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EN
Sustainability-related risk and vulnerability management have attained significant attention from academia and industry. Manufacturing industries in developing countries such as Pakistan are under severe economic pressure and striving to boost sustainable supply chain practices for achieving business excellence. In this context, the objectives of the present research are to examine the critical supply chain risks associated with sustainable development goals, namely social, economic, and environmental factors. The failure mode and effect analysis (FMEA) technique is employed for categorizing the risk factors and Pareto analysis for highlighting the more crucial and risky factors. For this purpose, a large-scale survey was carried out in the textile industries of Pakistan to develop a risk mitigation model for sustainability-related risks and vulnerability in a textile supply chain (TSC). It captures the input expressions of experts for risk factors, namely severity (s), occurrence (o), and detection (d) for calculating the risk priority numbers (RPNs) of identified alternatives. The results depict that endogenous environmental risks categorize as the most significant for the textile manufacturing industries, and the interfaces between the various risks associated with sustainability-related are also found very high. This study would be a toolkit for the industrial managers and policy-makers for creating sustainable manufacturing culture on organizational premises.
EN
Background: Continuous change is a vital factor for organization’s sustainable growth and success. The implementation of modern information technology in business has become a core need of the hour. This study endeavours to answer how to cope with resistance to change when implementing new technology in the banking sector. A theoretical model has been developed with the blend of ADKAR change model, Technology Acceptance Model (TAM), and Hofstede dimensions of national culture to investigate the impact of the ADKAR change model on Technology Acceptance under the moderation of two national culture’s dimensions. Materials and Methods: In order to collect data, 500 self-administered questionnaires were dropped personally in five major banks of five cities of Pakistan using the convenience-based employee intercept sampling technique. The validated response rate was 68% by having 340 fit questionnaires for analysis using covariance-based structure equation modelling with the help of SmartPLS. Results: The results uncover the significant existence of covariance between dimensions of the ADKAR change model and technology acceptance model. The findings are statistically significant, inferring the influential role of change management on technology adoption. Conclusion: The study results provide promising implications based on these conclusions and findings for both theoretical aspects of these different models and practitioners.
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