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Pursuing higher data rate with limited spectral resources is a longstanding topic that has triggered the fast growth of modern wireless communication techniques. However, the massive deployment of active nodes to compensate for propagation loss necessitates high hardware expenditure, energy consumption, and maintenance cost, as well as complicated network interference issues. Intelligent metasurfaces, composed of a number of subwavelength passive or active meta-atoms, have recently found to be a new paradigm to actively reshape wireless communication environment in a green way, distinct from conventional works that passively adapt to the surrounding. In this review, we offer a unified perspective on how intelligent metasurfaces can facilitate wireless communication in three manners: signal relay, signal transmitter, and signal processor. We start by the basic modeling of wireless channel and the evolution of metasurfaces from passive, active to intelligent metasurfaces. Integrated with various deep learning algorithms, intelligent metasurfaces adapt to cater for the ever-changing environments without human intervention. Then, we overview specific experimental advancements using intelligent metasurfaces. We conclude by identifying key issues in the practical implementations of intelligent metasurfaces, and surveying new directions, such as gain metasurfaces and knowledge migration. This article offers a unified perspective on how intelligent metasurfaces facilitate wireless communication in the ways of signal relay, transmitter, and processor.

We examine social movements that arise from tensions between countries. From a neo-institutional view, we posit that social movements targeting another country generate powerful pressures on firms doing business with the targeted country. Although informal and non-governmental, these pressures may coerce firms into curtailing their business activities with the targeted country. Empirically, we analyzed the 2012 anti-Japanese social movement in China using a panel dataset of Chinese-listed firms from 2006 to 2017. Through a quasi-experimental design and difference-in-difference method, we found that this social movement was associated with a significant reduction in Chinese firms’ import from Japan, as well as export and FDI activities. Furthermore, we found that animosity against the targeted country and firms’ network connectivity exacerbated this effect, while firms’ political capital weakened it. We also found that the impact of this social movement existed for four years after the movement subsided. We contribute by showing that social movements have significant impacts on firms’ international business activities. Firms need to pay attention to informal pressures from social movements, and proactively adapt their cross-border business activities. In today’s digital era, opinions and sentiments can quickly snowball into massive collective forces in the virtual and actual worlds.

Taking a strategic fit perspective, we investigate the relationships between task environment (environmental dynamism), institutional environment (state ownership and institutional development), and innovation strategy (cooperative strategy) in the context of China. Using a longitudinal data set of Chinese manufacturing firms from 2012 to 2017, we confirm that environmental dynamism positively drives firms’ decisions to cooperate for innovation. This driving effect is stronger for state-owned firms and firms located in regions with limited developed institutions. Overall, no one-size-fits-all innovation strategy exists, and the appropriateness of a strategy depends on the coalignment of a series of external and internal factors. The theoretical and practical implications of this finding are explored.

Diversity literature has demonstrated negative effects of surface-level diversity and positive effects of deep-level diversity. How do two types of diversity among cross national team members influence team knowledge sharing and team creativity? The purpose of this study is to explore conditions that leverage the positive and restrain the negative effects of team diversity on team knowledge sharing, which leads to team creativity. We expect inclusive climate as the significant condition and knowledge sharing as the profound intervening mechanism between team diversity and team creativity relationship. We tested the hypotheses with data from a sample of 60 cross-national research teams from several universities in China. The results support the hypothesized relationships among inclusive climate, team knowledge sharing, and team creativity. Our findings contribute to the advancement of team diversity and team creativity literature, and their theoretical and practical implications are discussed.

The original version of this article unfortunately contained a mistake. The spelling of the co-author name Wenjia Guo was incorrect. The original article has been corrected.

Obtaining a full view and complete information of the surrounding dynamics is of great significance for a plethora of applications in sensing, imaging, navigation, and orientation. However, conventional spatial spectrum methods heavily rely on a priori knowledge with a trial‐and‐error solution fashion, leading to a great challenge to estimate complete information in volatile scenarios. Inspired by the mechanism of the jumping spider (Salticidae), here a universal detection approach driven by an intelligent antenna array, with the usage of amplitude‐only information as inputs, is introduced. The applied machine learning method can process the received time‐varying signals in one single feed‐forward computation, bypassing a heavy recline on prior knowledge of the array structure. As a demonstration, a compact eight‐port antenna array is designed for simultaneous attainments of frequency, direction of arrival, and polarization, covering the entire microwave X band. Both the simulated and experimental results show that the average accuracies for the azimuth angle, elevation angle, and polarization are up to 98%, with a millisecond detection time. Different from conventional methods, the strategy herein does not involve a complex beamforming network and a time‐consuming trial‐and‐error solution fashion, allowing a big step toward a miniaturized, integrated, and cost‐effective detector. Herein, inspired by the jumping spider, a universal detection approach is introduced for dynamically perceiving multiple parameters of incoming waves. The key to its success is the machine learning model that allows real‐time prediction of the multi‐parameters in one single forward calculation. Experiment results show that the overall accuracy of the detector is up to 89% in the X band.

