Supply chain management and market responsiveness: a simulation study

Abstract

<jats:sec> <jats:title content-type="abstract-subheading">Purpose</jats:title> <jats:p>This study aims to provide a practical solution to the relationship between supply chain (SC) integration and market responsiveness (MR). A method is proposed to integrate SC and MR parameters, namely, product supply and demand in the context of low-value commodities (e.g. cement).</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title> <jats:p>Simulation and forecasting approaches are adopted to develop a potential procedure for addressing demand during lead time. To establish inventory measurements (safety stock and reorder level) and increase MR and the satisfaction of customer’s needs, this study considers a downstream SC including manufacturers, depots and central distribution centers that satisfies an unbounded number of customers, which, in turn, transport the cement from the industrialist.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Findings</jats:title> <jats:p>The demand during lead time is shown to follow a gamma distribution, a rare probability distribution that has not been considered in previous studies. Moreover, inventory measurements, such as the safety stock, depending on the safety factor under a certain service level (SL), which enables the SC to handle different responsiveness levels in accordance with customer requests. In addition, the quantities of the safety stock and reorder point represent an optimal value at each position to avoid over- or understocking. The role of SC characteristics in MR has largely been ignored in existing research.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Originality/value</jats:title> <jats:p>This study applies SC flexibility analyzes to overcome the obstacles of analytical methods, especially when the production process involves probabilistic variables such as product availability and demand. The use of an efficient method for analyzing the forecasting results is an unprecedented idea that is proven efficacious in investigating non-dominated solutions. This approach provides near-optimal solutions to the trade-off between different levels of demand and the SC responsiveness (SLs) with minimal experimentation times.</jats:p> </jats:sec>

Examining the impact of strategic supplier partnership, customer relationship and supply chain responsiveness on operational performance: the moderating effect of demand uncertainty

“…It should also be noted that variation and unpredictability in customers' needs are the major sources of demand uncertainty. Hence, practitioners should enhance information-sharing mechanisms among downstream players (Aljanabi and Ghafour, 2021) to improve the order forecast horizon. This will result in predicting the demand forecast precisely which subsides the effect of demand uncertainty and improves the responsiveness.…”

Environmental sustainability through designing reverse logistical loops: case research of poultry supply chains using system dynamics

“…Saeed (2008) concludes that variables in forecasts must be carefully chosen as tracking variables in supply chains. Additionally, a realistic approach is obtainable by combining supply chain and demand responsiveness by the use of effective simulation studies (Aljanabi and Ghafour, 2020). Größler et al (2008) analyze the classical problem of price reduction and product enhancements to capture market share using SD method.…”

An investigation of transportation logistics strategy on manufacturing supply chain responsiveness in developing countries: the mediating role of delivery reliability and delivery speed

“…In this situation, responsiveness is considered one of the most important practices needed to be implemented by manufacturing firms to attain a relative advantage ( Ayoub and Abdallah 2019 ; Banerjee et al., 2018 ). Aljanabi and Ghafour (2021) state that by increasing the demanding levels of customization and product variety in the marketplace, manufacturing firms with the capability to react quickly to meet customer demands on time will achieve an important and decisive competitive advantage over their competitors. Towards sub-sectors of the manufacturing industry electronics/IT, food processing, chemical/cosmetics, textile, pharmaceutical, and furniture, firms are formulating their strategies in order to enhance their responsiveness to customer demands by providing various products with very short lead times through suitable and convenient delivery mode(s).…”

“…Thus, most of their supply chains and transportation logistics have become a potential benefit to achieve a competitive advantage to improve their performance and serve their customers in a perfect way to let them be more satisfied. However, the current intensified competition is not exclusively between different manufacturing firms, but also among other competitors and partners external to their SC network ( Aljanabi and Ghafour, 2021 ; Sharma and Modgil, 2019 ).…”