production and operations management
Morteza Saeidi; Mostafa Ebrahimpour Azbari; MohammadRahim Ramazanian
Abstract
The purpose of this Article is to Designing a model for improving the Sustainable Performance of Small and Medium Food Companies in Guilan Province so that in the current environment, managers and decision makers by recognizing the factors, challenges and consequences to improve the sustainable performance ...
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The purpose of this Article is to Designing a model for improving the Sustainable Performance of Small and Medium Food Companies in Guilan Province so that in the current environment, managers and decision makers by recognizing the factors, challenges and consequences to improve the sustainable performance of Small and Medium Food Companies. The present Article is in the category of applied research from the perspective of purpose, in the category of exploratory-descriptive research in terms of nature and in the field of field studies based on data collection.This Article is in the category of qualitative research. A paradigm model was created by the Grounded theory method through three stages of open, axial and selective coding. The Results of data Analysis using Grounded Theory led to the formation of 13 main floors, 29 main categories and 248 concepts. The six main classes of paradigm model of the Grounded theory using theoretical coding in the form of: pivotal phenomenon (sustainable performance improvement), causal conditions (organizational survival, social and environmental obligation, gaining competitive advantage), contextual conditions (environmental factors, organizational factors), Interfering Conditions (environmental factors, organizational factors), strategies (macro level, organizational level). Finally the Economic, Social and Environmental consequences of achieving Sustainable Performance Improvement were achieved by implementing the strategies.
supply chain management
mona mousavie; Mahmoud Moradi; Mostafa Ebrahimpour Azbari
Abstract
In light of the continuous and rapid changes in global competition, companies face the imperative of consistently introducing new products or expanding their existing product lines to maintain their competitive edge. Recognizing that numerous factors within the supply chain influence the production, ...
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In light of the continuous and rapid changes in global competition, companies face the imperative of consistently introducing new products or expanding their existing product lines to maintain their competitive edge. Recognizing that numerous factors within the supply chain influence the production, design, distribution, and introduction of new products, understanding supply chain risks is crucial, spanning from the procurement of raw materials to the delivery of products to the market. Consequently, risk management stands as one of the most critical challenges within the supply chain, significantly impacting New Product Development (NPD) performance. This research seeks to answer the primary question: "How and to what extent do various supply chain risks affect newly developed products?" While prior research has employed various methods to evaluate and manage supply chain risks, few models have explored the interplay of these risks on each other and their influence on performance dimensions. In this study, based on a review of theoretical foundations and prior research within the clothing manufacturing sector, we identified dimensions of newly developed products and supply chain risks. We employed the Delphi technique through interviews to identify the most significant risks. Subsequently, we employed the Cross-Impact Analysis method to elucidate relationships between these factors. Finally, we utilized Bayesian networks to analyze the impact of identified risks on the performance of the selected new product, conducting sensitivity and scenario analyses. The findings indicate that environmental and supply risks are more likely to manifest than other risks, with three operational, distribution, and demand risks, influenced by environmental and supply risks, exerting the most direct impact on new product performance, particularly in the dimension of quality.IntroductionModern organizations recognize that traditional competitive strategies, such as improving quality and reducing costs, no longer suffice to remain competitive. Research has demonstrated that numerous new product development NPD projects face failure for various reasons. Effective risk identification and management, particularly concerning supply chain risks in NPD projects marked by a high degree of uncertainty, emerge as pivotal factors for NPD success. In this context, the clothing sector, characterized by a complex supply chain structure, has been extensively studied. However, prior research has predominantly examined existing risks individually, overlooking the interactions between risk components and their simultaneous effects on one or more project objectives. In this research, we not only assess the simultaneous impact of risks on product performance using the Bayesian network method, an effective approach in supply chain risk analysis, but also investigate the severity of risk impacts under different scenarios. This research addresses three primary objectives:Identification of supply chain risks in the clothing industry based on background research and case studies.Determination of interdependencies among variables using conditional modeling.Evaluation of the influence of supply chain risks on new product performance using the Bayesian network method under varying scenarios.Literature reviewNumerous researchers have investigated supply chain risks and their repercussions on product and organizational