Boosting Up Operational Performance of Manufacturing Organizations through Interpretive Structural Modelling of Enabling Practices

Abstract

For achieving world-class performance and competitiveness in today’s global highly complex environment and competition, there is an immense pressure on manufacturing organizations having limited resources to pursue operational excellence in terms of productivity and quality, reduce cost, and provide high-quality products in shorter lead times. Identification of representative practices affecting operational performance (OP) and understanding of mutual dependence among those practices will improve the performance of manufacturing organizations with available resources. A sample of 10 experts of academicians and senior company managers from different functional areas of large-scale textile, sugar, and cement industries were surveyed to identify critical practices influencing OP and then to develop the relationships among them. It also identifies those practices that support other practices (driving practices) and also those that are most influenced by other practices (dependent practices). Firstly, through in-depth review of relevant literature, 10 most influencing practices were identified. Then expert elicitation was employed, and a hierarchical structure was established by using interpretive structural modelling (ISM) technique. After determining driving and dependence power of practices, classification or clusters of these practices were made through an additionally carried out MICMAC (cross-impact matrix multiplication applied to classification) analysis. The results contribute that lean management, organizational culture, ISO 9001 (quality management system), and human resource management practices indicate strong driving power and are at the bottom of ISM model. This is a novel and useful application of ISM to identify inherent interactions among these practices and construct a structural graph. With the help of this strategic understanding, researchers and practitioners will be able to identify the focal areas and to pay more attention to driver practices to effectively incorporate them at their strategic and operational levels and the effectiveness in addressing these driver practices will influence the OP to a large extent.

Configuring the Drivers and Carriers of Process Innovation in Manufacturing Organizations

“…The significant effects imply that by placing focus on HRM, LM and OC, manufacturing organizations can boost the successful implementation of TQM and SCM practices. The results established are consistent with previous studies [85]. For example, Dubey and Singh [29] concluded that the relationship between LM and TQM is significant which endorses H 1 .…”

“…Furthermore, LM, HRM and OC can significantly enhance PI as shown in Table 6. These analytical results of direct effects are consistent with those obtained by [5,20,25,85]. Furthermore, it was found from the bootstrapping technique that 21% to 37% effects of LM, HRM and OC on PI were explained through TQM and SCM.…”

Developing an interplay among the psychological barriers for the adoption of industry 4.0 phenomenon

“…Warfield (1974) proposed the ISM technique to capture the complex interrelationships of emerging socio-economic factors. ISM is an interactive technique used by research groups in complex environments as a communication mode to transfigure ambiguous and equivocal mental models of systems into a well-defined and explicit hierarchical model (Alawamleh & Popplewell, 2011 [ 80 ]. ISM has been broadly utilized in the early literature on policymaking to its wide use in recent research [ 81 ].…”

“…Moreover, this clubbed analysis is helpful to differentiate the input, output and intermediate parameters [ 85 ]. The elements are categorized into four clusters depending upon their driving power and dependence: Autonomous, Dependent, Linkage and Independent [ 80 ].…”

Significance of digital technology in manufacturing sectors: Examination of key factors during Covid-19

“…Manufacturing companies are struggling to achieve excellence in their operations in terms of improved quality, productivity, and reduced cost. The Covid-19 pandemic has further aggravated the lacklustre operational performance due to unavailability of personnel, the crisis in the workforces' mental, physical and social dimensions along with lack of resources ( Arshad Ali et al, 2020 ). Lack of operational performance is one of the major concerns that need to be alleviated in manufacturing industries in this covid era.…”