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The purpose of this paper is to provide an overview of the evolution of service supply chain management from a behavioural operations perspective, pointing out future research directions for scholars.

This study searched five databases for relevant literature published between 2009 and 2018, selecting 64 papers for this review. The selected literature was categorised according to two dimensions: a service supply chain link perspective and a behavioural factor perspective. Comparative analysis was used to identify gaps in the literature, and five future research agendas were proposed.

In terms of the perspective of service supply chain link, extant literature primarily focuses on service supply and service co-ordination management, and less on service demand and integration management. In terms of the behavioural factor’s perspective, most focus on classic behaviour factors, with less attention paid to emerging behaviour factors. This paper thus proposes five research agendas: demand-oriented management and integrated supply chain-oriented behavioural research; broadening the understanding of the scope of behavioural operations; integrating the latest backgrounds and trends of service industry into the research; greater attention to behavioural operations in service sub-industries; and multimethod combination is encouraged to be used to dig into the interesting research problems.

This study constitutes the first systematic review of service supply chain research from a behavioural perspective. By categorising the literature into two dimensions, the state of existing research is evaluated with an eye towards future research avenues.

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.

Using social network theory (SNT), this study empirically examines the impact of digital supply chain announcements disclosing corporate social responsibility (CSR) information on stock market value.

Based on 172 digital supply chain announcements disclosing CSR information from Chinese A-share listed companies, this study uses event study method to test the hypotheses.

First, digital supply chain announcements disclosing CSR information generate positive and significant market reactions, which is timely. Second, strategic CSR and value-based CSR disclosed in digital supply chain announcements have a more positive impact on stock market, however there is no significant difference when the CSR orientation is either towards internal or external stakeholders. Third, in terms of digital supply chain network characteristics, announcements reflecting higher relationship embeddedness and higher digital breadth and depth lead to more positive increases of stock value.

First, the authors consider the value of CSR information in digital supply chain announcements, using an event study approach to fill the gap in the related area. This study is the first examination of the joint impact of digital supply chain and CSR on market reactions. Second, compared to the previous studies on the single dimension of digital supply chain technology application, the authors innovatively consider supply chain network relationship and network structure based on social network theory and integrate several factors that may affect the market reaction. This study improves the understanding of the mechanism between digital supply chain announcements disclosing CSR information and stock market, and informs future research.

This study explores the influencing factors of smart supply chain innovation (SSCI) for going global companies and designs a theoretical framework.

This paper is a multi-case study that includes a combination of exploratory and explanatory case studies.

First, the authors find that SSCI is embodied in product development and supply chain empowerment, which represent exploitative innovation and explorative innovation, respectively. Meanwhile, supply chain empowerment has a positive impact on product development. Second, the going global policy affects the transformation of supply chain empowerment to SSCI practices. Third, in terms of exploitative innovation, personalized demand positively affects SSCI through product development. Finally, explorative innovation, including emerging technology application and supply chain ecologicalization, has a positive effect on supply chain empowerment and thereby affects SSCI.

Supply chain innovation in the context of a smart economy has gained great popularity. This study sheds light on the influencing factors and mechanisms of SSCI from the exploitative and explorative aspects of innovations.

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.

This study explores the influencing factors on organizational efficiency of the smart logistics ecological chain, and designs the corresponding theoretical framework to guide the practice of enterprises

A multi-case study method is adopted in this study. It includes four companies A, B, C and D in China as the case study objects, collects data through enterprise survey and uses the combination of open coding and spindle coding to process the data. By testing the reliability and validity, the theoretical framework is summarized.

First, organizational efficiency in smart logistics ecological chains is directly related to their service and technology innovation capability. Second, symbiotic relationships, information sharing and customer demand affect the efficiency of smart logistics multi-case ecological chains by influencing their service capacity; their technological innovation capability regulates the mechanism of influence. Third, technological innovation in smart logistics ecological chains positively impacts their service capabilities. Improving technological innovation capability can enhance logistics service capabilities.

According to the characteristics of smart logistics, the theoretical framework about organizational efficiency of smart logistics ecological chain is constructed, which fills the research gap and can provide interesting perspectives for the future research related to the smart logistics ecological chain. At the same time, the findings can also help enterprises to better build the smart logistics ecological chain in practice.

Determining the variation law of the oxygen concentration in the ullage space of the fuel tank is the key to the design of the inert system. Among various factors affecting the oxygen concentration in the ullage space of the fuel tank, the temperature difference between day and night shows particular importance while relevant analysis and calculation are scarce.

This study establishes a theoretical simulation model of the central wing fuel tank of an aircraft according to the relevant provisions of day-night temperature variation in FAR25 airworthiness regulations, verifies the model with the existing experimental data and discusses the corresponding relationship between the oxygen concentration in the ullage space of the fuel tank and the day-night temperature difference. The influence of day and night temperature difference, fuel type, fuel load rate, initial oxygen concentration, dissolved oxygen evolution and other factors on the oxygen concentration in the ullage space of the fuel tank were analyzed, and the limit of initial oxygen concentration of the fuel tank before the shutdown at night meeting the requirements of the airworthiness provisions was proposed.

