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A green innovation strategy is an important step for enterprises to balance economic and environmental. As the executors of strategic decisions, the attitude and capabilities of senior managers determine the effectiveness of implementing green innovation. Therefore, this paper aims to explore the relationship between executive compensation incentives and green innovation.

Based on the data of heavily polluting enterprises listed in China's A-share market from 2015 to 2020, this study constructs an OLS model with fixed effects of time and industry, and uses the mediation three-step method to verify the correlation between executive compensation incentives, innovation openness and green innovation. Meanwhile, the grouping regression was used to test the moderating effect of environmental regulation on executive compensation incentives.

The empirical results show that executive salary incentives promote green innovation and equity incentives inhibit green innovation; the openness breadth partially mediates the relationship between salary incentives, equity incentives and green innovation, while the openness depth only partially mediates the relationship between equity incentives and green innovation; and environmental regulation positively moderates executive incentives.

Due to sample selection and variable measurement, the study lacks certain generality. Therefore, future research needs to further analyze the internal factors affecting green innovation from multiple dimensions.

This study provides a new evidence for analyzing how executive compensation measures affect green innovation, and further enhances the mediating mechanism of open innovation.

This study has significant theoretical implications for examining the intra-firm factors that affect green innovation.

With the advance of the Silk Road Initiative proposed by China, it has been a focus of China government to develop strategic emerging industries. The development of strategic emerging industries needs the support of competitive intelligence on many aspects such as strategical planning, policy making, industrial structure adjustment, and technology innovation. However, so far there are few studies toward the competitive intelligence systems for strategic emerging industries. In this article, we focus on a number of issues related to the competitive intelligence for strategic emerging industries in China. First, we conduct a strengths, weaknesses, opportunities, and threats analysis on the situations of strategic emerging industries in China, based on which the necessity of building a competitive intelligence (CI) service system for strategic emerging industries is discussed. Next, the authors present a framework of a CI service system for strategic emerging industries in China. The principles, components, working process, and product forms are deeply described. The CI service system proposed in this article consists of a cooperation network platform, three layered organizations, and three systems, which integrates organizations, information, people, network, and service platforms into an ecosystem to offer competitive intelligence supports for government, industry, and enterprises. Finally, the authors discuss a case study of the proposed CI service system for the new energy automobile industry.

In as much as it is contested, the Belt and Road Initiative (BRI) is also unexplored, underdiscussed, and, as a result, misunderstood. Frequently viewed through the lens of international relations and global economy, the diverse dimensions of collaboration, including business and research-industry clusters, that BRI enhances, tend to be excluded from the analysis. In a similar manner, the role of the Arab Peninsula in the grand strategy underpinning BRI and its implementation is rarely discussed. BRI is a forward-oriented initiative, an attempt to reap benefits of developments and circumstances that are only nascent. This bears two potent implications. First, as China attempts to influence the context in which it operates, it is subject to change itself; the Chinese business sector evolution attests to that. Second, some of China’s not so obvious partners of today, including those in the Arab Peninsula, are about to turn into key interlocutors of tomorrow. BRI taps into opportunities thus created. This chapter elaborates on these issues and, against this backdrop, outlines how the remaining chapters included in this volume add to this discussion.

This paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing and proposes an improved Bass model for the forecasting of such a demand and the demand for new clothing products.

From the perspective of how to solve the lack of data and improve the precision of the clothing demand forecast, this paper studies the measurement of clothing similarity and the addition of demand impact factors. Using the fuzzy clustering–rough set method, the degree of resemblance of clothing is determined, which provides a basis for the scientific utilisation of historical data of similar clothing to forecast the demand for new clothing. Besides, combining the influence of consumer preferences and seasonality on demand forecasting, an improved Bass model for a fast fashion clothing demand forecast is proposed. Finally, with a forecasting example of demand for clothing, this study also tests the validity of the method.

