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The purpose of this study is to propose a new coordinated dynamic demand lot-size and delivery planning problem (CDLSDP), in which the delivery policy is integrated into the coordinated dynamic demand lot-size problem (CDLSP).

As a non-deterministic polynomial complete (NP-complete) problem, this CDLSDP seems difficult to be solved by a polynomial-time method. To handle this problem effectively and efficiently, a four-phase heuristic that balances the setup and inventory costs in the coordinating and delivery stages is designed to find near-optimal solutions.

Numerous computational experiments show that the proposed four-phase heuristic is effective and efficient. For 1,800 experiments with different scales, and different joint setup costs, solutions by the proposed heuristic have an average gap no more than 1.34% from the optimal solution.

To decrease total system cost, the CDLSDP optimizes the time-phased replenishment and delivery schedule, which includes joint setup cost, item setup, delivery and inventory cost, for each period. An effective and efficient four-phase heuristic is designed to solve the CDLSDP.

Compared with the traditional CDLSP, the delivery policy is considered by the new CDLSDP. Moreover, the proposed four-phase heuristic is a good candidate for solving the CDLSDP.

It becomes a strategic option for enterprises to upgrade and improve supply chain efficiency (SCE) by promoting the digital transformation (DT). This study formulated a parallel mediation model to analyze the relationships among DT, supply chain transparency (SCT), supply chain agility (SCA) and SCE to reveal how DT affects SCE through the mediation of SCT and SCA.

Three paradigms, i.e. resource-based view (RBV), dynamic capability view (DCV) and structure-conduct-performance (SCP) were employed to address the parallel mediation effects. A total of 392 questionnaires (samples) from the port-hinterland supply chain in the DT pilot project of New Land-Sea Corridor in western China were collected, which was then applied to formulate a structural equation model (SEM) to verify the proposed hypotheses.

The results confirmed the existences of parallel mediating effects of SCT and SCA between DT and SCE. On one hand, the direct effect of DT on SCE is not significant when SCT and SCE plays jointly impacts on DT and SCE. On the other hand, SCT and SCA play a positive parallel full mediating effect of DT on SCE.

This study contributed to the literature on changing activities of SCE in DT processes. Specifically, it highlighted how DT leads to SCE via SCT and SCA activities. In addition, this study specified the conditions that the insignificant direct effect of DT has reflects on SCE, it is the time when SCT and SCE are jointly acting on DT and SCE.

By integrating insights from the RBV, DCV and SCP paradigms, this study clarified the mechanisms of DT on SCE, and provided insight on the role of SCT and SCA in the relationship between DT and SCE. The novelty of this study and the results extend the existing literature and provide implications for future research.

This study aims to find the impact of supply chain certification (SCCert) on supply chain efficiency (SCEffi) with the inverted U-shaped moderator role of supply chain complexity (SCComp).

In order to test the conceptual model and the hypothesized relationships between all the constructs, the 307 useable survey responses were collected using the purposive sampling technique on a seven-point Likert scale. The SPSS26.0 and AMOS24.0 were used to analyze data, and the hierarchical regression analysis was used to test the model.

This study reached a set of interesting results where it was confirmed that there is a significant relationship between SCCert and SCEffi. It further confirmed the inverted U-shaped moderating effect of SCComp between SCCert and SCEffi: on the left side of the threshold, the increase of SCComp will enhance the promotion effect of SCCert on SCEffi, while on the right side of the threshold, excessive SCComp will rather weaken the promotion effect of SCCert on SCEffi.

The findings provide implications for supply chain efficiency enablers to introduce/promote certification upgrading actions. The study provides a framework for solving the power and constraint problem of supply chain efficiency change.

Findings provide deeper and new insights into threshold feature of supply chain complexity, analyzing how supply chain certification activity realize supply chain efficiency reform through the moderating role of supply chain complexity.

This paper aims to explore the commodity transshipment planning among customers, which is commonly observed in production/sales enterprises to save the operational costs.