performance. Asgharenjad Nouri et al. (2021), in their article titled "The Effect of Risk Management on New Product Development in the Banking Industry," explored the impact of various risk indicators on new product development. Their results underscore the significant positive influence of managing all risk indicators, including technology, market, environment, finance, organizational resources, and commercialization, on new product development. Qazi et al. (2017), in their article titled “Supply Chain Risk Network Management,” prioritized risks and corresponding strategies through a case study involving semi-structured interviews. They initially identified organizational performance criteria and then linked them to relevant risks, using a matrix of expected profit to investigate the impact of risks on specified performance criteria. Subsequently, they employed the "weighted net evaluation" method to assess practical strategies.MethodologyIn conducting this research, we initially extracted supply chain risks and product performance dimensions from the existing literature. Subsequently, we employed the Delphi technique to select the most significant supply chain risks, providing indicators to participating experts through questionnaires with a 5-point Likert scale. We then used the Content Validity Ratio (CVR) index to confirm or reject the components derived from the questionnaires. In the next step, we used the Cross-Impact Analysis method, employing pairwise comparisons via questionnaires, to reveal relationships between the key risk criteria. Finally, we investigated the impact of identified risks on the performance of the selected new product within the supply chain of Happy Land factory using the Bayesian network method under various scenarios.Discussion and ResultsThe results from the Bayesian network analysis in this research demonstrate that environmental risk, as an external risk within Happy Land’s supply chain, exerts the most significant influence at the highest level of the Bayesian map. Subsequently, other risks, including economic risks, supplier risks, distribution risks, operational risks, and demand risks, are categorized in subsequent levels. Additionally, sensitivity analysis scenarios, depicted in the Tornado chart, reveal that supply chain risks have a substantial impact on performance criteria. According to this scenario analysis, the primary risk affecting quality and cost target nodes is operational risk, while the major risk affecting the product delivery time node is distribution risk, and the primary risk influencing profitability is demand risk. Results from both pessimistic and optimistic scenario analyses under the second scenario of the research indicate that in the pessimistic state, the presence of a high percentage of these risks significantly negatively impacts quality performance. Conversely, in optimistic scenarios, where these risk factors are not present, improvements in quality's functional dimension exhibit the most substantial impact.ConclusionWhen introducing a new product to the market, evaluating and managing supply chain uncertainties is essential due to the mutual influence of new product development and the supply chain. Supply chain risk management, which commences with the accurate identification and assessment of risks and proceeds with appropriate responses, is crucial for providing efficient and effective new products to the market. In addition to employing the Bayesian network method, a highly effective tool in supply chain risk analysis, we have endeavored to evaluate the simultaneous impact of risks on product performance and assess the severity of risk impacts under various scenarios, including optimistic, pessimistic, and sensitivity analyses. Scenario building proves to be an effective method for validating a developed model to measure the impact of risks under different conditions on target criteria.
Mostafa Ebrahimpour Azbari; Mohsen Akbari; Fatemeh Rafiei Rashtababdi
Abstract
Today, organizations in an environment with growing changes, should be flexible enough to manage unpredictable threats and opportunities in an uncertain future and lead to better performance. Also, they should optimize their business processes to achieve operational efficiency. Besides, Operational absorptive ...
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Today, organizations in an environment with growing changes, should be flexible enough to manage unpredictable threats and opportunities in an uncertain future and lead to better performance. Also, they should optimize their business processes to achieve operational efficiency. Besides, Operational absorptive Capacity is a significant learning capabilities that may explain why some companies are enable to create a more effective response to environmental uncertainties. In this study, the impact of environmental uncertainty mediated by manufacturing flexibility and operational efficiency and moderating role of operational absorptive capacity on the performance of manufacturing firms has been tested. Also, the effect of manufacturing flexibility on the operational efficiency has been tested. A questionnaire is used as an instrument to collect data that is provided by experts and managers of 101 manufacturing companies in Rasht province. For the data analysis, structural equation modeling techniques (SEM) with the approach of Partial Least Squares (PLS) has been used. The results show that the company's performance can be improved by increasing manufacturing flexibility and operational efficiency . Also, with increasing flexibility, can provide more effective responses to environmental changes. The results confirmed the effect of manufacturing flexibility on the operational efficiency, as well as moderating role of operational absorptive capacity
