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Few studies illustrate how contextual effects (e.g. assimilation and contrast) in pay-per-click ad design may impact consumers' attitudes and purchase intention. To fill this research gap, the authors provide theoretical predictions and empirical evidence on how ad design may prompt an assimilation and/or a contrast effect that may influence consumers' attitudes toward the ad and the brand and purchase intention. They also investigate whether the impact of contextual effects on consumers' decisions depends on the level of vividness in the ad.

A 2 (vividness: dynamic motion vs. static page) × 2 (information design: assimilation vs. contrast) × 2 (aesthetic design: assimilation vs. contrast) between-subjects experimental design is used to examine the effects of vividness, information design and aesthetic design. Conditional process analysis is used to assess the mediating role of attitudes toward the ad and the brand in the relationship between contextual effects and purchase intention.

For dynamic ads (i.e. high vividness) but not for static ads (i.e. low vividness), combined information contrast and aesthetic contrast designs generate a more favorable attitude toward the brand and a higher purchase intention than do combined information assimilation and aesthetic assimilation designs. Notably, combined information contrast and aesthetic contrast designs have the strongest effects than any other combination of assimilation and contrast designs of information and aesthetics. Attitudes toward the ad and the brand are significant mediators between contextual factors and intention to purchase.

The study examines the effectiveness of online ads from a new theoretical angle based on the attributes of pay-per-click ads.

The results suggest that when advertisers decide to use dynamic ads, they should adopt a contrast design for both the ad information and its aesthetics.

This study fills a research gap in the contextual effects literature, including providing evidence of an underlying process in the relationship between certain contextual effects and purchase intent. It also extends previous findings of assimilation/contrast in information design to aesthetics design and advances the literature on vividness by examining a moderation effect of vividness.

The purpose of this study is to unfold the role of managerial characteristics in developing the dynamic capabilities necessary to serve foreign customers and compete in export market ventures.

The authors test their proposed model using path analysis with data collected from export managers working in 204 small- and medium-sized Turkish exporters operating in various sectors.

The findings suggest that the positive effect of export managers’ process thinking skills on dynamic capabilities increases when the export managers’ learning and avoid orientations are low and prove orientation is high and export venture experience (duration and scope) increases. In addition, it has been found that export managers’ process thinking skills have an indirect effect on export performance through export venture dynamic capabilities.

This study makes three contributions. First, the authors conceptualize and operationalize dynamic capabilities in the context of exporting. The authors empirically validate export venture dynamic capabilities as a higher-level construct composed of sensing, seizing and reconfiguring elements pertinent to the firm’s export market operations. Second, based on the micro-foundations approach of competitive advantage, the authors study managers’ process thinking skills in exporting firms and how these abilities support dynamic capability development in export ventures. Finally, the authors investigate how the impact of export managers’ process thinking skills on export venture dynamic capabilities is influenced by their goal orientations and certain objective exporter characteristics pertaining to different aspects of export venture experience.

With the focus on the context of small and medium-sized enterprises (SMEs), this study aims to investigate the joint effects of entrepreneurial leadership, entrepreneurial orientation and dynamic capabilities and the mechanisms of how these factors influence firm performance.

A survey from 319 managers in information and communications technology SMEs in Vietnam was conducted, and structural equation modeling was adopted to analyze the collected data.

The results confirm that dynamic capabilities directly influence firm performance and serve as a mediator that connects entrepreneurial leadership and entrepreneurial orientation with firm performance. Additionally, entrepreneurial leadership was found to have a significant positive impact on entrepreneurial orientation.

This research augments the understanding of entrepreneurship and dynamic capabilities literature by examining the joint effects and mechanisms of how entrepreneurial leadership, entrepreneurial orientation and dynamic capabilities interact to enhance SMEs' performance. Furthermore, this study provides empirical evidence of the strategies that SMEs should pursue to attain favorable performance outcomes.

The purpose of this study is to provide new insights into the relationship between fiscal policy and total factor productivity (TFP) while accounting for several economic and econometric issues of the phenomenon like non-stationarity, fiscal feedback effects, persistence in productivity, country heterogeneity and unobserved global shocks and local spillovers affecting heterogeneously the countries in the sample.

