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Through the study, we identified four effective paths to improve governance performance and also found the key direction for future research on digital twin urban implementation of public crisis governance, i.e. how to find a balance between the cost and the effectiveness of governance.

A total of 22 urban public emergencies were selected based on key influencing factors, and four action paths to improve the performance of public crisis governance in digital twin cities were obtained using a fuzzy set qualitative comparative analysis model.

This paper identified digital twin technologies in urban public crisis governance, analyzed the key factors of public crisis governance in the digital twin city and proposed a path of action to improve the performance of public crisis governance in digital twin cities.

This study focuses on the influencing factors of public crisis governance in digital twin cities and the action paths to promote improved governance performance.

This study aims to propose the use of time series autoregressive integrated moving average (ARIMA) models to predict gas path performance in aero engines. The gas path is a critical component of an aero engine and its performance is essential for safe and efficient operation of the engine.

The study analyzes a data set of gas path performance parameters obtained from a fleet of aero engines. The data is preprocessed and then fitted to ARIMA models to predict the future values of the gas path performance parameters. The performance of the ARIMA models is evaluated using various statistical metrics such as mean absolute error, mean squared error and root mean squared error. The results show that the ARIMA models can accurately predict the gas path performance parameters in aero engines.

The proposed methodology can be used for real-time monitoring and controlling the gas path performance parameters in aero engines, which can improve the safety and efficiency of the engines. Both the Box-Ljung test and the residual analysis were used to demonstrate that the models for both time series were adequate.

To determine whether or not the two series were stationary, the Augmented Dickey–Fuller unit root test was used in this study. The first-order ARIMA models were selected based on the observed autocorrelation function and partial autocorrelation function.

Further, the authors find that the trend of predicted values and original values are similar and the error between them is small.

This study aims to solve the problem of repair path planning between multiple small-size defects in the field of additive manufacturing (AM) repair by using Python-based ant colony algorithm (ACO). The optimal parameter combination scheme is obtained by discussing the influencing factors of parameters in the ACO.

The effects of the information heuristic factor α, the expected heuristic factor ß and the pheromone volatile factor ρ on the simulation results were investigated by designing a three-factor and three-level orthogonal experiment. The fast convergence of ACO in finding the optimal solution of multiple small-size defect repair path problem is proved by comparing the simulation results with those of genetic algorithm (GA) on the same data set.

The ACO can effectively solve the repair path planning problem between multiple small-size defects by optimizing the parameters. In the case of 50 defect locations, the simulation results of the ACO with optimized parameters are 159.8 iterations and 3,688 average path lengths, while the GA has 4,027.2 average path lengths under the same data set and the same number of iterations, and by comparison, it is proved that the ACO can find the optimal solution quickly in the small-size defects repair path planning problem, which greatly improves the efficiency of defect repair.

The parameter-optimized ACO can be quickly applied to the planning problem of repair paths between multiple small-size defects in the field of AM repair, which can better improve the defect repair efficiency and reduce the waste of resources.

This paper aims to investigate the innovation pathway of gerontechnological enterprises under the market-organization-technology (MOT) perspective through configuration analysis.

Based on the analytical framework of technology, organization and market, this paper conducts configuration analysis on the cases of 55 elderly-friendly enterprises in China combined with fuzzy-set qualitative comparative analysis (fsQCA).

First, this study identifies the three first-level preconditions affecting innovation performance: organization's architectural innovation, technology adapting to aging and market environment attention on the innovation pathway of gerontechnological enterprises. These three first-level conditions include six sub-conditions. Second, this study investigates three innovation pathways by analyzing the configuration effects of preconditions: Configuration 1, technology-balanced type; Configuration 2, organization-market linkage type and Configuration, 3 balanced type. Third, there are differences in the distribution of different configuration types in subdivided industries. The technology-balanced configuration is mainly concentrated in design-driven innovative enterprises, the organization-market linkage configuration is mainly concentrated in medical auxiliary equipment enterprises and the balanced configuration is mainly concentrated in smart elderly care service platform enterprises empowered by digital technology. Fourth, there are differences in the innovation impact paths of the same configuration type. However, the essence lies in the high-level innovation performance formed by the coordinated evolution of technology, organization and market factors, reflecting the characteristics of the same goal through different routes.

