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Recognizing the differences between generations Y and Z, this exploratory study uses generational cohort theory as a framework to examine the brand perception of McDonald's, an international brand which has grown up with consumers for over 30 years in China. The paper aims to discuss this issue.

Measures of brand perception was built based on Aaker's brand personality model. A total 1,103 valid questionnaires were collected through an online survey platform. Factor analysis is the primary method to analysis the data.

The findings of this study reveal a favourable brand perception of McDonald's among young Chinese consumers which is consistent with Aaker's brand personality model and support the use of generational cohort theory as a market segmentation tool for brand perception. The differences between the two generational cohorts are not shown to be significant.

The most important contribution of this study is the evaluation of the personality of a major brand in China for Gen Z, a topic with very little existing research. Also, this research suggests future in-depth research into generational cohort theory in a Chinese context by recognizing homogeneity and heterogeneity exist simultaneously between generational cohorts.

This paper aims to propose hybrid global optimization based on multiple metamodels for improving the efficiency of global optimization.

The method has fully utilized the information provided by different metamodels in the optimization process. It not only imparts the expected improvement criterion of kriging into other metamodels but also intelligently selects appropriate metamodeling techniques to guide the search direction, thus making the search process very efficient. Besides, the corresponding local search strategies are also put forward to further improve the optimizing efficiency.

To validate the method, it is tested by several numerical benchmark problems and applied in two engineering design optimization problems. Moreover, an overall comparison between the proposed method and several other typical global optimization methods has been made. Results show that the global optimization efficiency of the proposed method is higher than that of the other methods for most situations.

The proposed method sufficiently utilizes multiple metamodels in the optimizing process. Thus, good optimizing results are obtained, showing great applicability in engineering design optimization problems which involve costly simulations.

The purpose of this paper is to develop a coiling robot in the production of coated elevator compensation chains to replace the manual coiling operations and improve the quality of compensation chains.

This paper introduces both mechanical and servo control system designs of the coiling robot. The structure of two friction wheels stabilizes the conveying speed of compensation chain, so the chain speed matches with the car speed. A centering mechanism pushes the chain to its original position. Seven servo motors are integrated into the system, and they are controlled by a servo control system based on programmable logic controller, positioning controller, analog output block and touch screen.

The results of the project show that the coiling robot can both greatly reduce the number of workers and the intensity of the work and improve the quality of the chain. The chain lid by the robot is not only neat, but also uniform in its inner stress.

When the output speed of the compensation chain from the rear friction wheel does not match the coiling speed, the coiling operation has to be halted. Then, the operator adjusts the chain speed and restarts the coiling operation.

The coiling robot is proven working. It has been adopted by a leading company manufacturing compensation chains.

This is the first coiling robot which is practically used in a production line of compensation chains. Its design, mechanism and control systems are of great reference values to people.

This study aims to model collaborative product development (CPD) among a focal firm (FF) and a fairness-concerned external partner (EP). The model is used to explore the impact of fairness concerns on revenue distributing contract and innovation efforts. The study also examines the role of follow-up sales in product development decisions.

A sequential game-theoretic model is developed to analyze product development decisions between the two parties, where participants exert innovation efforts to promote the product value and a revenue-sharing contract is used to distribute the revenue.

Fairness concern of EP has significant impacts on decisions. FF has incentives to change the contract in that fairness concerns might decrease his profit. Conditions and results change when the contract is endogenously decided. First, FF tends to develop the product independently. Second, FF may share a smaller revenue fraction with EP, as FF relies more on his own efforts during CPD. Third, FF cannot benefit from fairness concerns, as his profit is not higher than that in the benchmark. Finally, the existence of follow-up sales does not change FF’s decision about whether to collaborate with EP.

This study incorporates fairness preference into CPD decisions. Besides, a new concept of fairness called “effort-related fairness” is proposed.

