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This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.

In recent years, sustainable supply chain practices (SSCPs), including corporate social responsibility (CSR), have been recognised as important means of developing firms’ sustainability performance (SP). However, empirical findings on the SSCP–SP interaction are inconsistent and even contradictory. This research presents a quantitative meta-analysis that aims to uncover SSCP–SP interactions based on the correlations found in previously published empirical studies.

Based on the main and moderating variables and selection criteria, 64 sample studies were selected after a systematic literature review and meta-analysis.

The findings confirm a positive correlation (0.438) between SSCP and SP. The results also reveal various critical moderators identified through meta-regression.

This study provides insights for operations managers and policymakers regarding the significance of control variables (e.g. ISO certification, type of economy, innovation approach, data collection method) on the relationship between SSCP and SP for business operations. This research uncovers the impacts of ISO regulations and proposed hypotheses through the lens of the natural resource-based view (NRBV) and institutional-based view (IBV).

This research is unique in that it provides a systematic view of the SSCP–SP interaction, validates the results through a theoretical lens (NRBV and IBV) and generalises the results by evaluating the moderation effects via checking prior literature.

This study aims to explore the impact of supply chain quality event (SCQE) announcements on enterprises’ stock market value.

This study adopts the event study approach and analyzes the changes in shareholder value of companies listed in China based on data from 118 SCQE announcements. In the event study, the market, market-adjusted and Carhart four-factor models are used to estimate abnormal stock market returns, and a cross-sectional regression model is performed to examine the effects of SCQE announcements on enterprises’ stock market value.

SCQE announcements have a negative impact on shareholder value. From the perspective of the supply chain network structure, the market reacts more negatively to SCQE announcements issued by the enterprises with higher supply chain concentration. From the perspective of companies’ characteristics, announcements that do not reflect the establishment of supply chain quality cooperation have a more negative effect on stock market value, which indicates that the supply chain network structure and firm-level characteristic can moderate the market reaction.

The findings demonstrate a quantitative evaluation of how SCQE announcements affect the stock market value of listed companies and provide guidance for managers to enhance the value of SCQE announcements.

This study fills the research gap on the impact of SCQE announcements on stock market value by using secondary data and first explores the relationship between SCQE announcements and stock market value from the perspective of supply chain network. Furthermore, this study contributes to the literature on SCQE using an empirical study in China.

Sustainable supply chain management (SSCM), driven by the downstream buyers' power, transfers sustainability responsibilities to the upstream supplier. In contrast to the heavily-focused buyers' perspective in the literature, the authors investigate how this buyer-driven SSCM influences suppliers' performance, using the measure of stock market reaction.

Grounded by the resource dependence theory (RDT), the authors empirically analyze the power effect on suppliers. Event study methodology and regression analysis are used, based on a sample of 1977 paired supplier observations from 1990 to 2016.

The result suggests that although a negative stock market reaction for suppliers in SSCM exists, the effect is less negative at a high level of buyer and supplier dependence. For the investigation of the “consolidated SSCM initiative,” where buyers acquire exogenous power by collaboratively managing SSCM with their peers, the authors uncover that the negative impact of this consolidated SSCM initiative can be mitigated by the high interdependence that generates relational norms in the dyads.

The authors focus on dyadic relationships. Future research can use the study's findings to study the SSCM diffusion to lower-tier suppliers.

This paper has good managerial implications for both suppliers and buyers. The authors propose dependence-based strategies for supplier managers to reduce uncertainty in SSCM. Moreover, buyer managers can use the study's findings to strengthen suppliers' commitment.

The novelty of examining the suppliers' perspective contributes to exploring the supply chain impact of SSCM. The authors extend RDT and show that high dependence is not necessarily detrimental to suppliers in this buyer-driven SSCM context. The interesting finding of interdependence in the context of the consolidated SSCM initiative brings new insights that relational norms constrain the leverage of power in the dyads and are beneficial to the power-disadvantageous suppliers.

This study aims to explore the impact of blockchain announcements on enterprises' stock market value.

Based on resource-based theory, this study constructs a complete framework of the impact mechanism of blockchain announcements on the stock price of the announcing firm using the data of 143 blockchain announcements. An event study methodology is used in this research, and the market model, market-adjusted model and Carhart four-factor model are used to estimate stock abnormal returns after the blockchain announcement; and the cross-sectional regression model is used to test the influencing factors.

