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Damage detection of frame structures is important for guaranteeing the safety of people’s lives and property. Sensitivity analysis is an effective method for damage identification. The purpose of this paper is to conduct a sensitivity analysis of beam–column joint rotation angles for frame structures with limited flexural stiffness beams.

First, based on the D-value method and the assumption of inflection points, statically indeterminate frames were transformed to statically determinate structures, and the expressions of beam–column joint rotation angles were derived. Next, the sensitivity coefficients of beam–column joint rotation angles were obtained by taking the derivative of the expressions of beam–column joint rotation angles with respect to the linear stiffness of column. Finally, the expressions of the sensitivity coefficients were verified by a numerical example.

The analytical solutions of the sensitivity coefficients are in good agreement with finite element results. The results show that the beam–column joint rotation angles of damaged column decrease and those of intact columns within the same story increase when damage occurs.

In this study, the sensitivity coefficients of beam–column joint rotation angles with respect to the linear stiffnesses of columns were derived for frame structures. Based on the result of the sensitivity analysis, the relationship between the changes of beam–column joint rotation angles and damaged columns is revealed. The findings provide an important base to further detect damage of frame structures.

The way to measure the value of an enterprise’s R&D investments remains elusive for theoretical and empirical study on innovation economics. The paper aims to discuss this issue.

This paper expands the asset-value model pioneered by Griliches (1981) and applies it for the first time to the Chinese stock market to calculate the value of R&D investment instilled by Chinese manufacturing listed companies (CMLCs) from 2003 to 2014.

The authors find that: the assets-value model can better explain the enterprise value composition of CMLCs; with equal input, the value of R&D is higher than that of tangible assets, and lower than that of organizational assets; compared with the developed countries, the R&D value of CMLCs is lower; and the R&D value of CMLCs saw a downward trend from 2007 to 2014.

Furthermore, by rationally estimating the value of organizational assets and non-tradable shares, and innovatively introducing semi-annual momentum indicators from the perspective of behavioral finance to control the influence of investor sentiment on enterprise value, this paper tries to develop the asset-value model and provides a feasible solution to the problem of measuring the value of Chinese enterprises’ R&D investment.

In this meta-analysis, the authors investigate the relationship between self-construal and conflict management strategies and shed light on the inconsistent findings in the literature. Moreover, they examine the mediating role of face concerns in this relationship. Importantly, the present meta-analysis is the first to test the assumptions of face-negotiation theory with the meta-analytic structural equation modeling (MASEM), which enabled the authors to test the hypothesized relationships in one single model.

The authors used the method of MASEM to test the relationship between self-construal and conflict management and assess the mediating role of face concerns. In this regard, the authors employed one-stage meta-analytic structural equation modeling to perform MASEM and its moderators.

Two hundred fifty-four effect sizes based on thirty-three studies were pooled in this meta-analysis. The authors found that individuals with stronger independent self-construal and stronger self-face concerns were more likely to use forcing. Moreover, the relationship between independent self-construal and forcing was mediated by self-face concerns. Individuals with a stronger interdependent self-construal and individuals with stronger other-face concerns were more likely to use problem-solving and yielding. The relationship between interdependent self-construal and problem-solving and yielding was mediated by other-face concerns. Finally, interdependent self-construal also had an indirect effect, via other-face concern, on avoiding and compromising.

The present meta-analysis is the first effort that the authors are aware of to test the assumptions of face-negotiation theory (FNT) using MASEM method. The authors used one-stage meta-analytic structural equation modeling viewed as the state of the methods to perform MASEM and its moderators. They employed full information meta-analytic structural equation modeling to show the generalizability and heterogeneity of structural equation modeling parameters. They applied studentized deleted residuals to assess outlier analysis and also conducted different methods to perform MASEM to check the robustness of the findings resulted. Finally, the current study adds multiple methods of assessing for publication bias.

The purpose of this paper is to measure the performance of a sampling method through the average number of samples drawn in control.

