Suchergebnisse

Purpose
With the increasing awareness of global warming and the important role of last mile distribution in logistics activities, the purpose of this paper is to build an environmental and effective last mile distribution model considering fuel consumption and greenhouse gas emission, vehicle capacity and two practical delivery service options: home delivery (HD) and pickup site service (PS). This paper calls the problem as the capacitated pollution-routing problem with pickup and delivery (CPRPPD). The goal is to find an optimal route to minimize operational and environmental costs, as well as a set of optimal speeds over each arc, while respecting capacity constraints of vehicles and pickup sites.


Design/methodology/approach
To solve this problem, this research proposes a two-phase heuristic algorithm by combining a hybrid ant colony optimization (HACO) in the first stage and a multiple population genetic algorithm in the second stage. First, the HACO is presented to find the minimal route solution and reduce distribution cost based on optimizing the speed over each arc.


Findings
To verify the proposed CPRPPD model and algorithm, a real-world instance is conducted. Comparing with the scenario including HD service only, the scenario including both HD and PS option is more economical, which indicates that the CPRPPD model is more efficient. Besides, the results of speed optimization are significantly better than before.


Practical implications
The developed CPRPPD model not only minimizes delivery time and reduces the total emission cost, but also helps logistics enterprises to establish a more complete distribution system and increases customer satisfaction. The model and algorithm of this paper provide optimal support for the actual distribution activities of logistics enterprises in low-carbon environment, and also provide reference for the government to formulate energy-saving and emission reduction policies.


Originality/value
This paper provides a great space for the improvement of carbon emissions in the last mile distribution. The results show that the distribution arrangement including HD and PS services in the last mile adopting speed optimization can significantly reduce the carbon emission. Additionally, an integrated real-world instance is applied in this paper to illustrate the validity of the model and the effectiveness of this method.

Purpose
The purpose of this paper is to monitor the environmental efficiency of suppliers in the presence of undesirable output and dual-role factors with static and dynamic aspects. Meanwhile, it also aims to explain the main reason for the low efficiency of suppliers.


Design/methodology/approach
The authors propose a modified data model considering undesirable output and dual-role factors. The study integrates the modified data envelopment analysis model into the distance function of the Malmquist–Luenberger index. Moreover, this study uses the global benchmark technology to formulate a two-stage model. To verify the validity of this model, a model application is conducted on an automotive spare components company in China.


Findings
The results identify the unique status of dual-role factors based on the global optimality of the model and then categorize inefficient suppliers in an individual evaluation cycle. In addition, each supplier is projected on a frontier curve after obtaining the improved data. Furthermore, through the status plot of M-L and its components, this paper concludes that efficiency scale change is the main reason for the gap in ecological performance between different suppliers.


Research limitations/implications
The proposed model considers both undesirable output and dual-role factors; however, variables with different features, such as imprecise, fuzzy and qualitative characteristics, can be embedded into the presented two-stage model.


Originality/value
Evaluating green suppliers through multiple consecutive evaluation cycles will aid a company in effectively managing its key suppliers. Furthermore, the evaluation provides policy guidance for further improvement of suppliers.

PurposeIn the context of sharing economy and online shopping, establishing a stable urban joint distribution alliance (JDA) is extremely necessary for the entire logistics service market. The purpose of this paper is to rationally allocate the profits and determine the most stable allocation scheme for the urban JDA as well as provide a direction for cooperation between express enterprises and lead managers to pay more attention to the comprehensive performance.Design/methodology/approachCooperative game-based methodologies including the proportion method, the core theory, nucleolus and Shapley value have been employed. Four criteria consisting of enterprise operation, customer satisfaction, environmental sustainability and information technology have been incorporated into Shapley value for improvement.FindingsThis paper reveals that express enterprises in logistics service market can achieve more benefit from JDA than those who operate separately. Among proposed profit allocation schemes, improved Shapley value scheme shows more rationality by considering partners' asymmetric contribution. Besides, a stable alliance can be always ensured with partners' lower propensity to disrupt and relatively balanced negotiation power under improved Shapley value scheme.Originality/valueThis paper makes a few attempts to contribute to the literature on the improvement of Shapley value and applies the concept of "propensity to disrupt" into the field of logistics. Besides, this paper provides various profit allocation schemes and incorporates influencing factors into Shapley value for an improvement thus helping policy-makers make better-informed decisions on urban distribution. Additionally, a case study based on urban express enterprises in Southwest China has been conducted to verify the proposed profit allocation schemes.

PurposeThe paper investigates firms' optimal pricing policies and green strategies in a dynamic green supply chain with consideration of different retail service strategies. The purpose of the paper is to address the following research questions: (1) What are the optimal pricing policies and green strategies of the dynamic decentralized supply chain with the competitive or supportive retail service? (2) How does the dynamic consumer's perception of green product affect these equilibrium solutions?Design/methodology/approachThe paper establishes the dynamic game models and then derives a firm's instantaneous and steady-state feedback equilibrium solutions in three scenarios as follows: (1) the integrated supply chain; (2) the decentralized supply chain with competitive retail service and (3) the decentralized supply chain with supportive retail service. Finally, we conduct numerical analyses to compare the firm's instantaneous and steady-state equilibrium solutions and profit in the three scenarios.FindingsThe theoretical and numerical analysis results suggest that the supportive retail service is less inefficient than the competitive retail service in the decentralized supply chain and that the types of retail service have no influence on the green strategy. Moreover, a firm's myopia leads to lowering the greenness degree, retail service level and severe price competition, resulting in economic losses. Consumers' initial perception of greenness degree determines whether the retailer should adopt the skimming pricing strategy or penetration pricing strategy. Furthermore, only when consumers' perception of greenness degree is higher than a threshold, will the manufacturer produce green product with positive greenness degree.Originality/valueThis is one of few studies on the effect of different types of retail service on horizontal competition in green supply chain. The extension of the static study by adopting differential game approaches provides researchers with a deeper understanding of the application of retail service in green supply chain.