The paper is empirical. It builds an Error Correction Model (ECM) specification within a dynamic heterogeneous framework with common correlated effects and models both reverse causality and feedback effects.

The results of this study highlight some new findings relative to the existing related literature. The outcomes suggest some relevant evidence at both the academic and policy levels: (1) the causal effects going from fiscal deficit/surplus to TFP are heterogeneous across countries; (2) the effects depend on the time horizon considered; (3) the long-run dynamics of TFP are positively impacted by improvements in fiscal budget, but only if the austerity measures do not exert slowdowns in aggregate growth.

The main originality of this study is methodological, with possible extensions to related phenomena. Relative to the existing literature, the gains of this study rely on the way econometric techniques, recently proposed in the literature, are adapted to the economic relationship of interest. The endogeneity due to the existence of reverse causality is modelled without implying relevant performance losses of the models. Moreover, this is the first article that questions whether the effects of fiscal budget on productivity depend on the impact of the former on aggregate output growth, thus emphasising the importance of the quality of fiscal adjustments.

This study unravels an attempt to investigate the dynamic connectedness of agri-commodity (wheat) of Russia with 10 financial markets of wheat importing counties during the Russia–Ukraine invasion.

This study took the daily prices of Wheat FOB Black Sea Index (Russia) along with stock indices of 10 major wheat-importing nations of Russia and Ukraine. The time frame for this study ranges from February 24, 2022 to July 31, 2022. This time frame was selected since it fully examines all of the effects of the crisis. The conditional correlations and volatility spillovers of these indices are predicted using the DCC-GARCH model, Diebold and Yilmaz (2012) and Baruník and Křehlík (2018) models.

It is found that there is dynamic linkage of agri-commodity of with stock markets of Iraq, Pakistan and Tanzania in short run while stock markets of Egypt, Turkey, Bangladesh, Pakistan, Brazil and Iraq are spilled by agri-commodity in long run. In addition, it documents that there is large spillover in short run than medium and long run comparatively. This signifies that investors have more diversification opportunity in short run then long run contemplating to invest in these markets.

To the best of the authors’ understanding this is the first study to undertake the dynamic linkage of agri-commodity (wheat) of Russia with financial market of select importing counties during the Russia–Ukraine invasion.

This paper aims to understand better how strategic management (SM) affects organizational and operational performance by examining the mediating role of dynamic capabilities (DCs) in complex environments.

This study uses a survey of a sample of managers (n = 480) from each logistics firm and applies structural equation modeling to determine the relationships among variables.

The analyses identify SM directly and DCs as a mediator significant antecedent for the operational performance; further, environmental complexity shows an impact as a significant factor on both variables.

One of the managerial implications is that acquiring-sensing the environment should be orchestrated to be effective.

Previous DC literature studied underdeveloped DCs in complex environments and ignored the manager’s role as a connection between the environment and the firm. This paper contributes to the topic in three important ways: first, it clarifies the operational performance from the combination of the design of the DCs and the SM characteristics within the complex environment; second, the paper specifies that microfoundations of DCs are essential in the drive’s differences in the performance of the firms; and third, it clarifies regarding the role of the complex external environment rather than dynamic ones.

This paper aims to propose a dynamic parameter identification method based on sensitivity analysis for the 5-degree of freedom (DOF) hybrid robots, to solve the problems of too many identification parameters, complex model, difficult convergence of optimization algorithms and easy-to-fall into a locally optimal solution, and improve the efficiency and accuracy of dynamic parameter identification.

First, the dynamic parameter identification model of the 5-DOF hybrid robot was established based on the principle of virtual work. Then, the sensitivity of the parameters to be identified is analyzed by Sobol’s sensitivity method and verified by simulation. Finally, an identification strategy based on sensitivity analysis was designed, experiments were carried out on the real robot and the results were verified.