The authors' study generates new insights for innovation managers of gerontechnological enterprises about the innovation pathway.

This research enriches innovation management by integrating the linkage adaptation relationship among market, organization and technology factors; further research studies on the different configuration types suitable for different types of enterprises, as well as differentiated innovation pathways under the same configuration type, could contribute to the study on the innovation pathway under a premise of MOT.

Resource orchestration theory proposes that firms need resources, capabilities, and horizontal and vertical alignment to achieve high performance. Thus, we investigate which combinations of horizontal fit of resources (commitment-based HR systems for managers and nonmanagers) and capabilities (HR flexibility) together with vertical fit with business strategy (innovation versus cost leadership strategies) relate to superior performance.

Our study is based on a sample of 113 Spanish firms from which we collected data on commitment-based HR systems for managers and nonmanagers, HR flexibility, business strategy and performance. We employ a fuzzy set qualitative comparative analysis (fsQCA) to analyze which configurations lead to firm performance.

The empirical analysis shows that both HR practices and policies (commitment-based HR systems) and HR capabilities (HR flexibility) need to be aligned for high performance. The path for performance is comprised of a combination of commitment-based HR systems for staff and HR flexibility and by the absence of an innovation strategy or commitment-based HR systems for managers, HR flexibility, and a cost leadership strategy. We also find four paths where performance relies on efficiently combining an innovation and cost leadership business strategy.

Our findings make three key contributions to the literature. First, we help elucidate multicausal relationships inside the black box of the “HR–performance” relationship for firm performance. Second, we study the vertical fit with business strategy by considering innovation and cost leadership strategies. Third, we analyze multicausal pathways, thus uncovering different combinations of resources and capabilities for performance.

This study aims to investigate the influences of perceived and preferred coaching behaviors and the discrepancy between them on job satisfaction, mediated by the quality of the relationship with the immediate supervisor and adaptive performance.

The research adopted a cross-sectional survey design. A total of 220 Korean employees, small-sized team members, were recruited from the automotive industry for the study. This research explored the relationship between perceived and preferred coaching behaviors using the Pearson correlation. Structural equation modeling was used to analyze the relationships among perceived and preferred managerial coaching behaviors, the discrepancy between them, the quality of the relationship with the immediate supervisor, adaptive performance and job satisfaction.

Perceived and preferred coaching behaviors exhibited a weak correlation. Perceived coaching behaviors indirectly influenced job satisfaction through the quality of the relationship with the immediate supervisor and adaptive performance. The discrepancy between perceived and preferred coaching behaviors directly and indirectly influenced job satisfaction via adaptive performance. However, all paths related to preferred coaching behaviors were found to be insignificant.

Although the results of this research may be generalized to the Korean automotive industry, the findings highlight perceived and preferred coaching behaviors and the discrepancy between them as independent variables. The findings shed light on the influences of managerial coaching on the quality of the relationship with the immediate supervisor within Korean workplace cultures and how coaching behaviors contribute to triggering subordinates’ adaptive performance. In addition, the study provides how managerial coaching influences job satisfaction in the workplace.

Based on the findings, an organization should cultivate self-directed learning environments to enhance employees’ adaptive performance. The coaching training session should be added to the leadership development program for new managers. Team leaders need to consider their members’ preferences during managerial coaching.

The variables, such as preferred coaching variables and the discrepancy between perceived and preferred coaching behaviors, along with the research framework, represent a novelty in managerial coaching, as well as within the Korean context.

