Wantao Yu, Ramakrishnan Ramanathan, Xingyu Wang and Jiehui Yang
The purpose of this paper is to investigate the relationships between operations capability, productivity, and business performance in the context of environmental dynamism.
Abstract
Purpose
The purpose of this paper is to investigate the relationships between operations capability, productivity, and business performance in the context of environmental dynamism.
Design/methodology/approach
A proposed conceptual framework grounded in the resource-based view (RBV) and dynamic capability view (DCV) is analyzed using archival data from 193 automakers in the UK.
Findings
The results show that operations capability, as an important dynamic capability, has a significant positive effect on productivity, which in turn leads to improved business performance. The results also suggest that productivity fully mediates the relationship between operations capability and business performance, and that environmental dynamism significantly moderates the relationship between operations capability and productivity.
Practical implications
The research findings provide practical insights that will help managers develop operations capability to gain greater productivity and business performance in a dynamic environment.
Originality/value
Addressing the two important issues of moderation (i.e. environmental dynamism) and mediation (i.e. productivity), this study makes important contributions to the field of operations management by applying the RBV and DCV.
Details
Keywords
Xu Dongyang, Li Kunpeng, Yang Jiehui and Cui Ligang
This paper aims to explore the commodity transshipment planning among customers, which is commonly observed in production/sales enterprises to save the operational costs.
Abstract
Purpose
This paper aims to explore the commodity transshipment planning among customers, which is commonly observed in production/sales enterprises to save the operational costs.
Design/methodology/approach
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.
Findings
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.
ractical implications
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.
Originality/value
This paper develops a more compact model and some stronger valid inequalities. Moreover, the proposed algorithm is easy to implement and performs well.
Details
Keywords
Juying Zeng, Carlos Lassala, Maria Del Mar Benavides and Jiehui Li
This study aims to assess the mediating and driving roles of knowledge cooperation in the effectiveness of G60 Sci-tech Innovation Corridor (G60 STIC) for regional collaborative…
Abstract
Purpose
This study aims to assess the mediating and driving roles of knowledge cooperation in the effectiveness of G60 Sci-tech Innovation Corridor (G60 STIC) for regional collaborative innovation within the knowledge economy context. Furthermore, it focuses on whether knowledge cooperation is more effective than resource cooperation in terms of spatial spillover and its mediating effects on collaborative innovation.
Design/methodology/approach
This study employs multiple statistical and econometric approaches, including social cooperation network, Super-DEA, spatial difference-in-difference model (SDID) and mediating effect model, to measure the effectiveness of knowledge cooperation and resource cooperation paths within the framework of the G60 STIC on regional collaborative innovation in the Yangtze River Delta region (YRD) from 2002 to 2022.
Findings
First, the knowledge cooperation networks validate the strengthening of collaborative innovation is primarily centred on provincial cities and leading manufacturing locales, with smaller cities radiating outwards from these centres. The knowledge cooperation network was generally stronger than the resource cooperation network. Second, the G60 STIC significantly enhances collaborative innovation efficiency by intensifying knowledge, resource and interactive cooperation networks. Third, within the context of the knowledge economy, knowledge cooperation presents a stronger spillover and mediating effect in stimulating collaborative innovation than resource cooperation.
Originality/value
This study clarifies the existence of a knowledge cooperation network and its mediating role in stimulating the effectiveness of strategic, innovative platforms on collaborative innovation. This further verifies the stronger role of the knowledge cooperation than the resource cooperation, which serves as a vital element in promoting strategic innovative platforms to optimise collaborative innovation.
Details
Keywords
Xiang Li, Ming Yang, Hongguang Ma and Kaitao (Stella) Yu
Travel time at inter-stops is a set of important parameters in bus timetabling, which is usually assumed to be normal (log-normal) random variable in literature. With the…
Abstract
Purpose
Travel time at inter-stops is a set of important parameters in bus timetabling, which is usually assumed to be normal (log-normal) random variable in literature. With the development of digital technology and big data analytics ability in the bus industry, practitioners prefer to generate deterministic travel time based on the on-board GPS data under maximum probability rule and mean value rule, which simplifies the optimization procedure, but performs poorly in the timetabling practice due to the loss of uncertain nature on travel time. The purpose of this study is to propose a GPS-data-driven bus timetabling approach with consideration of the spatial-temporal characteristic of travel time.
Design/methodology/approach
The authors illustrate that the real-life on-board GPS data does not support the hypothesis of normal (log-normal) distribution on travel time at inter-stops, thereby formulating the travel time as a scenario-based spatial-temporal matrix, where K-means clustering approach is utilized to identify the scenarios of spatial-temporal travel time from daily observation data. A scenario-based robust timetabling model is finally proposed to maximize the expected profit of the bus carrier. The authors introduce a set of binary variables to transform the robust model into an integer linear programming model, and speed up the solving process by solution space compression, such that the optimal timetable can be well solved by CPLEX.
Findings
Case studies based on the Beijing bus line 628 are given to demonstrate the efficiency of the proposed methodology. The results illustrate that: (1) the scenario-based robust model could increase the expected profits by 15.8% compared with the maximum probability model; (2) the scenario-based robust model could increase the expected profit by 30.74% compared with the mean value model; (3) the solution space compression approach could effectively shorten the computing time by 97%.
Originality/value
This study proposes a scenario-based robust bus timetabling approach driven by GPS data, which significantly improves the practicality and optimality of timetable, and proves the importance of big data analytics in improving public transport operations management.