Search results

E-retailing grows rapidly in recent years. The majority of previous research on e-retailing service recovery has been mainly focussed on the customers’ perspective. The purpose of this paper is to examine service recovery from the operations management perspective of the e-retailing industry in order to investigate the impact of an integrated service recovery system on e-retailers’ capability improvement and market performance.

Empirical data consists of a sample of 256 employees from a leading e-retailer in China. Structural Equation Model was used to verify the relationship between the integrated recovery system and employees’ job satisfaction and organizational citizenship behavior (OCB) as well as e-retailers’ capability improvement and market performance.

The empirical results reveal that e-retailers need to pay attention to establishing an integrated recovery system. The system can facilitate employee job satisfaction and OCB, ultimately the e-retailer’s market performance. However, the relationships between job satisfaction and OCB as well as market performance are found to be low in the context of e-retailing in China.

This research contributes to the effectiveness of an integrated service recovery system in the context of e-retailing and the important role played by employees during recovery process.

Casting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of process variables related to properties of the materials used in making a mold and the product itself; hence, variables related to product/process designs are taken into consideration. Understanding casting techniques considering significant process variables is critical to achieving better quality castings and helps to improve the productivity of the casting processes. This study aims to understand the computational models developed for achieving better quality castings using various casting techniques.

A systematic literature review is conducted in the field of casting considering the period 2000–2020. The keyword co-occurrence network and word cloud from the bibliometric analysis and text mining of the articles reveal that optimization and simulation models are extensively developed for various casting techniques, including sand casting, investment casting, die casting and squeeze casting, to improve quality aspects of the casting's product. This study further investigates the optimization and simulation models and has identified various process variables involved in each casting technique that are significantly affecting the outcomes of the processes in terms of defects, mechanical properties, yield, dimensional accuracy and emissions.

This study has drawn out the need for developing smart casting environments with data-driven modeling that will enable dynamic fine-tuning of the casting processes and help in achieving desired outcomes in today's competitive markets. This study highlights the possible technology interventions across the metal casting processes, which can further enhance the quality of the metal casting products and productivity of the casting processes, which show the future scope of this field.

This paper investigates the body of literature on the contributions of various researchers in producing high-quality casting parts and performs bibliometric analysis on the articles. However, research articles from high-quality journals are considered for the literature analysis in identifying the critical parameters influencing quality of metal castings.

The systematic literature review reveals the analytical models developed using simulation and optimization techniques and the important quality characteristics of the casting products. Further, the study also explores critical influencing parameters involved in every casting process that significantly affects the quality characteristics of the metal castings.