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Drawing upon socio-technical system theory, this study intends to investigate the effects of the congruence and incongruence between artificial intelligence (AI) and explorative learning on supply chain resilience as well as the moderating role of organizational inertia.

Using survey data collected from 170 Chinese manufacturing firms, we performed polynomial regression and response surface analyses to test our hypotheses.

We find that the congruence between AI and explorative learning enhances firms’ supply chain resilience, while the incongruence between these two factors impairs their supply chain resilience. In addition, compared with low–low congruence, high–high congruence between AI and explorative learning improves supply chain resilience to a greater extent. Moreover, organizational inertia attenuates the positive influence of the congruence between AI and explorative learning on supply chain resilience, while it aggravates the negative influence of the incongruence between these two factors on supply chain resilience.

Our study expands the literature on supply chain resilience by demonstrating that the congruence between a firm’s AI (i.e. technical aspect) and explorative learning (i.e. social aspect) boosts its supply chain resilience. More importantly, our study sheds new light on the role of organizational inertia in moderating the congruent effect of AI and explorative learning, thereby extending the boundary condition for socio-technical system theory in the supply chain resilience literature.

This study aims to address the problem of low-temperature wave soldering in industry production with Sn-9Zn-2.5 Bi-1.5In alloys and develop qualified process parameters. Sn–Zn eutectic alloys are lead-free solders applied in consumer electronics due to their low melting point, high strength, and low cost. In the electronic assembly industry, Sn–Zn eutectic alloys have great potential for use.

This paper explored developing and implementing process parameters for low-temperature wave soldering of Sn–Zn alloys (SN-9ZN-2.5BI-1.5 In). A two-factor, three-level design of the experiments experiment was designed to simulate various conditions parameters encountered in Sn–Zn soldering, developed the nitrogen protection device of waving soldering and proposed the optimal process parameters to realize mass production of low-temperature wave soldering on Sn–Zn alloys.

The Sn-9Zn-2.5 Bi-1.5In alloy can overcome the Zn oxidation problem, achieve low-temperature wave soldering and meet IPC standards, but requires the development of nitrogen protection devices and the optimization of a series of process parameters. The design experiment reveals that preheating temperature, soldering temperature and flux affect failure phenomena. Finally, combined with the process test results, an effective method to support mass production.

In term of overcome Zn’s oxidation characteristics, anti-oxidation wave welding device needs to be studied. Various process parameters need to be developed to achieve a welding process with lower temperature than that of lead solder(Sn–Pb) and lead-free SAC(Sn-0.3Ag-0.7Cu). The process window of Sn–Zn series alloy (Sn-9Zn-2.5 Bi-1.5In alloy) is narrow. A more stringent quality control chart is required to make mass production.

In this research, the soldering temperature of Sn-9Zn-2.5 Bi-1.5In is 5 °C and 25 °C lower than Sn–Pb and Sn-0.3Ag-0.7Cu(SAC0307). To the best of the authors’ knowledge, this work was the first time to apply Sn–Zn solder alloy under actual production conditions on wave soldering, which was of great significance for the study of wave soldering of the same kind of solder alloy.

Low-temperature wave soldering can supported green manufacturing widely, offering a new path to achieve carbon emissions for many factories and also combat to international climate change.

There are many research papers on Sn–Zn alloys, but methods of achieving low-temperature wave soldering to meet IPC standards are infrequent. Especially the process control method that can be mass-produced is more challenging. In addition, the metal storage is very high and the cost is relatively low, which is of great help to provide enterprise competitiveness and can also support the development of green manufacturing, which has a good role in promoting the broader development of the Sn–Zn series.

This paper aims to obtain a calculation method by hand without iteration.

This paper adopts strains as known quantities to solve the internal forces and deformations of the section, simplifies the deflection curve of the column and obtains nomograms that can calculate the bearing capacity and reinforcement of circular reinforced concrete (RC) columns by hand.

