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The missing travel time data for roads is a common problem encountered by traffic management departments. Tensor decomposition, as one of the most widely used method for completing missing traffic data, plays a significant role in the intelligent transportation system (ITS). However, existing methods of tensor decomposition focus on the global data structure, resulting in relatively low accuracy in fibrosis missing scenarios. Therefore, this paper aims to propose a novel tensor decomposition model which further considers the local spatiotemporal similarity for fibrosis missing to improve travel time completion accuracy.

The proposed model can aggregate road sections with similar physical attributes by spatial clustering, and then it calculates the temporal association of road sections by the dynamic longest common subsequence. A similarity relationship matrix in the temporal dimension is constructed and incorporated into the tensor completion model, which can enhance the local spatiotemporal relationship of the missing parts of the fibrosis type.

The experiment shows that this method is superior and robust. Compared with other baseline models, this method has the smallest error and maintains good completion results despite high missing rates.

This model has higher accuracy for the fibrosis missing and performs good convergence effects in the case of the high missing rate.

Independent directors are important corporate decision participants and makers. Based on the Chinese cultural background, this paper interprets the listing order of independent directors as independent directors’ status, exploring their influence on the corporate research and development (R&D) behavior.

This paper studies A-share listed firms in China from 2008 to 2018 as the sample. The main method is ordinary least square (OLS) regression. We also use other methods to deal with endogenous problems, such as the firm fixed effect method, change model method, two-stage instrumental variable method, and Heckman two-stage method.

(1) Higher independent directors’ status attribute to more effective exertion of supervision and consultation function, and positively enhance the corporate R&D investment. The increase of the independent director’ status by one standard deviation will increase the R&D investment by 4.6%. (2) The above effect is more influential in firms with stronger traditional culture atmosphere, higher information opacity and higher performance volatility. (3) High-status independent directors promote R&D investment by improving the scientificity of R&D evaluation and reducing information asymmetry. (4) The enhancing effect of independent director’ status on R&D investment is positively associated with the firm’s patent output and market value.

This paper contributes to understanding the relationship between the independent directors’ status and their duty execution from an embedded cultural background perspective. The findings of the study enlighten the improvement of corporate governance efficiency and the healthy development of the capital market.

In confronting the challenge of climate change and progressing towards dual carbon goals, China is actively implementing low-carbon city pilot policy. This paper aims to focus on the potential impact of this policy on enterprise green governance, aiming to promote the reduction and balance of carbon emissions.

Based on the panel data of China's large-scale industrial enterprises from 2007 to 2013, this paper uses the Difference-in-differences (DID) method to study the impact and path mechanism of the implementation of low-carbon city pilot policy on enterprise green governance. Heterogeneity analysis is used to compare the effects of low-carbon city pilot policy in different regions, different enterprises and different industries.

The low-carbon pilot can indeed effectively enhance corporate green governance, a conclusion that still holds after a series of robustness tests. The low-carbon city pilot policy mainly enhances enterprise green governance through two paths: an industrial structure upgrade and enterprise energy consumption, and it improves green governance by reducing enterprise energy consumption through industrial structure upgrade. The impact of low-carbon city pilot policy on enterprise green governance shows significant differences across different regions, different enterprises and different industries.

This paper examines the impact of low-carbon city pilot policy on enterprise green governance. However, due to availability of data, there are still some limitations to be further tackled. The parallel trend test in this paper shows that the pilot policy has a significant positive effect on the green governance of enterprises. However, due to serious lack of data in some years, the authors only selected the enterprise data of a shorter period as our experimental data, which leads the results to still have certain deficiencies. For the verification of the impact mechanism, the conclusions obtained in this paper are relatively limited. Although all the mechanism tests are passed, the reliability of the results still needs to be further tested through future data samples. In addition, as the pilot policy of low-carbon cities is still in progress, the policy can be tracked and analysed in the future as more data are disclosed, and further research can be carried out through dimensional expansion.

Low-carbon city pilot policy plays an important role in inducing the green governance of enterprises. Therefore, policy makers can continue to strengthen the construction of low-carbon city pilots by refining pilot experience, building typical cases, actively promoting pilot policy experience, expanding pilot scope and enhancing the implementation efficiency of pilot policy nationwide, which will contribute to the optimization and upgrading of the regional industrial structure at the urban level and will provide experience and reference for the synergistic implementation plan of pollution reduction and carbon reduction.