This study aims to investigate whether the presence of female directors on audit committees affects audit fees in Chinese listed companies. This study also investigates whether the audit committee’s gender diversity moderates the relationship between the firm’s inherent situational factors (e.g. audit complexity and firm risk) and audit fees. Finally, this study investigates whether the effect of the audit committee’s gender diversity on audit fees varies with within-country institutional contingencies (e.g. state-owned enterprises [SOEs] vs non-SOEs and firms that are located in more developed regions vs firms that are located in less developed regions)

This study used the data of all A-share listed companies on the Shanghai and Shenzhen stock exchanges for the period from 2009 to 2015. The authors use ordinary least squares regression as a baseline methodology, along with firm fixed effect, Deference in Deference method, two-stage least squares regression, two-stage Heckman model and generalized method of moments models to control for the possible issue of endogeneity.

The study’s findings suggest that the presence of female directors on the audit committee improves internal monitoring and communication, which reduce the perceived audit risk and the need for assurances from external auditors. The results also suggest that female directors demand high-quality audits and further assurance from external auditors when the firm is more complex and riskier. In addition, the results suggest that within-country, institutional factors play significant role in shaping the governance role of gender-diverse audit committee.

The study contributes to the agency theory by providing evidence that the interaction between agency theory and corporate governance “board composition” generates an effective monitoring mechanism and contributing to the institutional theory by finding that role of female directors on audit committee varies from context to another. In addition, this study contributes to literature review of gender diversity in the boardroom by finding the economic benefit of having female directors on audit committee. Finally, this study has implications for policy-makers in promoting regulations to legalize women presence on the board, to external auditors in assessing control risk during planning the audit, to those who responsible for appointing audit committee members.

The authors extend earlier studies by providing novel evidence on the relationship between gender-diverse audit committees and audit fees in terms of both the supply- and demand-side perspectives; that female directors moderate the relationship between firm inherent situational factors (e.g. audit complexity and firm risk) and audit fees; and that the effect of audit committees’ gender diversity on audit fees varies with sub-national institutional contingencies.

The purpose of this paper is to investigate the association between aggressive tax planning and stock price synchronicity.

Employing the special institutional background of China, this study constructs tax aggressiveness and stock price synchronicity measures for a large sample of Chinese stocks spanning the period 2003–2015. The authors employ OLS regression as the baseline methodology, and a fixed effect model, the Fama–Macbeth method and GMM as sensitivity checks. Matched samples and difference-in-difference analyses are used to control for endogeneity.

The authors find a significant and positive association between aggressive tax planning and stock price synchronicity. Because material information about risky tax transactions tends to be hidden in various tax accruals accounts, aggressive tax strategies make financial statements less transparent, thereby, increasing information asymmetry and decreasing stock price informativeness. The authors also find that the firms engaging in aggressive tax planning exhibit relatively high corporate opacity. In addition, the authors find that improvements in the tax enforcement regime, ownership status and high-quality auditors all constrain the adverse effects of tax aggressiveness.

This study has important practical implications for China’s regulators, who are striving to reduce the tax burden of enterprises. It also helps investors to consider investment decisions more appropriately from a taxation perspective.

First, this paper contributes to the stock price efficiency literature by identifying the effect of a hitherto unexamined factor, namely, firm-level aggressive tax planning, on the efficiency of stock prices. Second, this study provides further empirical evidence to support the agency view of tax aggressiveness, and the informational interpretation of stock price synchronicity. Third, this study helps us better understand the effects of firm-level tax policy on firm-specific information capitalization in an environment where overall country-level investor protection is relatively weak.

The purpose of this paper is to efficiently use as few sample points as possible to get a sufficiently explored design space and an accurate optimum for adaptive metamodel-based design optimization (AMBDO).

A parameterized lower confidence bounding (PLCB) scheme is proposed in which a cooling strategy is introduced to guarantee the balance between exploitation and exploration by varying weights of the predicting error and optimum of a metamodel. The proposed scheme is investigated by a set of test functions and a structural optimization problem, in which PLCB with four kinds of cooling control functions are studied. Moreover, other infill criteria (such as expected improvement and its extension versions) are taken into comparison.

Results show that the proposed PLCB (especially PLCB with the first cooling control function) based AMBDO method can find the optimum with fewer evaluations and maintain good accuracy, which means the proposed PLCB contributes to the excellent efficiency and accuracy in finding global optimal solutions.

The parameterized version of the lower confidence bound metric is proposed for AMBDO, typically used in the context of adaptive sampling in efficient global optimization.