As competitive pressures persist and global economic influences continue to present new challenges, businesses need to be able to respond to emerging circumstances. Goal-setting and planning are key mechanisms contributing to organizational competitive success, yet organizations underappreciate the role of competency and capacity building factors that contribute to successful planning. This paper integrates three theoretical models enabling an investigation into the positive relationships between managerial activities generating information feedback, training in planning and skills and organizational performance outcomes, while exploring the positive mediating roles of goal-setting and planning.

A unique organizational sample of agribusiness producers (n = 499) in Canada is examined. A structural equation path analysis model is used to evaluate the main relationships.

The results suggest that organizations are finding that managerial and training activities should not be considered in isolation, but rather as supports for goal-setting, planning and performance outcomes. Thus, the implications are that managers can find organizational value enhanced through the building of human resource competency (e.g. management activities and training) with these emerging capacities aiding goal setting and planning activities.

This study makes three main contributions: first, by adopting a rational-design perspective and integrating theoretical frameworks focusing on (a) planning-performance and (b) goal-setting-planning. This extended model goes beyond previous studies by including managerial activities, training, goals, planning and performance outcomes. Second, this study uniquely accounts for a more comprehensive set of key confounding factors such as operational activities, organizational strategy and organizational size in the integrated framework. Finally, as far as the authors are aware, there has not been a survey study at the organizational level that has explored the role of managerial activities and training in planning within a similarly comprehensive model.

By adopting learning theory and a guanxi perspective, this study aims to investigate the effects of interpersonal guanxi (interpersonal networks or connections) and relationship learning on companies’ business performance when operating in a large emerging market.

Using a sample of 294 sales managers and salespeople in the Chinese hotel sector, the authors empirically test the authors' arguments through a structural equation modeling (SEM) approach.

The authors' findings indicate that strong interpersonal guanxi tends to generate more positive business performance. Furthermore, the authors find that relationship learning plays a mediating role in the association between interpersonal guanxi and hotel companies’ business performance in a Chinese context. Finally, the authors empirically explore the moderating effect of inter-firm dependence on the contribution of interpersonal guanxi to relationship learning. Findings demonstrate that this effect varies significantly based on inter-firm dependence, with interpersonal guanxi exhibiting a greater positive impact if such dependence is high.

This study enriches our understanding of interpersonal guanxi and of how companies can enhance the companies' business performance in an emerging market context.

This research examines how to enhance financial performance (FP) through the interplay between information technology and their suppliers in the supply chain. On this, the research objective is to assess the role of integration with suppliers (IWS) and integration by suppliers (IBS) in the interface between integrated information technology (IIT) and FP in the supply chain.

A theoretical model was designed, and hypotheses were tested with structural equation modelling and qualitative data from a survey of 205 multi-industry companies from Egypt.

The findings indicate that IIT has a positive significant relationship with financial performance, in this case, partially mediated jointly by IWS and IBS.

This study contributes to the literature by establishing a measurement approach for the proposed duality of supplier integration. A crucial implication of this duality is the requirement of IWS and IBS to enhance the effect of IIT on FP in supply chain partnerships and the fact revealed in our research that IWS precedes IBS in supply chains.

This paper aims to examine the effect of R&D laboratories on the perceived performance of MNE subsidiaries during recession.

Employing resource-based view and knowledge-based theory, the authors investigate a unique sample of 171 technologically heterogenous foreign MNE subsidiaries located in Greece over the period of recession 2009–2016. The sample subsidiaries operate different types of R&D laboratories.

The authors find that MNE subsidiaries with advanced R&D laboratories such as locally integrated laboratories (LILs) and internationally interdependent laboratories (IILs) perform better in recession than subsidiaries with support laboratories (SLs) or subsidiaries without R&D laboratories. Overall, the authors find an asymmetric performance contribution of R&D laboratories at subsidiary level.

The study provides useful insights into the environmentally derived “knowledge-based - performance” context, so filling an important research gap, since little is known about the performance impact of the input-side of technological activity at MNE subsidiary level, especially as regards R&D facilities/infrastructure. Based on the findings the authors identify important managerial implications.