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The purpose of this study is to explore the determinants of teachers’ continuance intention concerning cloud services.

This study uses a cloud service, namely, Google Sites, to support teacher collaboration and further develop a research model to explore the determinants of their continued usage intention.

The findings reveal that continued intention to use the cloud services is primarily determined by their attitude towards using it; attitude towards using is affected by perceived ease of use and perceived usefulness; and perceived ease of use is influenced by facilitating conditions, while perceived usefulness is influenced by social influence.

This study determines that teachers intend to continue using cloud services once training in using such services has been provided and if they hear favourable opinions from others.

The paper enables us to better understand factors affecting teachers' continuance intention toward cloud services.

The purpose of the paper is to note that customers are not necessarily human and to figure out how best to serve artificial intelligence (AI) customers. The authors also propose several major research streams, as examples, to help launch research on AI customers and how to serve them.

The current paper is a conceptual one that draws upon research from many areas to support the ideas proposed.

AI customer are proliferating. AI as customers can augment or replace human customers and can be the customer itself. Service providers may also be AI, which means that both humans serving AI customers and AI serving AI customers are relevant here. The authors show that even truly autonomous AI customers are likely to be more common in the future. The authors conclude that reverse engineering will probably not be successful in understanding AI customers and that an approach similar to how we research human consumer behavior is likely to be more useful.

Virtually, the entire literature on customers and how to serve them assumes that customers are human. With the rapid advancement of AI, purchase decisions are increasingly made by AI, suggesting that it is now important and necessary to consider the possibility of AI customers and how best to serve them. This paper opens the door for such research.

This paper aims to build and empirically test a multilevel framework integrating transaction cost economics and a resource-based view into a value co-creation ecosystem perspective to explain the chain- and firm-level effects of transaction-specific investments (TSIs) on supplier performance.

This paper investigates cross-level network effects using survey data from the List of Taiwanese Central Satellite Production Systems. A total of 34 buyers (hub firms) and 106 suppliers (satellite firms) from 34 supply chains responded to the survey.

Findings confirm that individual firms’ TSIs can foster co-specificity at the supply chain level, thereby improving supply chain integration (SCI). SCI can have a positive cross-level moderating effect on the TSI–performance relationship.

These two key concepts, value co-creation and co-specificity, extend the theoretical application of transaction cost theory and the resource-based view to cross-level study by contributing to the research on the TSI–performance relationship.

This study’s framework is a counter to the buyer–supplier–supplier relationships in which each actor who may have different goals can create value jointly and share benefits from their TSIs.

Owing to high co-specificity, being embedded in a well-integrated supply chain can be a threat when the environment is turbulent; for losing strategic flexibility, co-specificity and embeddedness may result in a collective adaptation concern. High degrees of SCI may slow the reaction to environmental turbulence for both buyers and suppliers.

Individual firms’ TSIs can foster co-specificity at the supply chain level, subsequently enhancing SCI. An integrated supply chain can be a collective asset that facilitates value co-creation. Individual firms can benefit from the sharing of collective value. SCI can also increase switching costs, thus reducing the likelihood of individual firm engaging in opportunistic behavior and cost safeguarding.

Rapid response is often the cornerstone of success in many industries, especially manufacturing. In the authors’ opinion, organizational structure will also affect the construction of a fast-response supply chain system. The main purpose of this research examines whether different levels of organizational structure have different effects on the relationship between external integration and firm performance.

This study applied questionnaires to collect data. This study collected 818 questionnaires from manufacturers in China, Hong Kong and Taiwan to verify our proposed model using structural equation modeling.

Results show that response speed perfectly mediates the relationship between external integration and firm performance. Different levels of organizational structure will also affect external integration. Strict organizational structure requires customer integration, while loose organizational structure requires supplier integration to quickly meet customer needs.

Companies can probably determine whether their organizational structure is higher or lower than that of their competitors. If firms can determine that their organization structure is high or low, they can adopt suitable external integrations to enhance quick response and operational performance.

In the relationship between supply chain integration and performance, we consider a mediating variable and moderating variable together. Results explain the reason that the relationship between supply chain integration and performance are inconsistent in previous studies. We have addressed external integration in alignment with organizational structure to provide better service and enhance performance by providing empirical evidence.

This study aims to investigate whether higher value creation leads to higher value appropriation and to identify the boundary conditions in a buyer–supplier relationship that can explain why a particular supplier can appropriate higher value than others.

The study uses questionnaire surveys. The sample of the survey has 150 publicly-listed supplier firms in Taiwan. The unit of analysis is the buyer–supplier relationship.

In the buyer–supplier relationship, suppliers’ bargaining power, partnership and a supplier’s original brand manufacturing (OBM) business can strengthen the positive relationship between value creation and value appropriation.

This study adopts the unilateral viewpoint of suppliers; however, some constructs might require dyadic evaluation. This study only explores the spillover effect of OBM business on the relationship between value creation and appropriation.

The spillover effect of a supplier’s OBM business in a buyer–supplier relationship allows the buyer to share more common benefits and the supplier to capture more private benefits as compensation. By broadening its customer base, a supplier can increase its bargaining power. A supplier can also maintain a strategic partnership with each essential buyer.

To avoid the dark-side effect of partnership, the model provides the contingency that a supplier can capture more value from a buyer–supplier relationship.

Forecasting population movement trends is crucial for implementing effective policies to regulate labor force growth and understand demographic changes. Combining migration theory expertise and neural network technology can bring a fresh perspective to international migration forecasting research.

This study proposes a conditional generative adversarial neural network model incorporating the migration knowledge – conditional generative adversarial network (MK-CGAN). By using the migration knowledge to design the parameters, MK-CGAN can effectively address the limited data problem, thereby enhancing the accuracy of migration forecasts.

