No abstract

PurposeThis study explores the interplay between lean management and circular production systems and their implications on zero-waste performance, green value competitiveness and social reputation.Design/methodology/approachQuestionnaire-based survey methodology is used to obtain empirical data from Ghanaian manufacturing SMEs. A multivariate statistical technique, specifically partial least square structural equation modelling is chosen to test the hypothesized relationships.FindingsThe empirical results confirm that lean management is a vital element in moving SMEs towards the implementation of circular production systems. The results also confirm that lean management and circular production systems combine effectively to bring about significant improvement in zero-waste performance, reinforce green value competitiveness and boost social reputation. The results further confirm the mediation role of circular production system between lean management, zero-waste performance, green value competitiveness and social reputation.Originality/valueAnchored on the tenets of the natural resource-based view theory, resource orchestration theory and stakeholder theory, this study proposes an integrated research model that builds new insights into the relationship between lean management, circular production system, zero-waste performance, green value competitiveness and social reputation. The proposed model directs the actions of SME managers in emerging countries to comprehensively evaluate their production processes to equalize the possible compatibility of lean management and circular production systems to meet their zero-waste performance targets, gain green value competitiveness and stimulate social reputation.

No abstract

No abstract

The increasing demand for electric power is an established trend in China, of which coal power accounts for a large proportion. This paper proposes an inventory hub location model considering multi‐type coal to minimize the total transportation and inventory cost in a multi‐coal‐power supply chain. A second‐order cone programming method is adopted to convert the original model. The exact solutions of the small‐scale real case show that the model can greatly reduce the total costs by CPLEX. For real‐world large‐scale cases, a customized greedy randomized adaptive search simulated annealing algorithm is devised and tested to obtain near‐optimal solutions within a reasonable time. The research has strong practical guiding significance for the management of the thermal coal supply chain.