How do independent innovations impact firm performance? Based upon exploratory learning perspective, we argue that independent innovations will exhibit a double-edged sword effect on firm performance over time. Further, we view cooperation with foreign partners as complementary assets, and examine the dynamical moderating effect of such complementary assets on the relationship between independent innovations and firm performance. By analyzing a sample of Chinese firms, we find that independent innovations can enhance long term firm performance, but dampen short term firm performance. Further, our results show that cooperating with foreign partners as complementary assets will improve the relationship between independent innovations and firm short term performance.

To study how firm networks function in different cultures, we employ meta-analysis methods to examine the impacts of tightness-looseness and individualist-collectivist cultures on the links between network centrality/structural holes and competitive advantage. Based on a sample from 74 studies encompassing 30,930 samples, we find that network centrality has a stronger positive impact on competitive advantage than structural holes. In addition, the findings indicate that the positive impacts of both network centrality and structural holes on competitive advantage are higher in loose cultures than in tight cultures. We also find that the positive impacts of both network centrality and structural holes on competitive advantage are higher in individualist cultures than in collectivist cultures.

This paper shows a novel scheme for direction-of-arrival (DOA) estimation of narrowband signals. In the scheme, the 1-bit measurement is used to reduce the system cost. A recovery compressed sensing (CS)-based algorithm with multiple measurement vector (MMV) is proposed to make up the information loss. The purposed MMV-OMP algorithm provides a new idea which make the compress sensing framework applicable directly to an MMV model. The effectiveness of the proposed approach is assessed through numerical simulations under different environment configurations. Comparisons with other methods are reported as well.

Acts of financial misconduct in business affect firms in many negative ways. Therefore, why do certain misdemeanants repeatedly commit these acts? We suggest that financial misdemeanants with different social networks will perceive the costs and benefits of committing financial frauds differently, thereby affecting the likelihood of committing financial frauds in the future. To be specific, we suggest that politically connected misdemeanants are less likely to recommit financial frauds, while misdemeanants at interlock network center are more likely to recommit financial frauds. In addition, we propose that misdemeanants are less likely to recommit financial frauds when their partners in the interlock network community are punished for financial frauds. To test our theory, we collected panel data from Chinese listed firms from 2005 to 2014 and employed event history analysis (EHA). 财务违规一旦被发现会给企业带来很多消极影响。那么，为什么有些企业会重复违规呢？本研究认为，违规企业的社会网络会影响违规企业对再次违规所面临的成本收益的判断，进而影响其重复违规的可能。具体而言，我们认为有政治关系的违规企业重复违规的可能性较低，而处在董事连锁网络中心位置的违规企业更有可能重复违规。此外，当违规企业所处的董事连锁网络小群体的伙伴因财务违规受过惩罚时，该企业重复违规的可能性会降低。运用事件分析方法（EHA），我们对2005年到2014年中国上市公司财务违规面板数据进行了分析，验证了本文的理论和假设。 Финансовые нарушения в бизнесе оказывают негативное влияние на компании. В таком случае, почему определенные нарушители постоянно совершают эти проступки? Мы предполагаем, что финансовые правонарушители с различными социальными связями будут по-разному воспринимать преимущества и недостатки, связанные с финансовыми махинациями, что влияет на вероятность совершения финансовых нарушений в будущем. Прежде всего, мы считаем, что нарушители с политическими связями реже совершают финансовые проступки, в то время как нарушители, которые находятся в центре сети социальных отношений, с большей вероятностью повторно совершают финансовые мошенничества. Кроме того, мы предполагаем, что нарушители с меньшей вероятностью вновь совершают финансовые махинации в том случае, если их партнеры в сети социальных отношений получают наказание за финансовые проступки. Для того, чтобы проверить нашу теорию, мы собрали панельные данные из китайских компаний, зарегистрированных на фондовой бирже в период с 2005 по 2014 годов, и провели исторический анализ событий. Los actos de malversación financiera en los negocios afectan las empresas de muchas maneras negativas. Por lo tanto, ¿por qué ciertos delincuentes de delitos menores cometen repetidamente estos actos? Sugerimos que los delitos financieros menores con diferentes redes sociales percibirán de manera diferente los costos y los beneficios de cometer fraudes financieros, por ende, afectando la probabilidad de cometer fraudes financieros en el futuro. Para ser específicos, sugerimos que los delincuentes de delitos menores menos políticamente conectados son menos propensos a volver a comer fraudes financieros. Además, proponemos que los delincuentes de delitos menores son menos propensos a volver a cometer fraudes financieros cuando sus aliados en la red comunitaria entrelazada son castigados por fraudes financieros. Para probar nuestra teoría, recolectamos datos de panel de empresas chinas que cotizan en bolsa entre el 2005 al 2015 y usamos análisis histórico de eventos.