of knowledge.

A questionnaire-based survey was used to measure the constructs of the research model. A survey package was delivered to project managers or team leads and 133 responses were returned.

The empirical results indicate that knowledge adaptation has a significant effect on departmental performance, whereas knowledge augmentation is more important to innovation than to routine departmental performance. The results also show that, while knowledge adaptation can be enhanced by communication and an uncertainty-avoidance culture, knowledge augmentation is an outcome of shared decision-making, the use of teams, and innovation-based policies.

Given the positive impact of uncommon use of knowledge on IS department performance, future research should explore other factors besides HRM practices to boost it.

The results can serve as guidance for managers looking to select HRM practices to promote uncommon use of knowledge.

This study introduces knowledge adaptation and knowledge augmentation as the component processes of uncommon use of knowledge to the IS discipline, and empirically validates the antecedents and consequences of uncommon use of knowledge using survey data.

The purpose of this paper is to integrate psychological dimension, social dimension, and environmental dimension – six internet psychological characteristics (dissociative anonymity, invisibility, asynchronicity, solipsistic introjection, dissociative imagination, and minimization of status and authority), deindividuation, social influence (subjective norm and descriptive norm), and containment theory (inner containment and outer containment) – to propose an innovative model which can make up for deficiencies in previous studies of the toxic online disinhibition effect.

On the basis of 530 valid responses collected from an online survey questionnaire, partial least squares technology was used to examine the research model.

The result shows that dissociative anonymity has a significant impact on deindividuation and toxic disinhibition. In addition, asynchronicity and dissociative imagination have a direct effect on toxic disinhibition. Besides, in social influence, the authors found that subjective norm is a stronger predictor of toxic disinhibition than descriptive norm. Moreover, in containment theory, the result shows that inner containment can effectively reduce toxic disinhibition but not outer containment.

This study can provide academics and practical side empirical evidence as to what factor would cause toxic disinhibition and provides an innovative view regarding the relationship between social influence and containment theory on toxic disinhibition.

This study investigates factors that motivate social media users to retransmit rumors. We focus on everyday rumors rather than catastrophic rumors and develop a model of everyday rumor retransmission based on the uses and gratification theory, the rumor retransmission model, and the basic law of rumor.

An Internet survey is conducted to collect data and test the proposed model. This study’s hypotheses are tested through partial least squares regression analysis.

The results show that socializing, information seeking and status seeking increase the intention to retransmit rumors. Perceived rumor credibility has a moderating effect on the impacts of socializing and status seeking on retransmission intention.

Our research model provides a theoretical foundation for future studies that want to explore motivations or values that determine rumor-sharing intention on social media. The findings can help government agencies and businesses to manage rumor retransmission on social media.

The purpose of this paper is to examine the complex relationships between permeability, work-family conflict, moral disengagement, behavioral disengagement, job strain and job engagement. In addition, this study aims to determine whether moral disengagement acts as a moderator and mediator in the relationship between work-family conflict and behavioral disengagement.

The authors apply partial least squares structural equation modeling to test the hypotheses, using a sample of 176 valid responses.

The results indicate that permeability is likely to promote work-family conflict, which in turn may trigger moral disengagement. Moral disengagement may lead to behavioral disengagement, which in turn may increase job strain and decrease job engagement. The findings also show that work-family conflict does not have a significant effect on behavioral disengagement, suggesting that moral disengagement fully mediates the influence of work-family conflict on behavioral disengagement. In addition, the moderating effect of moral disengagement is not significant.

Applying the transactional model of stress and coping theory and the moral disengagement theory, this study contributes to a better understanding of employees' experience of job strain caused by work-family conflict (induced by permeability of IM usage), as well as the employee's coping response.

The purpose of this paper is threefold. First, this study seeks to provide a framework for, and endeavor to gain, an in‐depth understanding of the decision‐making process in relation to playing or not playing massively multiplayer online role‐playing games (MMORPGs) by using qualitative data from interviewing both players and non‐players. Second, it seeks to establish a better measure and model using an ethnographic decision tree model that describes the decision‐making process of internet users. Finally, for cross‐validity purposes, it aims to verify the model using quantitative data from face‐to‐face surveys of players/non‐players in an online gaming context.

A two‐phase mixed method is adopted here. During the first phase, the decision tree development phase, to capture the concerns of internet users who are facing the choice of playing MMORPGs or not, qualitative‐based procedures are used to identify decision factors and organize them into a decision tree for better understanding a research problem. In the second phase, the decision tree verification phase, to test the predictive capability of the composite model, a quantitative‐based survey instrument, which represents the decision criteria identified in the first phase, is adopted for data collection and analysis.

The results revealed that 14 criteria, formulated as a decision tree, were identified in the model‐building phase. In the model‐testing phase, 137 decision processes were successfully predicted and 17 predictive pathways led to a decision against the factual, giving a predictive rate of 89 per cent.

The study bridges the gap between the research in online games and in decision making. At the theoretical level, the decision tree model can provide a more comprehensive and in‐depth explanation of the online games‐playing phenomenon. In practice, marketers can easily become aware of the user considerations and identify exactly what needs to be done to fulfil users' criteria for playing MMORPGs. And, from a methodological standpoint, a mixed method can help researchers improve techniques used in study for building more predictive models.

The purpose of this paper is to propose a moderated mediation model to explain how corporate social responsibility (CSR) and ethical leadership influence knowledge sharing and job dedication through the mediating mechanism of positive affective tone and cognitive meaningfulness.

The research hypotheses were empirically tested using a survey of employees from the high-tech industry in Taiwan. The research constructs in this study were measured using five-point Likert scales modified from existing literature. The survey data were empirically analyzed with two-step structural equation modeling (SEM) and regression analysis.

The empirical results of this study reveal that CSR and ethical leadership positively relate to positive affective tone and cognitive meaningfulness. Knowledge sharing is positively affected by positive affective tone whereas job dedication is positively affected by positive affective tone and cognitive meaningfulness. While the relationship between positive affective tone and job dedication is positively moderated by job demand, the relationship between cognitive meaningfulness and job dedication is negatively moderated by job demand.

This study elucidates the ethical influences from organizations (i.e. CSR) and leaders (i.e. ethical leadership) respectively to explain affective and cognitive processes involved in work situations. At the same time, by clarifying the moderating role of job demand, this study provides valuable implications for managers to effectively leverage job demand for increasing employees’ job dedication.