Compared with the traditional full-parameter identification method, the dynamic parameter identification method based on sensitivity analysis proposed in this paper converges faster when optimized using the genetic algorithm, and the identified dynamic model has higher prediction accuracy for joint drive forces and torques than the full-parameter identification models.

This work analyzes the sensitivity of the parameters to be identified in the dynamic parameter identification model for the first time. Then a parameter identification method is proposed based on the results of the sensitivity analysis, which can effectively reduce the parameters to be identified, simplify the identification model, accelerate the convergence of the optimization algorithm and improve the prediction accuracy of the identified model for the joint driving forces and torques.

With the continuous increase in the operating speed of high-speed trains, the wear and tear of rails on high-speed lines has also gradually deteriorated. At present, the phenomenon of asymmetric wear of rails in high-speed lines is relatively serious. This paper aims to analyze the effect of three typical rail profile wear on vehicle operation performance.

To solve this problem, by analyzing the wheel-rail contact relationship and establishing a vehicle dynamics model, the influence of worn typical rail profiles on the vehicle’s dynamic performance and carbody abnormal vibration is analyzed. Additionally, the effect of worn rail profiles on wheel wear is analyzed using a wear model.

The results showed that, compared to the standard rail profile, the three typical wear rail profiles show an increase in normal contact stress. The ride and safety indexes of the three rail profiles also increased compared with the CHN60 profile. The rail Profile 3 does not affect carbody vibration, while Profile 1 and Profile 2 can cause hunting vibrations of the carbody, with the main vibration frequencies around 7 Hz. The wheel wear depths under three typical rail profiles are 1.185 mm, 1.11 mm and 1.058 mm.

The effect of the measured typical rail profiles on the vehicle’s performance is analyzed, particularly in terms of abnormal vibrations and wheel wear. This analysis can provide guidance for the long-term maintenance of the rail system.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0270/

This study aims to exploit Tobin’s Q model of investment to examine the relationship between corporate governance and green innovation.

The study is based on a sample of 3,896 firms from 2002 to 2021, covering 45 countries worldwide. The authors adopt Tobin’s Q model to conceptualize the relationship between corporate governance and investment in green research and development (R&D). The authors argue that agency costs and financial market frictions affect corporate investment and are fundamental factors in R&D activities. By limiting agency conflicts, effective governance favors efficiency, facilitates access to external financing and encourages green innovation. The authors analyzed the causal effect by using the system-generalized method of moments (system-GMM).

The results reveal that the better the corporate governance, the more the firm invests in green R&D. A 1%-point increase in the corporate governance ratings leads to an increase in green R&D expenses to the total asset ratio of about 0.77 percentage points. In addition, an increase in the score of each dimension (strategy, management and shareholder) of corporate governance results in an increase in the probability of green product innovation. Finally, green innovation is positively related to firm environmental performance, including emission reduction and resource use efficiency.

The findings provide implications to support managers and policymakers on how to improve sustainability through corporate governance. Governance mechanisms will help resolve agency problems and, in turn, encourage green innovation.

Understanding the impact of corporate governance on green innovation may help firms combat climate change, a crucial societal concern. The present study helps achieve one of the precious UN’s sustainable development goals: Goal 13 on climate action.

This study goes beyond previous research by adopting Tobin’s Q model to examine the relationship between corporate governance and green R&D investment. Overall, the results suggest that effective corporate governance is necessary for environmental efficiency.

The authors explore the relationship between the exchange rate, bond yield and the stock market as well as the effect of capital market dynamics on the exchange rate before and during the COVID-19 pandemic.

The authors employ a non-linear autoregressive distributed lag (NARDL) methodology using daily data of the Indonesian economy over the period 2012–2021.

Whilst, over the full sample period, the authors find no cointegration between the exchange rate, the 10-year bond yield and stock market, for the COVID-19 period, evidence of cointegration is present. Furthermore, the results suggest that asymmetric effects are evident both in the short as well as the long run.

To the best of the authors’ knowledge, this is the first time that the relationship between the exchange rate, bond yield and the stock market as well as the effect of capital market dynamics on the exchange rate before and during the COVID-19 pandemic has been explored in the case of the Indonesian economy.