The impact of the low-carbon city pilot policy on enterprise green governance not only exists in two separate paths of urban industrial upgrading and enterprise energy consumption but also exists in a chain transmission path from macro to micro. The authors find that the effect value of each influence path is different, and there is an obvious leading influence path for the role of enterprise green governance. Therefore, in the process of implementing a low-carbon city pilot policy, policies should be designed specifically for different mechanisms. Moreover, complementing and coordinating several paths should be advocated to give full play to the green governance effect of enterprises brought by different paths and to further expand the scope of industries and enterprises where policies play a role.

To the best of the authors’ knowledge, for the first time, this paper connects macro mechanisms with micro mechanisms, discovering a macro-to-micro transmission mechanism in the process of low-carbon city pilot policy affecting enterprise green governance. That is, the low-carbon city pilot policy can facilitate industrial structure upgrading, resulting in reduced enterprise energy consumption, ultimately enhancing enterprise green governance.

This study aims to explore the correlation between Management Control Systems, Green Innovation, Social Media Networks, and Company Performance in medium-sized construction and real estate firm in Indonesia.

This research method uses quantitative approach. The sample selection technique uses simple random sampling. The analytical method in this study uses structural equation models based on variance. Statistical test tool used, is Smart PLS 3.0.

The management control systems have a significant and positive impact on social media networks, green innovation, and company performance in the upper-middle-class construction and real estate businesses in Java. Furthermore, social media networks and green innovation were found to mediate the strong relationship between management control systems and firm performance in medium-sized construction and real estate businesses in Java.

This research should provide a detailed, technical, and structured explanation of how companies assess suitability standards for implementing green innovation in Indonesia’s construction and real estate sectors.

The finding emphasize the importance of the management control system in enhancing firm performance. If, the elements of the management control system are met or adequate, it can improve the performance of those in charge, leading to satisfactory performance.

This finding is the first of its kind in Indonesia. It will contribute to shaping future development policies for government and private projects, ensuring they are more advance and environmentally conscious.

The main purpose of this study is to examine the impact of different dimensions of institutional quality indices on the economic growth of Sub-Saharan African (SSA) countries.

The study uses a panel data set of 31 SSA countries from 1991 to 2015 and employs a two-step system-GMM (Generalized Method of Moments) estimation technique.

The study's empirical results indicate that investment-promoting and democratic and regulatory institutions have a significant positive effect on economic growth; however, once these institutions are taken into account, conflict-preventing institutions do not have a significant impact on growth.

The study's findings suggest that countries in the region should continue their institutional reforms to enhance the region's economic growth. Specifically, institutions promoting investment, democracy and regulatory quality are crucial.

Unlike previous studies that use either composite measures of institutions or a single intuitional indicator in isolation, the present study has employed principal component analysis (PCA) to extract fewer institutional indicators from multivariate institutional indices. Thus, this paper provides important insights into the distinct role of different clusters of institutions in economic growth.

The purpose of this research is to discover equipment losses and assess the accomplishment of overall equipment effectiveness (OEE) values.

Industries specialized in die shops often have issues regarding their efficiencies, conferring to statistics further production line department procedure for various machines frequently suffered restrictions owing to excessive downtime and speed losses in machines thus, reducing their effectiveness and efficiency. OEE is a means of determining how effective a piece of equipment is when in working condition. Calculation of OEE finds the heart of the issue and the root cause for the underlying problem.

The dimensional outcomes suggest that the average machine effectiveness has not attained the norm of >85%, but there is still room for progression.

One recommended procedure to reduce losses is to keep the actual pace of operation and downtime of equipment constant. Many such suggestions are provided to reduce the losses.

The purpose of this research is to investigate the short-term capital markets' reactions to the public announcement first local detection of novel corona virus (COVID 19) cases in 12 major Asian capital markets.

Using the constant mean return model and the market model, an event study methodology has been implied to determine the cumulative abnormal returns (CARs) of 10 pre and post-event trading days. The statistical significance of the data was assessed using both parametric and nonparametric test statistics.

