Chinese Logistics Research Articles

Can logistics enterprises improve their competitiveness through ESG in the context of digitalization? Evidence from China

PurposeThis investigation endeavors to examine the routes by which environmental–social–governance (ESG) performance influences the competitive landscape for logistics enterprises, with a particular emphasis on the function of digitalization in this complex process. The research underscores the significance of the ESG context in the realm of digitalization, providing valuable insights into its impact on the overall competitiveness of logistics enterprises.Design/methodology/approachThis research gathers information from a total of 90 logistics enterprises that are publicly traded on the Shanghai and Shenzhen A-share stock markets for analysis and model testing. Due to the multiple pathways of influence and the constrained size of the sample, it has been decided that the Piecewise structural–equation–modeling (SEM) approach will be employed.FindingsThe research reveals that ESG factors positively impact enterprises' competitiveness (EC). The augmentation of competitiveness is attributed to the moderating role of green technology innovation (GTI) and agency costs between ESG and EC. In the context of digitalization, the level of digitalization of logistics enterprises may create a capital squeeze effect on environmental performance, weakening competitiveness. Conversely, the level of digitalization positively regulates the promoting effect of governance performance on competitiveness.Originality/valueThis research provides a sound theoretical foundation for understanding how ESG contributes to boosting the competitiveness of Chinese logistics enterprises and extends the application of Piecewise SEM in the research field of logistics enterprise competitiveness. Furthermore, it offers a practical pathway for companies to implement ESG practices and foster competitiveness in digital environments.

Uplift modeling and its implications for appointment date prediction in attended home delivery

Successful attended home delivery (AHD) is the most important aspect of e-commerce order fulfillment. Prior literature focuses on incentive scheme development for customers' choices of delivery windows and predictive analytics for delivery results, but it is not clear whether the effect of AHD on the appointment date set by customers increases the success rate of AHD. Therefore, we developed an uplift modeling method, PSM-NDML, as a relevant prescriptive analytic tool for AHD on an appointment date, which aims to estimate the causal effect of the by-appointment delivery on the delivery result. PSM-NDML integrates propensity score matching and double machine learning, effectively addressing sample selection bias, low predictive performance, and poor interpretability. Applied to a real-world product delivery dataset of a Chinese logistics company, PSM-NDML achieves superior performance relative to ten other state-of-the-art uplift models in terms of cumulative gain and the Qini coefficient. The predicted responses gained from PSM-NDML are also visually interpreted at the global and local levels, which reveals various managerial insights. In practice, the findings expand managers' understanding of the heterogeneous effects of AHD on appointment dates and provide decision support for logistics companies in the development of home delivery plans.

Research on value creation path of logistics platform under the background of digital ecosystem: Based on SEM and fsQCA methods

Digitalization and platform ecosystem have subverted the value creation mode between traditional logistics actors and brought new value additions. Few studies have been done to investigate the influencing factors prompting such value creation of digital platform ecological cooperation in the Chinese logistics industry. The study bridges the gap by using structural equation modeling and fuzzy-set qualitative comparative analysis methods to investigate data from 347 Chinese logistics firms cooperating under the logistics platform. Findings:(1) identification of customer value proposition, complementary cooperation, and multi-party interaction had an indirect influence on logistics service value realization. While transaction cost reduction and digital innovation had a direct influence. (2) Digital capabilities have a positive moderating effect on the relationship between transaction cost reduction and value realization. (3) Comparing the configurations of value realization and ～value realization, it is found that enterprises cannot create value if they only save costs without operation, and should improve digital capabilities to reduce transaction costs. At the same time, the identification of customer value proposition is the source of value creation.

Destination country’s institutional quality and Chinese E-commerce exports

This paper constructs a unique dataset of Chinese firm-level bilateral cross-border e-commerce exports using the back-end online logistics database of a famous Chinese logistics platform to study the impact of destination country’s institutional quality on Chinese cross-border e-commerce export. Our results show that the institutional quality of destination countries significantly boosts China’s cross-border e-commerce exports. Institutional quality has a more significant effect on the extensive margin than the intensive margin. Mechanism analysis shows that institutional quality significantly stimulates export entry, export survival, and continuous exports. Furthermore, destination country’s institutional quality has a greater impact on cross-border e-commerce export than on traditional export.