This paper aims to explore the drivers behind the accuracy of self-reported home valuations in the Warsaw (Poland) housing market.

In order to achieve the research goal, firstly, unique data on subjective residential property values estimated by their owners were compared with market-justified ones. The latter was calculated using geographically weighted regression, which allowed for taking into account spatially heterogeneous buyers' housing preferences. An ordered logit model was then used to identify the factors influencing the probability of the occurrence of bias towards over or undervaluation.

The results of the study revealed that, on average, homeowners overvalued their properties by only 1.94%, and the fraction of interviewees estimating their properties accurately ranges from 20% to 68%, depending on the size of the margin of error adopted. The drivers of the valuation bias variation were the physical, locational and neighbourhood attributes of the property as well as the personal characteristics of the respondents, for which their age and employment situation played a key role.

In contrast to previous studies, this is the first to examine drivers behind the accuracy of self-reported home valuations in a Central and Eastern Europe country. In addition, this work is the first to consider heterogeneous housing preferences when calculating objective property values.

This paper aims to successfully synthesize three-dimensional spindle-like Au functionalized Co₃O₄-ZnO nanocomposites; characterize the structure, morphology and surface chemical properties of the products; study the effect of Au NPs doping concentration, operating temperature different gas to, sensing properties; and introduce an attractive gas sensor for acetone detection.

Au NPs functionalized Co₃O₄-ZnO nanocomposite was prepared by coprecipitation and impregnation methods; the structure and surface chemical property of the products were characterized by XRD, SEM, TEM, UV-Vis, BET and XPS. The sensing ability of Au@Co₃O₄-ZnO for acetone and mechanism was analyzed systematically.

The results of gas sensing tests show that the unique component structure, Schottky junction and catalytic effect of Au functionalization make it have low operating temperature, excellent selectivity, high response (10 ppm, 56) and rapid response recovery time.

All the characterization and test data of the prepared materials are provided in this paper and reveals the gas sensing mechanism of the gas sensor.

The detection limit is 2.92–100 ppb acetone. It is promising to be applied in low-power, micro detection and miniature acetone gas sensors.

The gas sensor prepared has a lower working temperature and low detection limit, so it has promising application prospects in low-concentration acetone detection and early warning.

The unique component structure, Schottky junction and catalytic effect of Au functionalization Co₃O₄-ZnO make it have low operating temperature, excellent selectivity and rapid response recovery time.

Despite the availability of many metrics and tools for marketing performance measurement, the way in which firms use their marketing metrics remains underexplored. This study aims to address this gap by empirically establishing the differing effects of the diagnostic and interactive uses of marketing metrics on firms’ market-sensing capability, contingent on competitive intensity and focus on market-related metrics.

This study builds on survey data collected from 210 Irish-based firms, complemented by 21 in-depth interviews with business managers. Survey data are analysed using regression analysis.

This study finds that firms using marketing metrics interactively to communicate organizational focus are better able to sense their markets, especially under high competition. The authors observe a positive impact of the interactive use of metrics on market-sensing capability, but a U-shaped impact of their diagnostic use, the magnitudes of which further depend on competitive intensity and firms’ focus on market-related metrics.

This study provides a nuanced view of marketing performance measurement (MPM) practices within firms, particularly focussing on diagnostic versus interactive uses of marketing metrics. It also sheds further light on how two diverse uses of marketing metrics – diagnostic and interactive uses – influence a firm’s market-sensing capability. Moreover, the identification of boundary conditions also contributes to the discussion of contextuality in MPM, highlighting the importance of aligning a firm’s uses of marketing metrics with its business environment.

This study provides novel insights into how diverse uses of marketing metrics may benefit firms. The differing effects of diagnostic and interactive uses of marketing metrics on market sensing highlight a primary need for developing the latter and for using the former only with caution. It establishes that all firms would equally benefit from an interactive use of marketing metrics that is pivotal to improving their ability to anticipate, detect and sense market changes.

This study provides novel understanding of the role of marketing metric uses in firms’ market-sensing capability and contributes to the discussion of contextuality in marketing performance measurement. It highlights the importance of aligning a firm’s use of marketing metrics with its business environment.