Matching the adjusted average time to signal (AATS) of sampling methods, using as a reference the AATS of one of them the paper obtains the design parameters of the others. Thus, it will be possible to obtain, in control, the average number of samples required, so that the AATS of the mentioned sampling methods may be equal to the AATS of the method that the paper uses as the reference.

A more robust performance measure to compare sampling methods because in many cases the period of time where the process is in control is greater than the out of control period. With this performance measure the paper compares different sampling methods through the average total cost per cycle, in systems with Weibull lifetime distributions: three systems with an increasing hazard rate (shape parameter β=2, 4 and 7) and one system with a decreasing failure rate (β=0, 8).

In a usual production cycle where the in control period is much larger than the out of control period, particularly if the sampling costs and false alarms costs are high in relation to malfunction costs, the paper thinks that this methodology allows us a more careful choice of the appropriate sampling method.

To compare the statistical performance between different sampling methods using the average number of samples need to be inspected when the process is in control. Particularly, the paper compares the statistical and economic performance between different sampling methods in contexts not previously considered in literature. The paper presents an approximation for the average time between the instant that failure occurs and the first sample with the process out of control, as well.

This study applied eye-tracking techniques and questionnaires within the framework of the Stimulus-Organism-Response Model (SOR) and Technology Acceptance Model (TAM), to investigate the influencing factors of the public acceptance of 5G base stations.

This study used a combination of eye-tracking experiments and questionnaires. The data were analyzed using partial least squares structural equation modeling (PLS-SEM).

(1) The Technology Acceptance Model (TAM) could be used to explain the effects on public acceptance of 5G base stations in the context of the COVID-19 pandemic. The public's perceived usefulness and ease of use of 5G base stations positively affects public acceptance of 5G base stations. (2) The public's perceived risk of 5G base stations has a negative influence on the public acceptance of 5G base stations. (3) The public's visual attention to the different valence information about 5G base stations positively impacts the perceived ease of use while having negative impacts on perceived risk. (4) Visual attention to various valence information of 5G base stations can indirectly influence public acceptance through the perceived risk.

Applying the SOR and TAM to data obtained from eye-tracking experiments and questionnaires, this study analyzed the factors and mechanisms influencing public acceptance of 5G base stations in the context of the COVID-19 pandemic.

In this chapter we ask a simple question: how can we tell if strategic management research is making progress? While other limitations are noted, we argue that it is the absence of metrics for gauging research progress that is most limiting. We propose that research should focus on measures of effect size and that “precision” and “generalizability” in our predictions of important phenomena represent the core metrics that should be used to judge whether progress is occurring. We then discuss how to employ these metrics and examine why existing research practices are likely to hinder efforts to develop cumulative knowledge.

The purpose of this paper is to propose a system with the highest discriminatory power by selecting an indicator system based on the K–S test according to the unique circumstances of small enterprises.

The proposed method relies on calculating the K–S test statistical magnitude of D iteratively to reach a system with the maximum discriminatory power.

The empirical results, demonstrated using 3,045 small businesses from a Chinese bank, show that credit rating system should focus on the indicator system’s discriminatory power rather than a single indicator’s discriminatory power, because the interaction between indicators affects the discriminatory power of the system.

The proposed method creates a credit rating system with the highest discriminatory power, rather than its indicators, which is a more reasonable and novel approach to credit rating.

The approach is unique because the final system will have high discriminatory power and has excellent potential for decision support. The authors believe that this contribution is theoretically and practically relevant because credit rating for small business is especially difficult and complicated.

In order to develop novel high EP S‐containing additives and to meet the need of formulating GL‐5 gear oil or other high EP lubricating oils, aims to investigate the tribological behaviors and mechanism of a di(iso‐butyl)polysulfide (DIBPS), which was synthesized from some cheap materials at low temperature and under normal atmospheric pressure, as an additive in some mineral base oils compared with the traditional sulfurized olefin (SO) additive.