First discovery of local COVID 19 cases had a substantial impact on all 12 Asian markets on the event day, as shown by statistically significant negative average abnormal return (AAR) and cumulative average abnormal return (CAAR). The single factor ANOVA result has also demonstrated that there is no variability among 12 regional markets in terms of short-term market responses. Furthermore, there is little evidence that these major Asian stock market indices differ significantly from the FTSE All-World Index which might suggest possible spillover impact and co-integration among the major Asian capital markets. The study further discovers that market capitalization and liquidity did not have any significant impact on market reaction to announcement.

The study's contribution might have been compromised by the absence of socio-demographic, technical, financial and other significant policy factors from the analysis.

These findings will be considerably helpful in tackling this unprecedented epidemic issue for personal and institutional investors, industrial and economic experts, government and policymakers in assessing the market in special circumstances, diversifying risk and developing financial and monetary policy proposals.

This paper is the first to examine the effects of local COVID 19 detection announcement on major Asian capital markets. This study will add to the literature by investigating unusual market returns generated by infectious illness outbreaks and the overall market efficiency and investors' behavioral pattern of major Asian capital markets.

Grounded in self-congruency theory, this study aims to investigate the impact of different types of congruence in social media influencer marketing on consumers’ online impulse buying intentions under the moderating influence of wishful identification.

This study collects survey responses from an online sample of 232 social media users and analyses them using partial least squares structural equation modelling.

This study delineates two distinct pathways influencing online impulse buying intentions within influencer marketing: direct consumer–product congruence and the conditional role of consumer–influencer congruence. Particularly, the alignment between a consumer’s self-image and the product’s attributes independently drives online impulse buying intentions. Conversely, consumer–influencer congruence, despite high alignment, fails to spur online impulse buying intentions unless amplified by wishful identification – the consumer’s aspirational desire to emulate the influencer. This finding underscores the complexity of impulsive consumer behaviours in the digital marketplace, highlighting the pivotal role of product appeal and the conditional influence of influencer relationships on spontaneous purchasing decisions.

This study pioneers by elucidating the congruence interplay between consumers, influencers and products in online impulse buying, emphasising wishful identification as a critical moderating factor. Theoretically, it expands self-congruency theory by detailing the distinct roles of congruence types on impulsive behaviours, notably underlining the essential role of wishful identification for the effect of consumer–influencer congruence. Practically, the insights equip brands with a deeper understanding of the key drivers behind impulsive purchases in an influencer-centric digital marketplace, offering strategic guidance for optimising influencer collaborations and product presentations to enhance consumer engagement and sales.

The principal aim of the research was to develop Interactive Mobile Learning Modules (IMLM) as an approach to innovative teaching practices in online distance education.

The study employed educational action research, using a quasi-experimental design catering to ninth-grade students (N = 104) attending a public high school in Manila.

Our research indicates that IMLM has a positive effect on student engagement. It provides students with a convenient, easily accessible, and engaging means of understanding Genetics concepts. The execution of this initiative has facilitated the emergence of novel ideas, heightened the ease of use, and advanced more equitable opportunities within the education domain. Thus, IMLM’s utilization has resulted in a favorable shift in conceptual understanding. It has been found to support learners' concept test performance, as evidenced by score gains and statistically significant improvement in understanding.

The study is limited with the development and utilization of mlearning strategy to accommodate learners in the public school system in a developing country.

The study addresses ongoing strategy and discussion to enrich online learning through the mlearning strategy.

The study accommodates inclusivity and equitable learning through personalize mlearning strategy.

The study is novel because it utilize mlearning as innovative approach to teaching genetics.

The proliferation of mobile phones with integrated sensors makes large scale sensing possible at low cost. During mobile sensing, data mostly contain sensitive information of users such as their real-time location. When such information are not effectively secured, users’ privacy can be violated due to eavesdropping and information disclosure. In this paper, we demonstrated the possibility of unauthorized access to location information of a user during sensing due to the ineffective security mechanisms in most sensing applications. We analyzed 40 apps downloaded from Google Play Store and results showed a 100% success rate in traffic interception and disclosure of sensitive information of users. As a countermeasure, a security scheme which ensures encryption and authentication of sensed data using Advanced Encryption Standard 256-Galois Counter Mode was proposed. End-to-end security of location and motion data from smartphone sensors are ensured using the proposed security scheme. Security analysis of the proposed scheme showed it to be effective in protecting Android based sensor data against eavesdropping, information disclosure and data modification.