The Influence of Block-Chain Technology in Chinese Smart Logistics

Block-chain technology is an advanced database mechanism that allows information to be shared transparently within an enterprise network. The scale of Chinese logistics market is developing rapidly, whether it is e-commerce express delivery, cold chain transportation, international trade logistics and other fields, it is developing rapidly. Through an overview of block-chain and smart logistics, this paper discusses the feasibility and advantages of using block-chain in smart logistics. Including block-chain technology and the decentralization of smart logistics transaction subjects, efficient transaction mechanism, and transaction process security to discuss the important role of block-chain in smart logistics. At the same time, it analyzes the practical application of block-chain in SF Express, and analyzes the integration and development of block-chain and smart logistics. And at the end, it puts forward suggestions and prospects for the development of block-chain in smart logistics in the future.

Perspectives for the development of safe-ecosystems based on 5-pl logistics in Russia

The purpose of this research is to assess the prospects for the development of the Russian transport and logistics services market in the 5PL logistics segment as a basis for the development of safe ecosystems based on the active introduction of digital technologies into the supply chain. The research allows us to identify the key features of the introduction, application and development of the digital logistics segment of the People’s Republic of China and to reveal the features of using the practical experience of the People’s Republic of China in order to create and operate a digital logistics platform in Russia. Methods: comparative analysis of statistical data on the volume and speed of cargo transportation is used; analysis of the logistics sector to assess the level of regulation and government influence on the development of this industry and characteristics of the level of automation and application of modern IT solutions in the logistics sector of both countries according to their impact on efficiency and competitiveness. Results: the features of the formation of 5PL logistics in the People’s Republic of China are established, taking into account both the unique conditions for the development of transportation logistics and the advantages of digital progress penetrating into all spheres of the Chinese economy; the conditions for the promising development of the 5PL system provider format in Russia are determined; the current parameters of the functioning of the 5PL system of the People’s Republic of China with recommendations for their application in the territory are highlighted In order to increase the efficiency and competitiveness of the national transport and logistics system. Practical significance: the results obtained are of an applied nature, since they propose and justify a number of measures aimed at optimizing the logistics sector in Russia, based on the experience of the Chinese logistics services market with increasing momentum in the development and development of 5PL systems.

Roles of top management support and compatibility in big data predictive analytics for supply chain collaboration and supply chain performance

With the global digitalisation, big data has received growing attention from academicians and practitioners. However, only a few empirical studies examined the benefits of big data predictive analytics (BDPA) and its influence on supply chain collaboration (SCC) and supply chain performance (SCP). Addressing the identified gaps of the implementation of organisational information processing theory (OIPT), the current study provided the foundation to develop a conceptual framework. All relevant data were collected from 197 employees in the Chinese logistics industry. Partial least squares–structural equation modelling technique was performed. The obtained empirical results supported top management support and compatibility as critical factors for the adoption of BDPA. Moreover, BDPA exhibited positive influence on SCC and SCP. Additionally, SCC mediated the relationship between BDPA and SCP. This study presented significant theoretical contributions and provided guidelines that can benefit policymakers and organisations in the efforts of implementing BDPA for enhanced SCP. After all, improving SCP would benefit customers and the society in the case of reduction and wastage of resources.

The Analysis of Environmental Practices of Chinese Logistics Service Providers Based on the Avoid-Shift-Improve Framework

With the rapid development of the logistics industry, the environmental impact and environmental social responsibility of logistics service providers (LSP) are increasingly being considered by government policies and the public. The environmental management status of domestic logistics service providers and their actions need to be further analyzed. This paper takes domestic logistics service providers as the main body of research, based on the text information of a corporate social responsibility report, and uses the framework of Avoid-Shift-Improve (A-S-I) to make a structural analysis of the environmentally sustainable practices of enterprises in order to provide policy suggestions for improving the green development practices of the logistics industry from the micro perspective of enterprises.