The objective measurement method of clothing similarity in this paper solves the problem of the difficult forecasting of demand for fast fashion clothing due to a lack of sales data at the preliminary stage of the clothing launch. The improved Bass model combines, comprehensively, consumer preferences and seasonality and enhances the forecast precision of demand for fast fashion clothing.

The paper puts forward a scientific, quantitative method for the forecasting of new clothing products using historical sales data of similar clothing, thus solving the problem of lack of sales data of the fashion.

In the new retail era, the supply chain synergy produced by quality integration has become the new direction of service supply chain research. The purpose of this paper is to study how to promote the sustainable development of the retail service supply chain (RSSC) by comparing and analyzing the optimal quality behavior, optimal returns, and the combination of conditions and strategies of the participating members of the RSSC.

From the perspective of quality function development and service quality concern, this paper considers RSSC as a two-level supply chain structure composed of functional service provider and retail service integrator. In this paper, a dynamic optimization model of quality input-cooperation-coordination of RSSC is proposed under two quality cooperation modes of decentralization and integration. This paper adopts the differential game method to compare and analyze the optimal quality behavior, optimal income, forming conditions and strategic combination of the participating members of the RSSC in different situations.

(1) Compared with quality dispersion, quality integration has more significant Pareto improvement effect on quality behavior and optimal revenue of RSSC. (2) In the case of quality integration, the optimal revenue obtained by the service sharing model is generally better than that obtained by the retail alliance collaboration model. (3) Benefit distribution ratio and quality cost allocation determine the optimal quality behavior of participating members of the RSSC, and also become the key factors for participating members to choose the collaborative mode in the case of quality integration.

Based on the quality function development of RSSC, this paper introduces the concept of steady service quality, and discusses the relationship between the quality cooperation stability and the mode selection of RSSC. This provides a theoretical basis for how to build a RSSC with efficient operation and stable quality.

This study aims to review the role of green training and green work life balance (GWLB) on sustainable organizational performance (SOP) with a moderating variable “Emotional Intelligence” (EI).

For the development of the construct of the present study, a Scopus database was selected and research papers published in indexed journals were considered. Relevant keywords were selected and literature was searched on green training, EI, SOP, GWLB. The literature was reviewed to find out the linkage and possibility of development of integrated model. The main focus was on highlighting the relevance of green training on GWLB and its influence on SOP.

SOP can be achieved with the intervention of EI and GWLB; further green training is one of the influential practices of human resource development (HRD) which helps to develop the green behavior.

It can give new insight to the organization for application of green human resource practices for SOP. Development and designing the cohesive environmental work culture and willingness to protect environment through green training can be implemented by HRD. Perhaps, the application of green training encourages GWLB.

Quantitative research and cross sectional study is required to find out the intervening role of EI and work–life balance between green training and SOP across a broader range of sectors.

This research extends the literature review and developed a new integrated model which shows the link between green training and SOP.

This paper examines the effect of lockdown on a firm's financial performance. The authors aim to fill in the debate over the corporate world's repercussions from governments' COVID-19 response. Therefore, it is imperative to understand what effect the lockdown policy has on firm financial performance.

The study data are cross-sectional, covering a sample of 246 listed firms in Indonesia. The lockdown policy and period data were retrieved from the Indonesian Ministry of Health COVID-19 special task force website. The authors’ empirical model for performance specification is based on annual data, following a common performance function in economics and finance literature. In addition to controlling for the standard error and province effect, the authors also controlled the COVID-19 cases and the province effect.

The lockdown deteriorates the firm's profitability, but it is not up to making the firms at financial distress level. Simply put, lockdown erodes the profitability significantly, leading to declining performance; however, it does not mean the firms generate default.

Several shortcomings in the authors’ empirical setup need to be tackled for future research. For example, the study findings may limit the short-run effect but not the long-run effect (5–10 years after the pandemic). The findings also do not give room to justify that lockdown should not be imposed due to its deteriorating effect on the corporate world. Therefore, the authors leave this as a scope for future research.

This research is among the pioneer papers evaluating the effect of the government policy for mitigating the repercussions of COVID-19, and it reveals how this policy affects corporations.