Search results

The purpose of this research was to study the impacts of adoption of additive manufacturing (AM) for spare parts procurement, specifically in the context of supply chain resilience (SCR) especially regarding efficient spare parts inventory management. Furthermore, key narratives in the adoption of AM toward better SCR are explored.

In-depth interviews with semi-structured open-ended questionnaire were conducted to collect primary qualitative data from 24 supply chain management (SCM) experts. Respondents consisted of experts across various industries. The data were analyzed by thematic content analysis method.

The results indicated that AM could be a suitable tool to reduce dependence on original equipment manufacturers (OEMs) for spare parts procurement. Data analysis also revealed that AM adoption might lead to significant cost and lead time reduction. Designs protected as intellectual properties (IP), substantive post-processing requirements and material compatibility were revealed to be barriers in adoption.

The impacts of utilizing AM for procurement of spare parts on the overall resilience of the supply chain were highlighted. Theoretical analysis of the findings was based on theoretical aspects of SCR. This was especially regarding efficient spare parts inventory management. The study results revealed the factors responsible adoption of the AM technology. A novel approach was undertaken to study the effect of AM adoption on “time-to-market” of newly launched products.

The research provided insights regarding practical applications of AM adoption in spare parts procurement. The study could be beneficial to the early adopters of AM across industries for making managerial decisions. Unfamiliarity of supply chain managers with the AM technology was believed to be a major reason to adopt the technology. The study provided essential inputs regarding challenges and alternate adoption strategies of AM. Thus, the research was believed to be of potential value for creating awareness among supply chain managers regarding AM technology.

The research provided new insights on the impact of AM adoption in the context of SCR toward efficient spare parts inventory management. Various limiting and facilitating factors specific to Indian context were also explored.

This paper aims to assess the readiness of retail workers to use blockchain technology (BCT) to improve supply chain performance. The assessment was made via a quantitative approach taken using a theoretical framework based on Keller’s motivation model and self-determination theory in the BCT context.

The authors collected data from 567 retail workers from an emerging country through a structured survey questionnaire. The authors tested the hypotheses of the proposed model using Warp PLS 7.0 and controlled firm age, industry type and technological intensity.

Our findings may help firms in making the process of digital transformation inclusive. The authors found that supplier-based attention and motivation through BCT lead to supply chain performance, and that supplier-based satisfaction and trust achieved through BCT positively impact supply chain performance. Further, supplier-based relevance on raw material selection with the higher trust and motivation levels achieved through BCT was found to have a positive impact on supply chain performance.

IT supply chain applications are referred to as “lean” rather than “rich” because they still rely mainly on written and numerical means to present data. When the environment is less ambiguous, then less rich media can be used to facilitate communication. IT supply chain applications allow suppliers to spend time building relationships with other suppliers instead of focusing on administrative tasks, thus enhancing such relationships.

This study can be considered the first to assess retailer readiness to use BCT to improve supply chain performance through the theoretical lens of Keller’s motivation model and self-determination theory.