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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 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 purpose of this paper is to analyze the influencing factors of new logistics service product design (NLSPD) in China to establish a theoretical framework for the future development of the logistics industry.

The paper adopts the multi-case study method based on a sample of four Chinese logistics enterprises, in which the authors consider the logistics service maturity (LSM), a distinct characteristic of logistics enterprises.

NLSPD is directly related to the degree of supply–demand matching (SDM) and LSM. Customer demand, service capability and peer competition influence the performance of NLSPD through the SDM degree, whereas LSM moderates these influencing mechanisms. Moreover, the degree of SDM has a positive impact on LSM.

The findings can help the managers of logistics enterprises and practitioners in the logistics industry understand the complexity of NLSPD. First, they should broaden and deepen their service offering to enhance the degree of LSM. Second, they should pay attention to the factors that affect SDM systematically. Finally, it is vital to balance the relationship between LSM and SDM.

NLSPD has become an important tool affecting the competitiveness and sustainability of logistics service enterprises. This is the first paper to propose a theoretical framework for NLSPD that considers the characteristic of the logistics industry. It clarifies the mechanisms of influencing factors, and contributes to the literature by filling the research gap.

Oil is the natural resource recognized as the most important source of revenue in oil-dependent countries and is most often referred to as being susceptible to corruption owing to its strategic importance. A major challenge in addressing and encountering the problems in complex social systems, such as corruption, is how to structure the problematic situation and how to capture mental models of the stakeholders involved in the situation, and also how to identify the system’s behavior in response to various policy intervention attempts in the long run. This study aims to shed new lights on modeling and simulating corrupt system of the oil industry, as a complex social system needed to be structured according to social system theories’ principles.

Parson’s theory is applied as a basic framework to capture the complexities of a corrupt system, dividing the system into political and structural, economic, legal and judicial and cultural and social sub-systems. Then soft system dynamics methodology, which is a combination of the two well-known methodologies, soft system methodology and system dynamics, is applied to model and simulate the complexities involved in the oil industry of Iran, which owns the second-largest oil reservoir in the world and its economy is much dependent on the oil revenue, struggles with corruption, and plans for a large amount of anti-corruption activities.

After simulating and calibrating the model, three groups of policies, namely, “reducing corruption opportunities,” “reducing corruption demand,” and “increasing anti-corruption capacity” are implemented in the model. As to the simulation results, due to the mutual inter-causality of opportunity and demand for corruption, individual application of each group of policies will not be helpful for long, rather a combination of policies will conduce to substantial improvements in declining corruption in the oil industry.

The developed model addresses the dynamics of the complex socio-economic system of corruption in the system of oil industry via modeling and simulation. The developed four-dimension system dynamics framework could be considered as a guidance for corruption modeling in general and as a basic model for corruption modeling of oil-dependent countries’ systems in particular.

This chapter explores the contribution of The Open University (OU) Library to influencing curriculum decisions about embedding digital and information literacies in an online environment. Recommendations can be applied to higher education (HE) institutions as they develop permanent e-learning strategies to prepare for a long-term solution to online learning experiences. Learning providers are creating strategies for online content creation, student engagement, and skills development. It is an opportunity to demonstrate their value by making an effective transition to online learning, streamlining services to create student-centered experiences.

It investigates existing e-pedagogical approaches developed pre- and during the COVID-19 pandemic to embedding digital literacies in practice, drawing on the OU’s experience of developing effective frameworks for online teaching programs. The aim is to review institutional preparedness for effective transition, so that staff members and students can adapt to post-COVID realities. This draws upon student-centered, holistic design of programs to embed accessible and inclusive processes in distance learning, utilizing technological solutions to create optimal teaching and learning environments.

It will also make recommendations about how embedding digital literacies within the curriculum will equip graduates for post-education experiences within working and social contexts, by building activities into module that develop digital capabilities. For effective learning experiences to take place, institutions require development of born-digital support material to develop staff confidence and ability to produce effective, accessible online learning objects. As more organizations move to online, hybrid, and flipped learning interventions, high-level university strategy can future-proof learning design by developing the support that staff need to provide the best experiences for their learners.

The purpose of this paper is to study how supermarkets can maximize profits of selling perishable food through price adjustment based on real‐time product quality and values.

The value of the perishable food can be traced based on an automatic product identification technology radio frequency identification (RFID). With the support of the RFID, an optimization model can be developed to enable product tracking.