Environmental Sustainability Practices of Chinese Logistics Service Providers: A Perspective on Corporate Social Responsibility

Guided by the strategic objectives of "carbon neutrality" and "peak carbon" in China, low-carbon development in the logistics industry has become a core driver of industry transformation and upgrading. At the micro-level, companies are gradually accelerating their environmental strategic planning and actively promoting environmental sustainability practices. This paper focuses on logistics service providers (LSPs) and selects representative integrated logistics service companies for multidimensional analysis of corporate social responsibility report information. The paper analyzes the characteristics of environmental sustainability practices in companies from the perspectives of transportation strategies, green packaging, green buildings, and circular economy. Policy recommendations for the low-carbon and green development of Chinese logistics service providers are provided.

Social Network and Resources Integration Within Logistics Industry in China --- With Case Study of Cainiao Network

The business network in logistics industry is essential for integrating resources and establish firms own advantage of compettitiveness in the market, as well as providing more comprehensive services that facilitate firms to gain its revenue. Construction of intermediary platforms has therefore been an effective mean. Cainiao, a subdivided branch of Chinese giant enterprise Alibaba, has seized this opportunity. Though the debate about how social networks function to boost the high-quality development of firms has been very hot over the last three decades, few studies have mentioned and worked to understand to the linkage between social network analysis (SNA) and logistics chain management. Hence, the purpose of this research is to identify the construction of a business network by the giant Chinese logistics companies and its enhancing function of collaboration among firms and embeddedness for the success of Cainiao, which constructs the whole network. This paper will be carried out in concept explaination of essential terms in SNA and the practice of them into operation of Cainiao Network, as well as some diagrams made by Ucinet software will be applied. Results of the study show that through the early alliance of giant express enterprises, Cainiao has gained a wide network map that permits it to utilize abundant resources for the firms prosperity, and boosts the conjunction between the other companies and customers.

Evaluation of the Environmental Cost of Integrated Inbound Logistics: A Case Study of a Gigafactory of a Chinese Logistics Firm

In recent years, sustainable development has become an emerging trend in the logistics industry. Smart manufacturing factories pursue green logistics processes with lower energy consumption and reduced carbon emission. The environmental sustainability of the logistics process is widely acknowledged as an important issue. However, a standardized methodology for assessing the environmental cost of logistics-process-aided smart manufacturing is lacking. This paper presents a concept for determining the inbound logistics environmental cost (ILEC) of a gigafactory. Additionally, a novel structured methodology for ILEC assessment is proposed to uniformly describe the gigafactory’s logistics environmental cost, regarding the “double carbon” goal (peak carbon dioxide emissions and carbon neutrality). First, eight types of basic logistics activities and six logistics phases associated with the gigafactory’s inbound logistics are defined. The mapping relationships between the logistics phases and the basic logistics activities are constructed. Then, the novel concepts of environmental price cost (EPC) and environmental impact cost (EIC) are defined and presented. Finally, the ILEC of the gigafactory, including EPC and EIC, is assessed based on mapping relationships and an environmental cost model. We validate this model using the advanced Geely Automobile factory in China in order to analyze the actual inbound logistics environmental costs and how to assess its environmental price and environmental impact. Results from the data model show the environmental costs throughout the whole process and the detailed composition ratio of EPC and EIC in the inbound logistics. Based on the implementation of the ILEC model, our study helps gigafactories to identify critical logistics nodes through energy consumption and to measure the environmental performance of the inbound logistics process. Furthermore, our study helps gigafactories to develop practical environmental strategies.

Does green technology innovation contribute to logistics companies’ market value? The effects of stakeholder engagement and public attention

Although logistics companies are encouraged to carry out green technology innovation (GTI) to mitigate their carbon footprint and negative environmental impact, the performance effect of GTI still needs more conclusive evidence. Building on the resource-based view and stakeholder theory, we investigate the impact of logistics companies’ GTI on their market value and further explore the moderating effects of stakeholder engagement and public attention. We use panel data from 53 publicly listed Chinese logistics companies between 2011 and 2021 to test our hypothesized model. We find an inverted U-shaped relationship between GTI and market value. Interestingly, supply chain partner engagement steepens the inverted U-shaped GTI–market value linkage, whereas scientific institution engagement flattens this curvilinear linkage. In addition, public attention weakens this inverted U-shaped GTI–market value relationship. Our study extends the logistics literature by untangling the curvilinear GTI–market value relationship and the distinct moderating effects of stakeholder engagement and public attention on this relationship. It also provides managerial advice for managers in the Chinese logistics industry.

Financing constraints and impact on corporate performance growth: Study in China listed logistics enterprises.