Blockchain announcements elicit a significantly positive market reaction on the release day. Compared to announcements not pertaining to technical innovation, blockchain technical innovation announcements exhibit a more positive market reaction towards the announcing companies. Strategic-level announcements exhibit a more positive market reaction than operational-level announcements. Enterprise characteristics, such as enterprise-scale and enterprise innovation ability, do not affect stock market reactions to blockchain announcements.

The findings reveal the economic value of conducting blockchain activities in the Chinese stock market. Findings of this study can help managers understand the value of implementing blockchain activities in a different market environment and guide them on how to improve the market value of their enterprises through the active implementation of blockchain activities.

To the best of the authors’ knowledge, this is the first event study to focus solely on the value of pure blockchain announcements in an emerging market. This study considers multiple resource and capability factors that would influence blockchain technology adoption, improve the current understanding of how blockchain announcements affect corporate stock prices and provide directions for future comparative studies of market reactions to blockchain announcements in different stock markets.

The purpose of this paper is to explain why fashion companies would “go green” and to evaluate business models and sustainable supply chains. By applying the Five‐R framework, the authors further evaluate the initiation, implementation and institutionalization journey of a local fashion company and generate important insights and findings.

It is an exploratory qualitative study. The Five‐R conceptual framework is reviewed, proposed, and applied for a real case analysis.

From the studies, data and literature gathered and analyzed hitherto, it is evident that fashion companies can seize competitive advantage through strategic management of environmental challenges. In their greening initiatives, fashion companies should strongly consider the product development process and extend stewardship across the multiple life‐cycles of products. The Five‐R framework, together with its future extensions, can offer an opportunity to clearly display what has been achieved by the company at present and also succinctly demonstrate what area the company is lacking in or where there is room for further beneficial development.

This research focuses on examining the scenario of one real company. The findings need not be generalized and applicable to all companies: this is a major research limitation of this study.

The research findings can help explain and conceptualize fashion companies’ journal of going‐green. Some specific recommendations are given and managerial insights are generated.

This paper undertakes a qualitative real case analysis to study green supply chain management (SCM) challenges by applying the Five‐R framework. The authors believe that this study belongs to the first group of research works which specifically examine this area in the domain of fashion marketing and management.

The fashion industry faces more challenges from demand uncertainty than many other businesses because it creates products that are highly seasonal with short lifetimes and demand is inherently volatile. Such a situation introduces difficulties in fashion supply chain management. The solution to the agile supply chain involves setting up seamless or boundary-less connections between supply chain members. These connections can minimize buffers between the different stages in the chain. In an agile network, such connection is critical and can be enabled by web-software, allowing different actors to be connected without needing to have the same computer system. With integrated web systems, businesses in different geographical locations can behave as if they belong to the same enterprise. The forecasting of future sales is one of the key constituents of these solutions. Today’s enterprises in fashion often employ various IT services in supply chain operations and a forecasting system is often expected to be accessible by independent users and systems through a standardized interface. Therefore, web-software is the right solution in this circumstance. There are many methods in the sales forecasting field. In this paper, we focus on exploring the implementation of a web-based forecasting system in which various forecasting methods can be utilized. This web-based forecasting system is expected to bring great flexibility into fashion enterprise operations and enhance their supply chain management. A case analysis is presented in the paper in which a neural network is utilized as the forecasting method. We believe that the implementation mechanism is highly applicable to help fashion companies in improving their operations.

This paper aims to study the shopping preferences of the mainland Chinese travelers who visit Hong Kong under the solo travel policy (STP), and identify the differences between their expected and actual satisfactory levels towards fashion retailers in Hong Kong.

An empirical research method with surveys was employed. Statistical methods, such as the paired t‐test, were used to analyze the data.

A significant difference between the respondents' actual shopping satisfactions and their expectations was found for several factors. Some shopping preferences and spending patterns of the STP travelers were identified.

Owing to resource constraints, the data were collected at a few locations only. This is a major research limitation of this study.

The research findings can help fashion retailers to understand better the needs of STP travelers from mainland China. Some specific recommendations are given and managerial insights are generated.

This paper undertakes empirical research to study mainland tourists' shopping behavior towards Hong Kong fashion retailers under the STP. This study is one of the first research works exploring this area.