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The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

The purpose of this paper is to artificially construct a functional surface with self-propulsion flow characteristics for the directional transportation of propellant in surface tension tanks.

In this study, a method to enhance the propulsion efficiency by using functional surfaces of self-propulsion performance was proposed. Superhydrophilic wedged-groove with the superhydrophobic background was fabricated and the self-propulsion capacity was verified.

It is found that the self-propulsion capacity is related to the divergence angle of the wedged-groove in the hydrophilic area, and the velocity of the droplets on the deflector plate is the largest with the divergence angle of 4°; the temperature gradient field formed by the condensing device at the nozzle can accelerate the droplet outflow from the tank.

Realization of this idea provides an accurate control strategy for the complex flow process of propellant in plate surface tension tanks, which could enhance the efficiency of the tension tank significantly.

Emerging technologies are capable of enhancing organizational- and individual-level outcomes. The organizational behavior (OB) field is beginning to pursue opportunities for researching emerging technologies. This study aims to describe a framework consisting of white, black and grey boxes to demonstrate the tight coupling of phenomena and paradigms in the field and discusses deconstructing OB’s white box to encourage data-driven phenomena to coexist in the spatial framework.

A scoping literature review was conducted to offer a preliminary assessment of technology-oriented research currently occurring in OB.

The literature search revealed two findings. First, the number of published papers on emerging technologies in top management journals has been increasing at a steady pace. Second, various theoretical perspectives at the micro- and macro- organizational level have been used so far for conducting technology-oriented research.

By conducting a scoping review of emerging technologies research in OB literature, this paper reveals a conceptual black box relating to technology-oriented research. The essay advocates for loosening OB’s tightly coupled white box to incorporate emerging technologies both as a phenomenon and as data analytical techniques.

The purpose of this research is to develop a better understanding of the hurdles in implementing Lean Six Sigma (LSS) for operational excellence in digital emerging technology companies.

We have conducted case studies of LSS implementations in six US-based companies in the digital emerging technology industry.

Critical success factors (CSF) for LSS implementations in digital emerging technology companies are: (1) organizational leadership that is engaged to the implementation, (2) LSS methodology that is rebranded to fit existing shared values in the organization, (3) restructuring of the traditional LSS training program to include a more incremental, prioritized, on-the-job training approach and (4) a modified LSS project execution methodology that includes (a) condensing the phases and tools applied in LSS projects and (b) adopting more iterative project management methods compared to the standard phased LSS project approach.

The qualitative nature of our analysis and the geographic coverage of our sample limit the generalizability of our findings.

Implications comprise the awareness and knowledge of critical success factors and LSS methodology modifications specifically relevant for digital emerging technology companies or companies that share similarities in terms of focus on product development, innovation and growth, such as R&D departments in high-tech manufacturing companies.

Research on industry-specific enablers for successful LSS implementation in the digital emerging technology industry is virtually absent. Our research informs practitioners on how to implement LSS in this and alike industries, and points to aspects of such implementations that are worthy of further attention from the academic community.

Family firms (FF) reveal a considerable heterogeneity in their innovation behavior. Due to the successful long-term preservation of their innovation capacity via special resources and routines, multi-generational FF are of special interest in terms of learning from good practices. Against this background, the purpose of this paper is to ascertain principles for successful innovation behavior in long-term successful FF and to contribute to bridging the theory-practice gap.

Results are generated by analyzing innovation and innovation processes in five cases of long-term successful FF. On the basis of these good practice cases, the “rules of the game” of innovating are re-constructed using fine and system analyses based on narrative interviews with the FF CEOs.

Intense reflection on the innovation characteristics of the five good practice cases along with a critical examination of the literature on innovation in FF were used to derive practical suggestions for FF in the form of 11 principles for FF taking a proactive interest in innovation.

The 11 generated principles of successfully innovative FF were validated by FF CEOs who confirmed the practical relevance of these principles as valuable guidelines for successful innovation. Owners and managers may reflect on these principles against the background of the innovation behavior of their firms and adapt them to their contextual conditions.

These principles serve as tangible suggestions for developing adequate innovation management strategies for individual FF. Furthermore, two FF CEOs were invited to comment on the viability of principles based on their comprehensive practical experience.

As a major theoretical breakthrough of the Marxist political economy based on the practice of China’s reform and opening up, the theory of socialist market economy constitutes an important part of the political economy of socialism with Chinese characteristics. The paper aims to discuss this issue.

Its essence is that socialism (as a social system) and market economy (as a resource allocation mechanism) can be organically integrated to exert the advantages of both at the same time and generate new institutional and systematic advantages.

It has condensed many important theoretical viewpoints, involving major theoretical and practical issues, such as the relationship between the government and the market, the basic economic system, the income distribution system, the operation of the market economy and the opening up to the outside world, which have become the basic principles of socialist political economy with Chinese characteristics.

The new practice of comprehensively deepening reform and building a moderately prosperous society in an all-round way is bound to provide an impetus to the deepening and systematization of the theory of socialist market economy.

This study aims to fill the research gap regarding the usability of group reporting information in the central government. It answers the question of how the consolidated information should be formed to benefit the real needs of governmental information users.

The empirical research is based on a survey and interviews among key internal preparers and users in the central government sector in the case country, Finland.

Results show that the private sector approach regarding consolidation is not appropriately transferable to the central government sector. The key stakeholders identified several economic and financial reporting needs that exceed what formal Consolidated Financial Statement (CFS) can offer. Consolidation is needed but not according to the extensive full control approach, but rather following the budgetary approach consolidating units of the legal person of the government, and further using the partial control approach for consolidating by discretion essential special purpose SOEs.

Respondents and interviewees represented governmental internal organisations, free experts, auditors and financial managers from the group entities. Politicians and citizens were not directly represented.

Research gives applicable insights into central governments planning and developing group reporting for information needs in a favourable cost-benefit ratio. Findings benefit the development of EU's EPSAS (European Public Sector Accounting Standards) project which is still incomplete.

Research recommends governments to make a thorough analysis before deciding on a new financial reporting system. A critical analysis prevents governments to waste money and resources on a reporting system not fulfilling the real needs of information users.

The value of this research is that the private sector approach in consolidation was not taken as granted. This study investigated critically and empirically the real need for consolidated information serving steering and overseeing purposes of the government's group entities.