Nomograms include five variables: mechanical reinforcement ratio, relative normal force, dimensionless bending moment, slenderness ratio and ultimate dimensionless curvature. Nomograms corresponding to all classes of concrete have been drawn, and their dimensionless form makes them widely applicable. The calculation results of nomograms are compared and analysed with numerical calculation results, and the difference is within 5%, meeting the engineering requirements.

Calculating the bearing capacity of compression bending components requires considering second-order effects. Therefore, the calculation of the bearing capacity of circular RC columns requires iterative calculation, as it includes dual nonlinearity of material and geometry, and the two are coupled with each other. To calculate the bearing capacity of the section adopting ordinary concrete, it is necessary to solve the transcendental equation iteratively. For high-strength concrete, it can only be solved by numerical integration. A fast calculation method by hand is proposed in this paper.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

Considering the bounded confidence of decision-makers (DMs), a new grey multi-criteria group consensus decision-making (GMCGCDM) model is established by using interval grey number (IGN), cobweb model, social network analysis (SNA) and consensus reaching process (CPR).

Firstly, the model analyzes the social relationship of DM under social networks and proposes a calculation method for DMs’ weights based on SNA. Secondly, the model defines a cobweb model to consider the preferences of decision-making alternatives in the decision-making process. The consensus degree is calculated by the area surrounded by the connections between each index value of DMs and the group. Then, the model coordinates the different opinions of various DMs to reduce the degree of bias of each DM and designs a consensus feedback mechanism based on bounded confidence to guide DMs to reach consensus.

The advantage of the proposed method is to highlight the practical application, taking the selection of low-carbon suppliers in the context of dual carbon as an example. Comparison analysis is performed to reveal the interpretability and applicability of the method.

The main contribution of this paper is to propose a new GMCGCDM model, which can not only expand the calculation method of DM’s weight and consensus degree but also reduce the time and cost of decision-making.

This study delves into the less-explored domain of teachers’ readiness for leadership roles by investigating the direct and indirect relationships between positive school culture and teachers' readiness for leadership roles through affective-identity motivation to lead, and teacher optimism.

This study employed partial least squares structural equation modelling (WPLS-SEM) for data analysis. The data were gathered from 424 elementary school teachers who do not hold any leadership positions in Xi’an, China. A total of 391 samples were used after sampling weight adjustments.

There is a significant and positive direct relationship between positive school culture and teachers’ readiness for leadership roles. Affective-identity motivation to lead and teacher optimism emerged as significant mediators in this dynamic.

This study complements and expands on the study of the relationship between positive school culture, affective-identity motivation to lead, teacher optimism and teachers' readiness for leadership role. This research has established a theoretical framework for school stakeholders to cultivate future teacher leaders.

These findings provide valuable theoretical insights into educational leadership literature and contribute to a more comprehensive understanding of the factors influencing teachers in assuming leadership roles, particularly in the context of Asian societies.

Corporations are confronted with growing demands to take a stand on socio-political issues, i.e. corporate social advocacy (CSA), which affects their reputation in the public. Companies use different CSA message strategies, including calling the public to support and act on the issue they advocate. Using reactance theory, the authors investigate the impact of CSA messages with a call to action on corporate reputation in the case of a company's gender equality initiative.

A one-factorial (CSA message with or without a call to action) between-subjects experiment was conducted by surveying 172 individuals living in Switzerland. The CSA messages were created in the context of gender equality.

The authors' study indicates that CSA messages with a call to action compared to those without overall harmed corporate reputation due to individuals' reactance, which is higher for CSA messages with a call to action, negatively affecting corporate reputation. The impact of the CSA message strategy with a call to action on corporate reputation remains significant after controlling for issue alignment and political leaning.

Communicating about socio-political issues, especially taking a stand, is a significant challenge for corporations in an increasingly polarized society and has often led to backlash, boycotts and damage to corporate reputation. This study shows that the possible adverse effects of advocating for socio-political issues can be related to reactance. It emphasizes that companies advocating for contested issues must be more cautious about the message strategy than the issue itself.