Based on 2010-2019 Chinese logistics listed companies as research samples, the paper used the binary Logit model measuring degree of financing constraints. The Kernel density function and Markov chain model are used to forecast China listed companies financing logistics dynamic constraints and business performance growth. Furthermore the stock of knowledge was chosen as a threshold variable to explore the impact of financing constraints on corporate performance growth of listed logistics enterprises. We find that the degree of financing constraints of logistics enterprises in our country has not been significantly eased. Corporate performance has not changed significantly and there are no obvious spatial gap and polarization with the passage of time. The impact of financing constraints on the corporate performance growth of logistics enterprises in China has a double threshold effect of knowledge stock, and has an inhibitory effect that first increases and then decreases. This is because in the short term, the investment of knowledge stock by enterprises can crowd out more corporate liquidity, and in the long run, it is related to the conversion rate of the knowledge stock itself. Because of the uneven regional distribution of resources and differences in the degree of economic development, there is a growing disincentive effect in central China as the stock of knowledge accumulates.

Identifying business information through deep learning: analyzing the tender documents of an Internet-based logistics bidding platform

PurposeThe tender documents, an essential data source for internet-based logistics tendering platforms, incorporate massive fine-grained data, ranging from information on tenderee, shipping location and shipping items. Automated information extraction in this area is, however, under-researched, making the extraction process a time- and effort-consuming one. For Chinese logistics tender entities, in particular, existing named entity recognition (NER) solutions are mostly unsuitable as they involve domain-specific terminologies and possess different semantic features.Design/methodology/approachTo tackle this problem, a novel lattice long short-term memory (LSTM) model, combining a variant contextual feature representation and a conditional random field (CRF) layer, is proposed in this paper for identifying valuable entities from logistic tender documents. Instead of traditional word embedding, the proposed model uses the pretrained Bidirectional Encoder Representations from Transformers (BERT) model as input to augment the contextual feature representation. Subsequently, with the Lattice-LSTM model, the information of characters and words is effectively utilized to avoid error segmentation.FindingsThe proposed model is then verified by the Chinese logistic tender named entity corpus. Moreover, the results suggest that the proposed model excels in the logistics tender corpus over other mainstream NER models. The proposed model underpins the automatic extraction of logistics tender information, enabling logistic companies to perceive the ever-changing market trends and make far-sighted logistic decisions.Originality/value(1) A practical model for logistic tender NER is proposed in the manuscript. By employing and fine-tuning BERT into the downstream task with a small amount of data, the experiment results show that the model has a better performance than other existing models. This is the first study, to the best of the authors' knowledge, to extract named entities from Chinese logistic tender documents. (2) A real logistic tender corpus for practical use is constructed and a program of the model for online-processing real logistic tender documents is developed in this work. The authors believe that the model will facilitate logistic companies in converting unstructured documents to structured data and further perceive the ever-changing market trends to make far-sighted logistic decisions.

A Study on Strategy-making of Five Big Chinese Logistics Companies under the Impacts of COVID-19

In this paper, we examine the impact of Covid-19 on the Chinese logistics industry, using both qualitative and quantitative analysis to examine the performance of the top five logistics companies in the months following the initial outbreak in early 2020. The top five companies are Shunfeng, Yuantong, Zhongtong, Shentong, and Yunda. Using a linear regression model and a questionnaire of 251 individuals, we analyze the strengths and weaknesses of the top five companies. We then conclude with our financial recommendations for the five companies, based on our analysis.

Leverage, liquidity, cash flows and company performance of Chinese listed logistics companies during COVID-19 based on multiple linear regression model and data mining

Due to the control policies, company performance is highly affected by the COVID-19 pandemic. This paper aims to examine the impact of leverage, liquidity and cash flows from operations towards company performance of Chinese logistics companies during the COVID-19 crisis. The data are collected from listed logistics companies during 2020-2021, and multiple regression analysis is carried out. Company performance is measured through return on assets and return on equity. The results show that liquidity and cash flows from operations have a positive impact on company performance, while leverage negatively affects company performance. This paper will contribute to the current literature and will aid corporate managers to deal with the COVID-19 crisis.

