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As the subtitle indicates, this book presents a new classical microeconomic framework. It develops a new unifying analytical framework that covers topics concerning international trade, development economics, growth theory, transaction costs economics, comparative economics, management economics, urban economics, industrial organization, and macroeconomics. The new classical microeconomic framework is used to bring the analysis of economies of specialization, the division of labor, and the structure of economic organization into the central place of economics.

Estimations on people movement behaviour within a country can provide valuable information to government strategic resource plannings. In this paper, we propose to utilize multi-domain statistical data to estimate people movements under the assumption that most population tend to move to areas with similar or better living conditions. We design a Multi-domain Matrix Factorization (MdMF) model to discover the underlying consistency patterns from these cross-domain data and estimate the movement trends using the proposed model. This research can provide important theoretical support to government and agencies in strategic resource planning and investments.

Zhao, X orcid:0000-0003-0153-5173 ; Green residential buildings (GRBs) are one of the effective practices of energy saving and emission reduction in the construction industry. However, many real estate developers in China are less willing to develop GRBs, because of the factors affecting green residential building development (GRBD). In order to promote the sustainable development of GRBs in China, this paper, based on the perspective of real estate developers, identifies the influential and critical factors affecting GRBD, using the method of social network analysis (SNA). Firstly, 14 factors affecting GRBD are determined from 64 preliminary factors of three main elements, and the framework is established. Secondly, the relationships between the 14 factors are analyzed by SNA. Finally, four critical factors for GRBD, which are on the local economy development level, development strategy and innovation orientation, developer's acknowledgement and positioning for GRBD, and experience and ability for GRBD, are identified by the social network centrality test. The findings illustrate the key issues that affect the development of GRBs, and provide references for policy making by the government and strategy formulation by real estate developers.

Despite the recent surge in scholarly attention to anti‐Asian racism, what is largely missing in this growing body of literature is a bridge connecting studies on this subject to the broader field of race and ethnicity studies. In this special issue, we propose to use the concept of transculturality, which is defined as the process of cultural interaction, interpenetration, and hybridization that transcends the traditional borders of individual cultures, to establish this connection. In this introductory article, we first critically review the concepts of culture, interculturality, and multiculturality in the studies of race and ethnicity. Upon this review, we explain how transculturality advances the knowledge of racial and ethnic identity, ideas, and practices. This introduction concludes with an overview of each contribution, setting the stage for a comprehensive exploration of this complex and multifaceted issue. Collectively, this special issue aims to not only provide theoretical and empirical insights into the transculturality of anti‐Asian racism but also build a bridge between the studies of the Asian diaspora and the general research on race and ethnicity.

Objective We examine how human operators adjust their trust in automation as a result of their moment-to-moment interaction with automation. Background Most existing studies measured trust by administering questionnaires at the end of an experiment. Only a limited number of studies viewed trust as a dynamic variable that can strengthen or decay over time. Method Seventy-five participants took part in an aided memory recognition task. In the task, participants viewed a series of images and later on performed 40 trials of the recognition task to identify a target image when it was presented with a distractor. In each trial, participants performed the initial recognition by themselves, received a recommendation from an automated decision aid, and performed the final recognition. After each trial, participants reported their trust on a visual analog scale. Results Outcome bias and contrast effect significantly influence human operators' trust adjustments. An automation failure leads to a larger trust decrement if the final outcome is undesirable, and a marginally larger trust decrement if the human operator succeeds the task by him/herself. An automation success engenders a greater trust increment if the human operator fails the task. Additionally, automation failures have a larger effect on trust adjustment than automation successes. Conclusion Human operators adjust their trust in automation as a result of their moment-to-moment interaction with automation. Their trust adjustments are significantly influenced by decision-making heuristics/biases. Application Understanding the trust adjustment process enables accurate prediction of the operators' moment-to-moment trust in automation and informs the design of trust-aware adaptive automation.