This paper aims to examine the role of local/provincial government in influencing corporate social and environmental reporting (CSER) in China, and more specifically, how the underlying economic and political factors associated with local government have influenced the quality of CSER.

The authors used 234 environmentally sensitive companies listed on the Shanghai and Shenzhen Stock Exchanges during 2013 and 2015 as the research sample to test the relationship between CSER and local government’s political connection and economic prioritisation and the potential mediating effect of local economic prioritisation.

The analysis provides evidence that local/provincial government’s political geographical connectedness with the central government has directly and positively influenced the level of CSER, while local prioritisation of economic development has a direct but negative effect on CSER in China. In addition, local/provincial prioritisation of economic development has mediated the relationship between local–central political geographical connectedness and CSER.

While local/provincial governments are heavily influenced by the coercive pressure from the central government, they also act in their own political and economic interests in overseeing CSER at the local level. This study raises the question about the effectiveness of the top-down approach to improving CSER in China and suggests that the central government may need to focus more on coordinating and harmonising different local/provincial governments’ interests to enable achieving a common sustainability goal.

The authors provide evidence revealing how the economic and political contexts of local government have played a significant role in shaping CSER in China. More specifically, this paper addresses a gap in the literature by highlighting the importance of local government oversight power for CSER development and how such oversight is determined by local prioritisation of economic development and political geographical connectedness of local and central governments.

Even the greatest developed countries have capitulated to the destructions imposed on the global supply systems, as the COVID-19 pandemic has revealed. The purpose of this study is to explore human resource sourcing strategies for managing supply chain performance during the COVID-19 outbreak. There are six human resource sourcing strategies such as outsourcing, near sourcing, integration, the requirement of suppliers, joint ventures and virtual enterprise that are considered to measure supply chain performance.

Based on collecting data from the potential respondents of Indian manufacturing companies, the elevation of human resource sourcing strategies to supply chain performance is measured considering the multiple regression analysis techniques.

The results of the study revealed that four of the six hypotheses have a significant and positive relationship with supply chain performance during the COVID-19 outbreak while two hypotheses are partially supported that lent good support to this study.

In this critical situation, this study will enable managers and practitioners to support the business in giving customers the best services on time.

The novelty of this study is to identify the key human resource sourcing strategies by using multiple regression analysis methods, considering the case of Indian manufacturing companies to measure their supply chain performance during the COVID-19 outbreak era.

The global energy sector draws significant stakeholder attention due to never-ending controversies surrounding its environmental impacts. Investors’ response to such controversies causes direct financial implications for these firms. Furthermore, environmental, social and governance (ESG) sensitivity, which is likely to safeguard the energy sector firms from such controversies, is itself conditional to the development stage of a country and its regulatory environment. Therefore, this study aims to investigate if the influence of ESG on the share price volatility (SPV) of energy sector firms is subject to the development stage of the countries.

The study investigates nine years of panel data of 93 global energy sector firms from developing and developed nations. Using dynamic two-way fixed effects estimation and computing robust standard errors to obtain the econometric results.

The main finding reveals that the impact of ESG on SPV is, indeed, subject to the development stage of the nations. Similar results are observed for the effects of the social dimension of ESG on SPV. While ESG impacts the SPV negatively for firms in developing economies, the impact is the opposite for firms in developed nations. In other words, strong ESG propositions induce share price stability for developing countries while destabilizing the firms in developed nations.

The policymakers should further streamline the regulations and policies related to ESG adoption and adherence. In practice, the energy sectors should streamline their operations. Firm managers, especially in the energy sector, should devise strategies with ESG as an essential component to safeguard their firms against environmental and market volatility and adversatives. The firms in developing nations should further strengthen their social dimension of ESG to foster social equity and harmony.

The study contributes through its niche investigations on the energy sector, which is very important for the world economy. The study is relevant in the current scenario when the world faces a severe energy crisis due to global supply chain issues.