1. North Carolina Agricultural and Technical State University
An Examination of the Antecedents of Responsiveness in Aggregate Production Planning (APP) under Supply Chain Risks
Presented by S.Vahid Reza Nooraie
Department of Industrial and Systems Engineering
INTRODUCTION
This paper examines the relationships among flexibility,
agility and, responsiveness in a supply chain under risk of
disruptions. Based on the review of the literature, a
conceptual model is developed to address flexibility-agility-
responsiveness relationships, which are further examined
using hypotheses testing. Numerical values for hypothesis
testing are obtained from a robust multi-objective mixed
integer nonlinear programming model for an Aggregate
Production Planning (APP) model exposed to supply chain
risks. Based on the review or the literature, we propose a
theoretical framework linking elements of uncertainty with
agility, flexibility and internal/external integration to
determine the relationship between responsiveness and
customer satisfaction under demand risk. According to the
numerical results obtained from a manufacture’s supply
chain, we find that there is a significant relationship between
flexibility and internal integration with responsiveness. Our
findings suggest that in a supply chain under demand risk,
improvement in agility is contingent upon flexibility
improvement. Finally, we suggest investment on flexibility
and internal integration to enhance responsiveness to meet
customer demand fluctuations.
CONCLUSION
ABSTRACT RESULTS & ANALYSIS
This study seeks to contribute to the OM literature by
proposing a conceptual model that relates responsiveness,
flexibility and agility in a supply chain under demand risk.
We attempt to better define the meaning boundaries of the
terms by not only specifying what our interpretation of the
literature indicates they are, but also, and importantly, by
specifying how they are interrelated together. This
clarification forms the basis for our proposed conceptual
model through reviewing the prior literature (Braunscheidel
and Suresh, 2009; Williams et al., 2013). Using a
combination of robust optimization and hypothesis testing,
we examine the validity of a conceptual model for flexibility-
agility-responsiveness relationship for an APP under demand
risk. We later discuss how supply chain responsiveness is
related to total cost and shortage of an aggregate production
planning model to satisfy demand under risk. The next