The DIBPS additive was designed and synthesized, of which the main composition is the di(iso‐butyl)trisulfide. Its load‐carrying capacity, anti‐wear and friction reduction properties as additive in some mineral base oils, compared with the traditional SO additive, were investigated using a four‐ball machine and a Timken tester according to relative testing standards. The tribological mechanism was discussed according to the SEM and XPS analytical data.

The results indicate that the four‐ball P_D value and the Timken OK value of the prepared DIBPS in VHVIS500 is clearly better than that of the traditional SO; the anti‐wear property of DIBPS is equivalent to the traditional SO and the friction reduction effect of DIBPS is better than that of the traditional SO. The SEM and XPS data show that the DIBPS additive experiences different tribochemical reaction during tribological process compared with the traditional SO. The S active element of DIBPS reacted with surface metal mainly to form FeSO₄ and/or Fe₂(SO₄)₃ inorganic film, but the S active element of the traditional SO reacted with the surface metal mainly to form FeS inorganic film. This may be the chief reason why the prepared DIBPS possesses better EP properties than the SO.

The results show that the polysulfide additive (DIBPS) possesses better extreme pressure property than the traditional SO. However, more experimental study such as the synergic effect with other additives must be performed, from which it will be clearly shown whether the novel polysulfide can be applied in industrial oils.

These results may be useful for the researchers to formulate some high EP industrial oils.

This paper proves that the designed polysulfide additive, of which the main composition is the trisulfide, possesses better extreme pressure property than the traditional SO, and its tribological mechanicsm is also different with that of SO. It is noticed that the preparative method of this novel polysulfide additive has some superiorities, such as: low‐experimental temperature, low‐experimental pressure and cheap materials.

Since the issuance in 2009, the digital currency has enjoyed an increasing popularity and has become one of the most important options for global investors. The purpose of this paper is to propose a hybrid model ( KDJ–Markov chain) which integrates the advantages of the stochastic index (KDJ) and grey Markov chain methods and provide a useful decision support tool for investors participating in the digital currency market.

Taking Litecoin's closing price prediction as an example, the closing prices from May 2 to June 20, 2017, are used as the training set, while those from June 21 to August 9, 2017, are used as the test set. In addition, an adaptive KDJ–Markov chain is proposed to enhance the adaptability for dynamic transaction information. And the paper verifies the effectiveness of the KDJ–Markov chain method and adaptive KDJ–Markov chain method.

The results show that the proposed methods can provide a reliable foundation for market analysis and investment decisions. Under the circumstances the accuracy of the training set and the accuracy of the test set are 76% and 78%, respectively.

This study not only solves the problems that KDJ method cannot accurately predict the next day's state and the grey Markov chain method cannot divide the states very well, but it also provides two useful decision support tools for investors to make more scientific and reasonable decisions for digital currency where there are no existing methods to analyze the fluctuation.

A new approach to analyze the fluctuation of digital currency, in which there are no existing methods, is proposed based on the stochastic index (KDJ) and grey Markov chain methods. And both of these two models have high accuracy.

High power and speed are new demands for rotating machinery which needs the journal bearings with high dynamic characteristics. The critical speed of the rotor-bearing system is one of the most significant parameters to evaluate the dynamic characteristics. This paper aims to investigate the theoretical and experimental analysis of a rotor system supported by large diameter elliptical bearings.

To obtain the theoretical and experimental support for rotor-bearing system design, dynamic characteristics theoretical analysis based on the finite difference method is given and an experiment focuses on critical speed identification is carried out.

The theoretical calculation results indicate that the critical speed is near to 800 rpm and there is no large vibration amplitude round working speed (1,500 rpm). Using the test bench in the factory unit, vibration data including three experimental processes are obtained. According to the vibration data, the critical speed is identified which also indicates that it is stable when working at 1,500 rpm.

The design method for the rotor system supported by large diameter elliptical bearing can be obtained by the theoretical and experimental results shown in this paper.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2020-0122/