The model was tested by forecasting migration flows between different countries and had good generalizability and validity. The results are robust as the proposed solutions can achieve lesser mean absolute error, mean squared error, root mean square error, mean absolute percentage error and R² values, reaching 0.9855 compared to long short-term memory (LSTM), gated recurrent unit, generative adversarial network (GAN) and the traditional gravity model.

This study is significant because it demonstrates a highly effective technique for predicting international migration using conditional GANs. By incorporating migration knowledge into our models, we can achieve prediction accuracy, gaining valuable insights into the differences between various model characteristics. We used SHapley Additive exPlanations to enhance our understanding of these differences and provide clear and concise explanations for our model predictions. The results demonstrated the theoretical significance and practical value of the MK-CGAN model in predicting international migration.

The purpose of this paper is to understand the formation of knowledge management (KM) decisions, including intention for knowledge contribution and knowledge exploration. The authors build on the goal-directed model and a trust-based lens to develop a belief-trust-decision framework. The authors theorize belief as individual factors (one’s virtual skill) and environmental factors (cooperative norms, familiarity), and trust as emotional trust and cognitive trust. Individual factors represent one’s virtual skill to control knowledge exchange, while environmental factors reflect the level of support/control for this exchange by the context.

This study uses a survey method to collect data and partial least squares to analyze them.

The authors found that KM decision is affected by two types of trust, directly or indirectly. They are, in turn, influenced by individual factors and environmental factors.

Generalizability of the findings to virtual communities with different collaboration protocol deserves further investigation. This study contributes to the research on KM and social behavior by providing a comprehensive explanation on KM decision through one’s goal achievement in knowledge exchange behavior, in terms of trust development. Besides, the authors theorize one’s belief on knowledge exchange as skill-control and context-control to represent the drivers for trust.

The results provide suggestion for managers regarding how skill-control and context-control should be managed to improve trust development, which serves as goal achievement for KM decisions.

The authors extend prior work by yielding a new insight into how and why one’s beliefs on skill-control and context-control for knowledge exchange are transferred into KM decision through one’s goal achievement, characterized as trust development at both emotional and cognitive levels.

This study aims to examine the components and evolution of the Chinese wine festival market using the Dalian International Wine and Dine Festival (DIWDF) as a case study.

Adopting a longitudinal approach, survey data were collected from attendees of the first, fifth and seventh DIWDF in 2012, 2016 and 2018, respectively. Cluster analysis segmented attendees by wine and festival experience and consumption features. Comparative analysis was conducted to examine segment differences by demography, festival motivation, satisfaction and intention. Changes in segments over time were examined across the three times.

The following three clusters were identified: “wine-novice fest-newbies,” “occasional drinker fest-goers” and “wine-lover fest-enthusiasts.” Over the study period, the proportion of “wine-lover fest-enthusiasts” increased significantly while the percentages of the other two segments decreased, demonstrating the evolution of the Chinese wine festival market and their consumer impacts.

This study offers straightforward indicators of market value via consumption features for both wine businesses and festival organizers. The characteristics of the segments and their inter-linkage have important implications for developing product mix, targeting strategies, festival service design and market development.

This is the first known empirical research globally to investigate relationships among market segments both horizontally (differences between segments) and vertically (development over time) and to incorporate both wine- and festival-related consumption features.

In order to make sure of the safety of a long-span suspension bridge under earthquake action, this paper aims to study the traveling wave effect of the bridge under multi-support excitation and optimize the semi-active control schemes based on magneto-rheological (MR) dampers considering reference index as well as economical efficiency.

The finite element model of the long-span suspension bridge is established in MATLAB and ANSYS software, which includes different input currents and semi-active control conditions. Six apparent wave velocities are used to conduct non-linear time history analysis in order to consider the seismic response influence in primary members under traveling wave effect. The parameters α and β, which are key parameters of classical linear optimal control algorithm, are optimized and analyzed taking into account five different combinations to obtain the optimal control scheme.

When the apparent wave velocity is relatively small, the influence on the structural response is oscillatory. Along with the increase of the apparent wave velocity, the structural response is gradually approaching the response under uniform excitation. Semi-active control strategy based on MR dampers not only restrains the top displacement of main towers and relative displacement between towers and girders, but also affects the control effect of internal forces. For classical linear optimal control algorithm, the values of two parameters (α and β) are 100 and 8 × 10–6 considering the optimal control effect and economical efficiency.

The emphasis of this study is the traveling wave effect of the triple-tower suspension bridge under multi-support excitation. Meanwhile, the optimized parameters of semi-active control schemes using MR dampers have been obtained, providing relevant references in improving the seismic performance of three-tower suspension bridge.

This paper highlights cooperation as an important moderating condition of competitive action and response. Drawing on a new perspective of collective identity on competitive dynamics, the purpose of this paper is to stress the impacts of market commonalities and resource similarities on competitive actions and responses and focus on the moderating effect of cooperation on the relationships mentioned above.

This study employs logistic regression analysis to test the hypotheses in the Taiwanese flour industry at the period 2002–2005.

The results indicate market commonalities and resource similarities have a negative effect on the likelihood of a price-competitive action and a price-competitive response. Moreover, the level of cooperation among firms moderates the relationships among market commonalities, resource similarities, price-competitive actions, and price-competitive responses.

To understand and predict competitive behavior help firms to control and avoid unnecessary rivalry and therefore maintain mutual forbearance with competitors.

This study provides a new angle on cooperation-level analysis, contributing the use of collective identity theory to analyze the moderating effects of cooperation on competitive actions and responses.