The results show that the temperature difference between day and night, fuel load rate, initial oxygen concentration and other factors have different effects on the oxygen concentration in the ullage space of fuel tank. The initial oxygen concentration limit before shutdown shall be 2% below the 12% oxygen concentration stipulated by FAA.

The research results in this paper will be of good reference value to the design of the inert system and the calculation of the flammability exposure evaluation time. This paper aims to be good reference of the design of the inert system and the calculation of the flammability exposure evaluation time.

The research results of this paper can provide practical guidance for the current civil airworthiness certification work.

This study explores the impact of carbon neutrality policies on Chinese stock market from a supply chain perspective. Specifically, the carbon policy refers to the Action Plan for Carbon Dioxide Peaking Before 2030 (the Plan) in China.

This paper is based on the resource dependence theory (RDT) and applies the event study methodology to explore the impact. It uses the cross-sectional regression model to reveal the moderating effect of supply chain characteristics on the stock market reaction with a data set of 354 listed companies in A-shares (excluding ChiNext and SME board).

The promulgation of the Plan shows a significant negative stock market reaction. Customer concentration, out-degree centrality and smart supply chains (SSCs) have a significant negative moderating effect. In-degree centrality and supplier concentration have a significant positive moderating effect. Furthermore, the conclusions concerning out-degree centrality, supplier concentration and SSCs are counterintuitive.

For policymakers, the study results provide a reference for evaluating the carbon neutrality policy. For managers, this study provides theoretical support for strategically adjusting and designing supply chain structures in the context of advocating peak carbon dioxide emissions and carbon neutrality.

This paper is the first attempt that includes the supply chain structure factors into the impact of carbon neutrality policies on the stock market.

The review aims to facilitate a broader understanding of platform opening and cooperation and points out potential research directions for scholars.

This study searches Web of Science (WOS) database for relevant literature published between 2010 and 2021 and selects 86 papers for this review. The selected literature is categorized according to three dimensions: the strategic choice of platform opening and cooperation (before opening), the construction of an open platform (during opening) and the impact of platform opening and cooperation (after opening). Through comparative analysis, the authors identify research gaps and propose four future research agendas.

The study finds that the current studies are fragmented, and a research system with a theoretical foundation has not yet formed. In addition, with the development of platform operations, new topics such as platform ecosystems and open platform governance have emerged. In short, there is an urgent need for scholars to conduct exploratory research. To this end, the study proposes four future research agendas: strengthen basic research on platform opening and cooperation, deeply explore the dynamic evolution and cutting-edge models of platform opening and cooperation, analyze potential crises and impacts of platform openness and strengthen research on open platform governance.

This is the first systematic review on platform opening and cooperation. Through categorizing literature into three dimensions, this article clearly shows the research status and provides future research avenues.

It is an indispensable part of airworthiness certification to evaluate the fuel tank flammability exposure time for transport aircraft. There are many factors and complex coupling relationships affecting the fuel tank flammability exposure time. The current work not only lacks a comprehensive analysis of these factors but also lacks the significance of each factor, the interaction relationship and the prediction method of flammability exposure time. The lack of research in these aspects seriously restricts the smooth development of the airworthiness forensics work of domestic large aircraft. This paper aims to clarify the internal relationship between user input parameters and predict the flammability exposure time of fuel tanks for transport aircraft.

Based on the requirements of airworthiness certification for large aircraft, an in-depth analysis of the Monte Carlo flammability evaluation source procedures specified in China Civil Aviation Regulation/FAR25 airworthiness regulations was made, the internal relationship between factors affecting the fuel tank flammability exposure time was clarified and the significant effects and interactions of input parameters in the Monte Carlo evaluation model were studied using the response surface method. And the BP artificial neural network training samples with high significance factors were used to establish the prediction model of flammability exposure time.

The input parameters in the Monte Carlo program directly or indirectly affect the fuel tank flammability exposure time by means of the influence on the flammability limit or fuel temperature. Among the factors affecting flammability exposure time, the cruising Mach number, balance temperature difference and maximum range are the most significant, and they are all positively correlated with flammability exposure time. Although there are interactions among all factors, the degree of influence on flammability exposure time is not the same. The interaction between maximum range and equilibrium temperature difference is more significant than other factors. The prediction model of flammability exposure time based on multifactor interaction and BP neural network has good accuracy and can be applied to the prediction of fuel tank flammability exposure time.

The flammability exposure time prediction model was established based on multifactor interaction and BP neural network. The limited test results were combined with intelligent algorithm to achieve rapid prediction, which saved the test cost and time.