The analysis of the model shows promising benefits of applying a dynamic pricing policy and obtains the optimal ordering decision in respects of deterministic and stochastic demand function with RFID.

Although technological approaches for tracking products have attracted increasing attentions in both research and practice, little research have proved the profit using RFID by mathematics, the result of this paper can prove the benefit by using RFID.

The result of this paper can tell the supermarket how to make the price and the ordering decision by using the RFID.

This study proves the benefit of using the RFID by mathematical model based on the conceptual model before, and tell the method how to use RFID for pricing and making ordering decision.

The concept of the customer order decoupling point (CODP) has been used in many different contexts as an important structural concept for the traditional forward supply chain. The CODP is rarely explicitly applied in reverse supply chain management and the purpose of this paper is to show that the CODP can be an important corner stone of a framework for analysis of the closed‐loop supply chain containing both forward and reverse material flows.

Conceptual similarities are identified using analogies between forward and reverse supply chains. First, the concepts are discussed in their original context of forward flows and thereafter the concepts are applied on reverse flows. Finally, a holistic closed‐loop model is established.

The conventional CODP framework for forward flow supply chains can be extended to cover also reverse material flows and therefore providing a foundation for a more comprehensive discussion of closed‐loop supply chains useful in both education, research, and industrial applications. Using the suggested extended framework it is possible to identify nine fundamental supply chain configurations.

Differentiating between demand driven and forecast driven activities plays a critical role in practical supply chain management and this paper highlights that this approach also can be applied to closed‐loop supply chains and therefore extending the reach of the toolbox previously developed for the forward supply chain.

The concept CODP has not previously been comprehensively treated for the closed‐loop supply chain and this paper provides a foundation for establishing a strategic structural framework for discussing issues such as lean vs agile and balancing efficiency and responsiveness in a more comprehensive context involving also reverse material flows.

This study aims to consider the influence of density difference integral and relative flow difference on traffic flow, a novel two-lane lattice hydrodynamic model is proposed. The stability criterion for the new model is obtained through the linear analysis method.

The modified Korteweg de Vries (KdV) (mKdV) equation is derived to describe the characteristic of traffic jams near the critical point. Numerical simulations are carried out to explore how density difference integral and relative flow difference influence traffic stability. Numerical and analytical results demonstrate that traffic congestions can be effectively relieved considering density difference integral and relative flow difference.

The traffic congestions can be effectively relieved considering density difference integral and relative flow difference.

Novel two-lane lattice hydrodynamic model is presented considering density difference integral and relative flow difference. Applying the linear stability theory, the new model’s linear stability is obtained. Through nonlinear analysis, the mKdV equation is derived. Numerical results demonstrate that the traffic flow stability can be efficiently improved by the effect of density difference integral and relative flow difference.

This paper aims to put forward an extended lattice hydrodynamic model, explore its effects on alleviating traffic congestion and provide theoretical basis for traffic management departments and traffic engineering implementation departments.

The control method is applied to study the stability of the new model. Through nonlinear analysis, the mKdV equation representing kink-antikink soliton is acquired.

The predictive effect and the control signal can enhance the traffic flow stability and reduce the energy consumption.

The predictive effect and feedback control are first considered in lattice hydrodynamic model simultaneously. Numerical simulations demonstrate that these two factors can enhance the traffic flow stability.

The purpose of this study is to explore the influence of the electronic throttle (ET) dynamics and the average speed of multiple preceding vehicles on the stability of traffic flow.

An extended car-following model integrating the ET dynamics and the average speed of multiple preceding vehicles is presented in this paper. The novel model’s stability conditions are obtained by using the thought of control theory, and the modified Korteweg–de Vries equation is inferred in terms of the nonlinear analysis method. In addition, some simulation experiments are implemented to explore the properties of traffic flow, and the results of these experiments confirm the correctness of theoretical analysis.

In view of the results of theoretical analysis and numerical simulation, traffic flow will become more stable when the average speed and ET dynamics of multiple preceding vehicles are considered, and the stability of traffic flow will also be enhanced by increasing the number of preceding vehicles considered.

This study leaves the factors such as the mixed traffic flow, the multilane and so on out of account in real road environment, which more or less influences the traffic flow’s stability, so the real traffic environment is not fully reflected.

There is little research integrating ET dynamics and the average velocity of multiple preceding vehicles to study the properties of traffic flow. The enhanced model constructed in this study can better reflect the real traffic, which can also give some theoretical reference for the development of connected and autonomous vehicles.