A mixed integer programming (MIP) model is built and five types of valid inequalities for tightening the solution space are derived. An improved variable neighborhood search (IVNS) algorithm is presented combining the developed multistart initial solution strategy and modified neighborhood local search procedure.

Experimental results demonstrate that: with less decision variables considered, the proposed model can solve more instances compared to the existing model in previous literature. The valid inequalities utilized to tighten the searching space can efficiently help the model to obtain optimal solutions or high-quality lower bounds. The improved algorithm is efficient to obtain optimal or near-optimal solutions and superior to the compared algorithm in terms of solution quality, computational time and robustness.

This research not only can help reduce operational costs and improve logistics efficiency for relevant enterprises, but also can provide guidance for constructing the decision support system of logistics intelligent scheduling platform to cater for centralized management and control.

This paper develops a more compact model and some stronger valid inequalities. Moreover, the proposed algorithm is easy to implement and performs well.

The purpose of the study is to evaluate the severity of public events in real time from the perspective of social media and to construct the early warning mechanism of public events.

This study constructed the severity assessment system of public events from the dimensions of the netizens' role, the Internet media's role, the spread of public events and the attitudes and feelings of netizens. The method of analyzing the influence tendency of the public event severity indicators was proposed. A total of 1,107,308 microblogging entries regarding four public events were investigated. The severity of public events was divided into four levels.

It is found that serious public events have higher indicator values than medium level events on the microblogging platform. A quantitative severity classification standard for public events was established and the early warning mechanism of public events was built.

Microblogging and other social media platforms provide rich clues for the real-time study and judgment of public events. This study only investigated the Weibo platform as the data source. Other social media platforms can also be considered in future.

Different from the ex-post evaluation method of judging the severity of public events based on their physical loss, this study constructed a quantitative method to dynamically determine the severity of public events according to the clues reflected by social media. The results can help the emergency management departments judge the severity of public events objectively and reduce the subjective negligence and misjudgment.

The purpose of this paper is to study the influence of the processing parameters of diamond wire sawing on surface morphology and roughness.

First, a wire saw cutting model is established to determine the positional relationship between a wire saw and the machined surface of the workpiece, and the abrasive grain cutting trajectory is generated. Through the data processing of the cutting trajectory, the simulation of the three-dimensional surface topography of the slice and the calculation of the surface roughness are realized by using the GUI programming of MATLAB. Finally, different surface roughness values are obtained by changing the machining parameters (saw wire speed and workpiece feed speed).

The conclusion is that the surface roughness of the slice is larger when the feed speed is higher and smaller when the linear speed is higher.

Diamond wire saw cutting is the first process of chip processing, and its efficiency and quality have an important impact on subsequent processing. This paper will focus on the influence of the sawing wire cutting processing parameters (sawing wire speed and workpiece feed speed) on the surface roughness to optimize the processing parameters and obtain smaller surface roughness values. Through MATLAB three-dimensional simulation, the surface morphology can be observed more intuitively, which provides a theoretical basis for improving the processing quality.

The purpose of this paper is to clarify how Chinese multinationals perceive factors affecting the integration-responsiveness (I-R) framework.

This study extends quantitative and conceptual studies that have clarified and assessed the underlying factors that influence multinational enterprises’ (MNEs) international business strategy choices relating to global integration and local responsiveness with the use of cross-level and in-depth interviews. Top management perceptions from nine Chinese MNEs with operations in Australia are detailed.

The study obtains empirical evidence on applying the I-R framework in the context of MNEs from emerging markets. Also the hybrid factors affecting both integration and responsiveness synchronously have been confirmed by Chinese multinationals.

As a cross-sectional study, the paper focuses on senior executives’ perceptions on factors affecting the I-R framework. This analysis would be enriched by melding these perspectives with extensive secondary data on the companies concerned to assess the ratings assigned.

When studying factors affecting global integration and local responsiveness prior studies have centred on multinationals from advanced economies and/or their subsidiaries in emerging markets. This concentration leaves unclear the relevance of developed country centred findings to MNEs from emerging markets and their subsidiaries in advanced economies, and the demonstration of how emerging markets MNEs perceive factors affecting the I-R framework.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.