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This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

This paper aims to clarify the spatial connection characteristics and organization mode of logistics economy of 21 cities in Guangdong Province under the background of the integrated development of Guangdong, Hong Kong and Macao Bay area, and explore the spatial development characteristics and influencing factors of logistics economy in Guangdong Province.

This paper constructs the development level model of urban logistics economy in Guangdong Province from three aspects: demand level, supply level and support level, and uses the entropy weight method to measure the development level index of urban logistics economy in Guangdong Province. Then, the traffic accessibility index model is used to measure the traffic accessibility index between cities in Guangdong Province. Finally, using the social network analysis method, combined with the development level index of urban logistics economy in Guangdong Province and the urban traffic access index in Guangdong Province, this paper analyzes the spatial connection characteristics and influencing factors of logistics economy network in Guangdong Province.

There are regional differences in the development level of logistics economy in Guangdong Province; The overall network density of its logistics economic connection is large, but there is an imbalance in the network structure, and the core edge phenomenon is obvious; Logistics economic space presents the characteristics of double core development.

Because the research object is the spatial connection characteristics of logistics economy in Guangdong Province, the research results may lack universality. Therefore, researchers are encouraged to put forward further tests.

By studying the spatial connection mode of logistics economy in 21 cities in Guangdong Province, China, this paper promotes the original methods and empirical contributions, and constructs the research framework of spatial relationship of logistics economy. This research framework is universal to a certain extent.

This paper is conducive to promoting the integrated development of logistics economy in Guangdong Province and improving the balance of regional development of logistics economy.

Firstly, this study provides a new perspective to understand the spatial relationship and spatial spillover of logistics economy from relational data rather than attribute data. Secondly, This study enriched and broadened the research topic of spatial correlation of logistics economy. Thirdly, this research aims to promote the original methods and empirical contributions. Specifically, this study establishes a comprehensive research framework on the spatial network structure of logistics economy.

This study aimed to develop the integration of the multiperiod production-distribution model in a closed-loop supply chain involving carbon emission and traceability. The developed model was for agricultural food (agri-food) products, considering the reverse flow of food waste from the disposal center (composting center) to producers.

The results indicate that integrating the production and distribution model considering food waste recycling provides low carbon emissions in lower total costs. The sensitivity analysis also found that there are trade-offs between production and distribution rate and food waste levels on carbon emission and traceability.

This study focuses on the mathematical modeling of a multiperiod production-distribution formulation for a closed-loop supply chain.

The model of the agri-food closed-loop supply chain in this study that considers food recycling and carbon emissions would help stakeholders involved in the agri-food supply chain to reduce food waste and carbon emissions.

The present study is aimed at developing a multi-level framework for assessing circularity in agri-food industries by providing the user with a step-by-step approach and selecting a customized set of indicators capable of accurately assessing the circular economy (CE) level.

The framework is composed of four stages. In the first stage, a CE theoretical model based on operations, product and services, culture, organization and ecosystem criteria has been implemented and adapted to the agri-food sector. In the second stage, users are required to collect a set of indicators capable of measuring each criterion. In the third stage, a weight is assigned to each indicator using analytical hierarchy process (AHP). Lastly, a geometric multi-criteria decision-making (MCDM) model, called axial distance-based aggregated measurement (ADAM) model, is used to normalize, assess and aggregate the results and produce final scores for the different alternatives to be ranked based on their final circularity scores.

The model can be a useful tool to support corporate decisions in the CE, making entrepreneurs aware of their starting level. It indicates the extent to which companies are implementing circular business models across different dimensions and, thus, where they are still lacking.

Beyond the attempts to measure the circularity of corporate performance from a purely environmental perspective, the study adopts a holistic view, considering the complexity and disruption of all the principles of the CE.

Non-profit organizations (NPOs) are exposed to a highly competitive environment in which they are forced to grow their commercial activity to acquire additional financial resources. This study aims to create an understanding of how NPOs involved in textile reuse as a revenue-generating programme manage their reverse supply chains (RSC).

The research involves an embedded single-case study of NPOs in Finland involved in post-use textile collection. The main data sources are semi-structured interviews and participant observations.

