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After the “quantity era,” today higher education has entered into the “quality era” and as “the gate keepers of quality,” quality assurance agencies (QAAs) are playing more and more irreplaceable important roles and their social status are becoming more and more prominent. However, how to guarantee the quality of the QAAs? Who can review the QAAs? The purpose of this paper is based exploration of these questions.

Following the founding of the European Quality Assurance Register (EQAR) for Higher Education, the Asia Pacific Quality Register (APQR) became the second in the international quality assurance (QA) networks to implement QA register, in 2015 with initiative of Asia-Pacific Quality Network.

This paper first retrospects the history and process of APQR, and subsequently the implementation of APQR is described in detail from the two aspects of the criteria and the procedure, and at the end, the paper concludes with a summary of the three characteristics of this first formal implement of APQR: APQR is an international register open to all the QAAs; APQR emphasizes characteristics evaluation of diversity; and APQR highlights the combination of quantitative assessment and qualitative assessment.

Today on the international stage of QA, APQR has emerged as “the watchman of quality” in the Asia-Pacific region as counterpart of EQAR in Europe. How far away does such newly emerging form of guaranteeing the QAAs’ quality go forward, what is its future prospects and other concerning issues, are some of the question that need enthusiastic attention and contribution.

The purpose of this paper is to explore the concept of data assets and how companies can assetize their data. Using the literature review methodology, the paper first summarizes the conceptual controversies over data assets in the existing literature. Subsequently, the paper defines the concept of data assets. Finally, keywords from the existing research literature are presented visually and a foundational framework for achieving data assetization is proposed.

This paper uses a systematic literature review approach to discuss the conceptual evolution and strategic imperatives of data assets. To establish a robust research methodology, this paper takes into account two main aspects. First, it conducts a comprehensive review of the existing literature on digital technology and data assets, which enables the derivation of an evolutionary path of data assets and the development of a clear and concise definition of the concept. Second, the paper uses Citespace, a widely used software for literature review, to examine the research framework of enterprise data assetization.

The paper offers pivotal insights into the realm of data assets. It highlights the changing perceptions of data assets with digital progression and addresses debates on data asset categorization, value attributes and ownership. The study introduces a definitive concept of data assets as electronically recorded data resources with real or potential value under legal parameters. Moreover, it delineates strategic imperatives for harnessing data assets, presenting a practical framework that charts the stages of “resource readiness, capacity building, and data application”, guiding businesses in optimizing their data throughout its lifecycle.

This paper comprehensively explores the issue of data assets, clarifying controversial concepts and categorizations and bridging gaps in the existing literature. The paper introduces a clear conceptualization of data assets, bridging the gap between academia and practice. In addition, the study proposes a strategic framework for data assetization. This study not only helps to promote a unified understanding among academics and professionals but also helps businesses to understand the process of data assetization.

This paper discusses the urban management challenges in the Greater Kuala Lumpur area. Before examining Greater Kuala Lumpur's economic and social environment, we will look at the factors that make it a competitive and fiscally sound entity. When considering urban development and redevelopment, we consider how proposed and ongoing projects, as well as plans, hierarchical links, and road networks, contributed to the increase. Because there is no urban growth boundary, land use change and rural encroachment, as well as environmental degradation and the impact of national economic projects on urban expansion, are both rapid and linear in the analysis. This paper also considers how to manage linear development that results in the creation of new suburbs. Finally, we propose strategies for achieving sustainable urban expansion and management by balancing the financial and governance capacities of Greater Kuala Lumpur local governments.

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.

Social networks have changed the communication patterns significantly. Information available from different social networking sites can be well utilized for the analysis of users opinion. Hence, the organizations would benefit through the development of a platform, which can analyze public sentiments in the social media about their products and services to provide a value addition in their business process. Over the last few years, deep learning is very popular in the areas of image classification, speech recognition, etc. However, research on the use of deep learning method in sentiment analysis is limited. It has been observed that in some cases the existing machine learning methods for sentiment analysis fail to extract some implicit aspects and might not be very useful. Therefore, we propose a deep learning approach for aspect extraction from text and analysis of users sentiment corresponding to the aspect. A seven layer deep convolutional neural network (CNN) is used to tag each aspect in the opinionated sentences. We have combined deep learning approach with a set of rule-based approach to improve the performance of aspect extraction method as well as sentiment scoring method. We have also tried to improve the existing rule-based approach of aspect extraction by aspect categorization with a predefined set of aspect categories using clustering method and compared our proposed method with some of the state-of-the-art methods. It has been observed that the overall accuracy of our proposed method is 0.87 while that of the other state-of-the-art methods like modified rule-based method and CNN are 0.75 and 0.80 respectively. The overall accuracy of our proposed method shows an increment of 7–12% from that of the state-of-the-art methods.