section describes a literature review, which addresses the
theoretical use of the terms as they appear in the literature in
various contexts.
RESEARCH QUESTIONS
H1: Internal integration is positively related to supply chain agility?
H2: External flexibility is positively related to supply chain agility?
H3: External flexibility is positively related to supply chain responsiveness?
H4: Supply chain agility is positively related to supply chain
responsiveness?
H5: Internal integration is positively related to supply chain responsiveness?
ROBUST MODEL
Min 𝑖,𝑗,𝑔,𝑡 𝑎𝑖𝑗 𝑐𝑗𝑔
𝜉
𝑋𝑖𝑗𝑔𝑡 + 𝑠,𝑚,𝑗,𝑡 𝐶𝑀𝑠𝑚𝑡
𝜉
𝑆𝑈𝑃𝑠𝑚𝑗𝑡 + 𝑘,𝑗,𝑡 𝑆𝐿 𝑘𝑗𝑡
𝜉
𝐿 𝑘𝑗𝑡 +
𝑘,𝑗,𝑡 𝐹𝐶 𝑘𝑘′𝑗𝑡
𝜉
𝐹𝐿 𝑘𝑘′𝑗𝑡 + 𝑘,𝑗,𝑡 𝐻𝐶 𝑘𝑘′𝑗𝑡
𝜉
𝐻𝐿 𝑘𝑘′𝑗𝑡 +
𝑘,𝑘′,𝑗,𝑡 𝑇𝐶 𝑘𝑘′𝑗
𝜉
𝑈𝐿 𝑘𝑘′𝑗𝑡 + 𝑚,𝑗,𝑡 𝐶𝐼𝑀 𝑚𝑗𝑡
𝜉
𝐼𝑀 𝑚𝑗𝑡 + 𝑖,𝑗,𝑡 𝐶𝐼𝑃𝑖𝑗𝑡
𝜉
𝐼𝑃𝑖𝑗𝑡 +
𝑠,𝑚,𝑗,𝑡 𝑇𝐶𝑆𝑠𝑗𝑡
𝜉
𝑆𝑈𝑃𝑠𝑚𝑗𝑡 + 𝑖,𝑗,𝑐,𝑡 𝑇𝐶𝐶𝑖𝑐𝑡
𝜉
𝐶𝑈𝑆𝑖𝑗𝑐𝑡 + 𝑖,𝑐,𝑡 𝜋𝑖𝑐𝑡
𝜉
𝐵𝐷𝑖𝑐𝑡
𝜉
-
𝑖,𝑗,𝑐,𝑡 𝑃𝑖𝑐𝑡
𝜉
𝐶𝑈𝑆𝑖𝑗𝑐𝑡
Min 𝑡 𝑀𝑎𝑥 𝑐 𝑖 𝐵𝐷𝑖𝑐𝑡
𝜉
Subject to
𝐼𝑃𝑖𝑗𝑡 = 𝐼𝑃𝑖𝑗 𝑡−1 + 𝑔 𝑋𝑖𝑗𝑔𝑡 - 𝑐 𝐶𝑈𝑆𝑖𝑗𝑔𝑐𝑡 ∀ 𝑖, 𝑗, 𝑡,
𝐼𝑀 𝑚𝑗(𝑡−1) + 𝑠 𝑆𝑈𝑃𝑠𝑚𝑗[𝑡−𝐿𝑇𝑠𝑗] - 𝑔,𝑖 𝑋𝑖𝑗𝑔𝑡 𝛾𝑖𝑚 ∀ 𝑚, 𝑗, 𝑡,
𝐿 𝑘𝑗𝑡 = 𝐿 𝑘𝑗(𝑡−1) + 𝐻𝐿 𝑘𝑘′𝑗𝑡 - 𝐹𝐿 𝑘𝑘′𝑗𝑡 + 𝑘′ 𝑈𝐿 𝐾′𝑘𝑗𝑡 - 𝑘′ 𝑈𝐿 𝐾𝑘′𝑗𝑡 ∀ 𝑘, 𝑗, 𝑡,
𝑘 𝐿 𝑘𝑗𝑡 𝜐 𝑘 (𝑇𝐶𝐴𝑃1𝑡𝑗 + 𝑇𝐶𝐴𝑃2𝑡𝑗) ≥ 𝑖,𝑔ԑ{1,2} 𝑋𝑖𝑗𝑔𝑡 𝑎𝑖𝑗
𝜉
∀ 𝑗, 𝑡,
𝑖 𝑋𝑖𝑗3𝑡 𝜐𝑙 𝑎𝑖𝑗
𝜉
≤ 𝑇𝐶𝐴𝑃3𝑗𝑡 ∀ 𝑗, 𝑡,
𝐵𝐷𝑖𝑐𝑡
𝜉
= 𝐵𝐷𝑖𝑐(𝑡−1)
𝜉
+ 𝐷𝑖𝑐𝑡
𝜉
- 𝑗 𝐶𝑈𝑆𝑖𝑗𝑐[𝑡−𝐿𝑇 𝑗𝑐] ∀ 𝑖, 𝑐, 𝑡, 𝜉,
𝑚 𝐼𝑀 𝑚𝑗𝑡 ≤ 𝐶𝐴𝑃𝑀𝑗 ∀ 𝑗, 𝑡,
𝑖 𝐼𝑃𝑖𝑗𝑡 ≤ 𝐶𝐴𝑃𝑃𝑗 ∀ 𝑗, 𝑡,
𝑘(𝐹𝐿 𝑘𝑘′𝑗𝑡 + 𝐻𝐿 𝑘𝑘′𝑗𝑡) ≤ 𝛼(𝑡−1) 𝑘 𝐿 𝑘𝑗(𝑡−1) ∀ 𝑗, 𝑡,
𝐹𝐿 𝑘𝑘′,𝑗𝑡 + 𝑘′ 𝑈𝐿 𝑘𝑘′𝑗𝑡 ≤ 𝐿 𝑘𝑗(𝑡−1) ∀ 𝑘, 𝑗, 𝑡,
𝑘′ 𝑈𝐿 𝑘𝑘′𝑗𝑡 . 𝐹𝐿 𝑘𝑘′𝑗𝑡 = 0 ∀𝑘, 𝑗, 𝑡,
𝑈𝐿 𝑘′𝑘𝑗𝑡 ≤ 𝑀𝑈𝑃 𝐾𝐾′ ∀𝑘, 𝑘′
, 𝑗, 𝑡,
𝑗 𝑆𝑈𝑃𝑠𝑚𝑗𝑡≤ 𝐶𝐴𝑃𝑆𝑠𝑚𝑡 ∀𝑠, 𝑚, 𝑡,
𝑋𝑖𝑗𝑔𝑡, 𝑆𝑈𝑃𝑠𝑚𝑗𝑡, 𝐼𝑀 𝑚𝑗𝑡, 𝐼𝑃𝑖𝑗𝑡,𝐶𝑈𝑆𝑖𝑗𝑐𝑡, 𝐵𝐷𝑖𝑐𝑡
𝜉
≥ 0
𝐿 𝑘𝑗𝑡, 𝐹𝐿 𝑘𝑘′𝑗𝑡, 𝐻𝐿 𝑘𝑘′𝑗𝑡, 𝑈𝐿 𝑘𝑘′𝑗𝑡, ≥ 0 and integer ∀𝑖, 𝑗, 𝑙, 𝑐, 𝑔, 𝑘, 𝑠, 𝑚, 𝑡.
This research was supported by an award from the National Science Foundation (NSF), “Research Initiation Award Grant: Understanding Risks and Disruptions in Supply Chains and their Effect on Firm
and Supply Chain Performance”, Award Number 1238878.)
The results indicate that the proposed model can provide a promising approach to providing an efficient production
planning in the context of the supply chain exposed to different types of risks. We offered a decision policy based on
the relationship among flexibility, agility, internal integration, and responsiveness to show how the most appropriate
strategies based on customer demands as it related to change by quality, quantity, variety, and lead-time. Through this
process we were able to demonstrate a conceptual model based on flexibility, agility, internal integration and
responsiveness to cope demand risk in supply chain through minimizing shortage.