This study is inspired by the microfoundations movement and identifies the underlying microfoundations of the NPOs’ capabilities for managing RSC for textile reuse. The study contributes to the literature by demonstrating NPOs’ lower-level, granular practices and their adaptations for achieving quality outcomes in textile reuse.

The findings have context sensitivity and apply to the NPOs which operate in a context similar to Finland, such as in other Nordic countries.

This study continues the discussion on the adoption of “business-like” practices in the NPOs’ pursuit of additional revenue streams to finance humanitarian work. The findings of this study can also be transferred to the growing area of domestic textile circularity.

Using the case of NPOs in textile reuse, the study illustrates how RSC management can serve a social, non-profit cause and transform unwanted textile products into a source of fundraising for humanitarian work.

This enriches the understanding of NPOs’ practices within the scope of revenue-generating programmes by examining one of them – textile reuse through charity shops from an RSC perspective.

Study on the internal legalization process of strategic change for a large number of ultra-large enterprises in China.

This paper takes formulation process of Suning Appliance Group’s 10-year strategy (2010–2020) as the research case, designs the research issues, propositions and analysis unit of the case study, and uses the data collection and analysis methods in the grounded theory to realize the theoretical development from data to viewpoint conceptualizing and to proposition categorizing.

There are four key concepts that affect the judgment of overall strategic legitimacy of super-large enterprises: Emerging-market opportunities and strategic operational positioning, legitimacy perspective mainly manifests as legitimacy judgment of strategic direction within organization. Positioning of core resources (including intangible resources) and their value identification methods or value evaluation criteria, the legitimacy perspective is mainly reflected in the organization's internal legitimacy judgment of functional planning, especially implementation path. The impact factors of the key performance of each SBU are positioned, and the legitimacy perspective is mainly reflected in the organization’s internal judgment on the legitimacy of strategic supporting measures, especially the resources needed for the implementation of the strategy and capacity development. The periodical strategic objectives and performance measurement indicators of each SBU are mainly reflected in the organization’s internal legitimacy judgment on strategic alignment and specific action plans for strategic operational units. The legitimacy of these four key concepts is strongly influenced by the rationality of these strategic concepts, which are closely related to their shaping patterns driven by right-brain and left-brain thinking modes.

This case is a longitudinal study of the strategic decision-making process, not a longitudinal follow-up of the actual implementation of the strategy. In addition, given that the case enterprise was facing the emerging market at that time and focused on pushing firms to seize opportunities, not much research has been done on the impact of external legitimacy on the strategic formulation process, a variable that is increasingly being focused on today.

This model has guidance significance and practical demonstration role for a large number of enterprises that are implementing the “+Internet” strategic change under traditional offline operation.

According to the summary of the connection between data and propositions in several rounds, this paper constructs a theoretical model of left and right brain thinking mode driving key concepts to achieve the internal legalization process of strategic changes.

In the analysis process, the legalization theory and the sense-making method are introduced into enterprises’ strategy making process. Based on this analysis framework, this paper analyzes in detail that the top decision-making level and the middle and high executive level form key strategic concepts to promote the internal legalization process of strategic decision-making driven by the right-brain intuitive thinking mode and the left-brain rational thinking mode, which greatly improves the quality of strategy formulation and the operability of strategy implementation.

This study examines the impact of customer involvement (CI), technology strategy, firm internationalization and servitization on product and service innovation performance (SIP) in hybrid offerings. In addition, it investigates the moderating role of digitization and co-creation in the relationship mentioned above.

A research framework was developed through the lens of service-dominant (S-D) logic theory, and the proposed research hypotheses were empirically tested. Primary data were collected via the survey method, and structural equation modeling was used to analyze the data.

Findings of this study suggest that the S-D logic theory effectively explains CI and servitization in hybrid offerings. Furthermore, digitization is a crucial driver of SIP. Additionally, this paper finds that co-creation moderates between servitization and innovation performance of hybrid offerings.

Besides theoretical contributions, this study presents valuable insights to manage service networks during servitization.

First, this work proposes a comprehensive framework of hybrid offerings' driving factors (i.e. CI, firm internationalization, technology strategy and servitization) and their impact on product and SIP. Second, it tests the moderating effects of digitalization and co-creation in the context of hybrid offerings.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.