Dynamic Evaluation of Energy Carbon Efficiency in the Logistics Industry Based on Catastrophe Progression

The logistics industry has an irreplaceable role in promoting Chinese economic development, and its carbon emissions have become a hot topic of academic research. However, more research needs to be conducted on this. This study is based on establishing an evaluation index system for the efficiency of energy carbon emissions in the Chinese logistics industry. The catastrophe progression method was used to evaluate this statically. A dynamic evaluation model was also established based on the characteristics of fuzzy rewards and punishments. The results showed that the static values in the southeastern provinces of China were always between 0.9 and 1, and there was a significant increase in the dynamic values under the fuzzy reward and punishment scenario. Provinces in the southwest fluctuated between 0.8 and 0.95, while the dynamic values did not increase much. In the northern provinces, the static assessment values were consistently between 0.7 and 0.9, while the dynamic values were decreasing. It is therefore important to reward provinces with high static assessment values and penalize those with low static assessment values. The perspective of the characteristics of fuzzy rewards and punishments is also essential for fair and equitable management, reward and punishment in the different provinces in the study.

Economic growth and carbon emissions in Pakistan: the effects of China's Logistics Industry.

The logistics business is a crucial contributor to economic development, yet it is also the leading source of carbon emissions. Economic growth at the expense of environmental deterioration is a challenging issue; this phenomenon offered a new avenue for scholars and policymakers to investigate and address these issues. The recent study is one of the attempts to explore this intricate subject. The goal of this research is to determine whether or not the Chinese logistics sector has an impact on Pakistan's GDP and carbon emissions as a result of CPEC. The research utilized data from 2007Q1 to 2021Q4 using the ARDL approach for an empirical estimate. Due to the mixed order of variable integration and finite data set, the ARDL technique is well deserved, which helps reach sound policy inferences. The study's key results indicated that China's logistic business enhances Pakistan's economic development and carbon emissions in the short and long term. Similarly, China's energy usage, technology, and transportation contribute to Pakistan's economic progress at the price of environmental damage. The empirical study may be a model for other developing nations, given Pakistan's viewpoint. With the support of the empirical results, policymakers in Pakistan and other associated countries would be able to plan for sustainable growth in conjunction with CPEC.

How Internet of Things can influence the sustainability performance of logistics industries – A Chinese case study

The introduction of new information technologies has started reshaping global industrial sectors and supply chains. Due to the introduction of the Internet of Things (IoT) real-time management strategies have been adopted by the global logistics industry, turning the branch into an intelligent service supplier. This paper assesses the influence of IoT on the Chinese logistics sector and related environmental performance between 2011 and 2018. This paper establishes an evaluation framework for the logistics performance under social, economic and environmental dimensions by using time entropy weighting. Using a grey correlation approach, we identify a strong positive correlation between the logistics performance and the IoT market scale. We further find a significant and increasing correlation trend for an expansion of the IoT market and the reduction of carbon and PM 2.5 intensity. The environmental regulation though positively correlated with logistics sustainability, shows less potential to directly improve economic and social performance. It also indirectly promotes sustainability performance of the logistics industry through support for technological innovation. High investment in IoT is estimated to limit the potential of small and medium-sized enterprises to increase their labor compensation and expand the scale of employment. Finally, we project China’s IoT market developments for 2021–2025 using a grey forecasting model considering the influence of investment confidence and COVID-19. The results indicate that China’s share of the global IoT market will likely rise from 18% to 30% by 2025.

What drives horizontal logistics collaboration? A grounded theory analysis of Chinese logistics service providers.

Horizontal logistics collaboration is characterized by the highly professional cooperation of logistics service providers at the same level of the supply chain, which is an effective way to optimize the development and sustainability of modern logistics. Conducting a coding analysis of data from 41 in-depth interviews, this study constructs a theoretical framework of the driving force of horizontal logistics collaboration among Chinese logistics service providers to synchronously improve service, market, efficiency, and emergency competitiveness through cooperation with peer competitors to enhance sustainable comprehensive competitiveness. The four driving forces encourage logistics service providers to adjust their thoughts in the planning stage, change their behavior in the implementation stage, and transform their strategy in the evaluation stage. The results also indicate differences between China and other countries in the driving force, effective utilization of logistics workers, cross-institutional collaboration of state-owned enterprises, and integration of artificial intelligence technology. Finally, we propose relevant recommendations for managers.