Predicting the impact of operational and financial variables on bullwhip effect using threshold regression: Indian context

2020 ◽  
Vol 13 (2) ◽  
pp. 211-227
Author(s):  
Sachin Gupta ◽  
Anurag Saxena
Keyword(s):  
Supply Chain ◽  
Linear Regression Analysis ◽  
Bullwhip Effect ◽  
Mitigation Strategies ◽  
Threshold Region ◽  
Threshold Regression ◽  
Content Type ◽  
Financial Variables ◽  
Novel Approach ◽  
The Impact

Purpose The operational aspects of supply chain, when handled correctly, results in diminishing the impact of the bullwhip effect. The purpose of this study is to analyze the impact of operational and financial variables on the bullwhip effect. Various operational factors that contribute to the bullwhip effect in a supply chain are identified and their impact on variability in production is measured at manufacturer’s end in the supply chain. Design/methodology/approach Ten different sectors of the Indian economy are identified and analyzed on the basis of bullwhip effect. The ratio of change in production with respect to change in demand is taken as a metric to measure the bullwhip effect. Initially, the impact of identified variables on bullwhip effect is analyzed using the linear regression analysis and then to gain more insights, the threshold regression model is applied according to the change in bullwhip ratio. Findings The study identifies four threshold regions in which bullwhip ratio is changing its slope considerably. The operational and financial variables impacting bullwhip effect differently in these four regions provide useful insights about how the variables are impacting the bullwhip effect. Research limitations/implications Past 11 years of observations on identified operational and financial variables are studied for ten different sectors. The operational and financial variables are identified on basis of available literature but may not be exhaustive in nature. Practical implications The present study implies that the emphasis must be given to the magnitude of the bullwhip ratio. Strategies must be adopted that result in mitigation of bullwhip effect. Such mitigation strategies must not only be restricted on the basis of type of product or sector, perhaps they must be on the basis of threshold region of bullwhip ratio. Originality/value The study suggests a novel approach to study the bullwhip effect in supply chain management using the application of threshold regression considering the bullwhip ratio as a threshold variable.

Investigating the impact of inventory inaccuracy on the bullwhip effect in RFID-enabled supply chains using colored petri nets

2019 ◽  
Vol 14 (2) ◽  
pp. 360-384 ◽  
Author(s):  
Maria Drakaki ◽  
Panagiotis Tzionas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Petri Nets ◽  
Information Sharing ◽  
Bullwhip Effect ◽  
Colored Petri Nets ◽  
Content Type ◽  
Multi Stage ◽  
The Impact ◽  
Serial Supply Chains

PurposeInformation distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.Design/methodology/approachA simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.FindingsThe bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.Research limitations/implicationsInformation sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.Originality/valueColored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.

Mitigating supply chain disruptions – a normal accident perspective

2014 ◽  
Vol 19 (2) ◽  
pp. 142-152 ◽  
Author(s):  
Kathryn A. Marley ◽  
Peter T. Ward ◽  
James A. Hill
Keyword(s):  
Supply Chain ◽  
Theoretical Basis ◽  
Design Methodology ◽  
Mitigation Strategies ◽  
Management Approach ◽  
Processing Plant ◽  
Supply Chain Disruptions ◽  
Content Type ◽  
Steel Processing ◽  
The Impact

Purpose – Existing supply chain literature provides examples of countermeasures that firms can adopt to mitigate abnormal or catastrophic supply chain disruptions. However, none address reducing interactive complexity prior to adopting countermeasures to mitigate everyday or normal supply chain disruptions. Most mitigation strategies focus on adding capabilities or resources to protect an organization. Here, the authors aim to consider an alternative strategy of examining current processes to determine whether processes can be simplified by using the normal accident theory and its constructs of interactive complexity and coupling as a theoretical basis. Design/methodology/approach – The authors develop a model based on the normal accident theory and use logistic regression to test their propositions in the context of a steel processing plant and its customers. Findings – The findings show the importance of reducing interactive complexity to mitigate supply chain disruptions. However, high inventory is not considered a significant countermeasure, and high inventory levels may increase the likelihood of causing a disruption downstream. These findings support the lean management approach of operating under low inventory levels while eliminating complexity to make problems more visible, causing fewer disruptions. Originality/value – While others have examined the impact of mitigation strategies conceptually, no study has captured information from actual supply chain disruptions to assess how interactive complexity and inventory levels affect disruption potential at downstream customers' facilities. Capturing information from supply chain disruptions enables managers to assess the situation as the disruption is occurring. The authors suggest a strategy in which countermeasures that increase slack in the system should be considered only after the system is sufficiently simplified to mitigate disruptions.

Operations-based classification of the bullwhip effect

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Gupta ◽  
Anurag Saxena
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Logistic Regression ◽  
Supply Chain ◽  
Discriminant Analysis ◽  
Bullwhip Effect ◽  
Content Type ◽  
Operational Variables ◽  
Artificial Neural ◽  
The Impact

Purpose Present study deals with the most discussed rather than addressed yet still an unsolved problem of supply chain known as the bullwhip effect. Operational variables affecting the bullwhip effect are identified and their role in causing the bullwhip effect has been explored using artificial neural networks. The purpose of this study is to analyze the impact of identified operational reasons that affect the bullwhip effect and to analyze the bunch of variables that are more prominent in explaining the phenomenon of the bullwhip effect. Design/methodology/approach Ten major sectors of the Indian economy are analyzed for the bullwhip effect in the present study, and the operational variables affecting the bullwhip effect in these sectors are identified. The bullwhip metric is developed as the ratio of variance in production to the variance in the demand. The impact of identified operation variables on the bullwhip effect has been discussed using the artificial neural network technique known as multilayer perceptron. The classification is also performed using neural network, logistic regression and discriminant analysis. Findings The operation variables are found to be varying with respect to sectors. The study emphasizes that analyzing the right set of operation variables with respect to the sector is required to deal with the complex problem, the bullwhip effect. The operational variables affecting the bullwhip effect are identified. The classification result of the neural network is compared with those of the logistic regression and discriminant analysis, and it is found that the dynamism present in the bullwhip effect is better classified by neural network. Research limitations/implications The study used 11 years of observations to analyze the bullwhip effect on the basis of operational variables. The bullwhip effect is a complex phenomenon, and it is explained on the basis of an extensive set of operational variables which is not exhaustive. Further, the behavioral aspect (bullwhip because of decision-making) is not explored in the present study. Practical implications The operational aspect plays a gigantic role to explain and deal with the bullwhip effect. Strategies to mitigate the bullwhip effect must be in accordance with the operational variables impacting the sector. Originality/value The study suggests a novel approach to study the bullwhip effect in supply chain management using the application of neural networks in which operational variables are taken as predictor variables.

Relation between foreign ownership and firm value – Fixed-effect panel threshold regression analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruchi Kansil
Keyword(s):  
Firm Value ◽  
Foreign Ownership ◽  
Fixed Effect ◽  
Threshold Regression ◽  
Firm Characteristics ◽  
Content Type ◽  
Threshold Levels ◽  
Novel Approach ◽  
The Impact ◽  
Panel Threshold Regression

PurposeThe paper examines the differential impact of various firm characteristics on firm value across various threshold levels of foreign ownership.Design/methodology/approachUsing a panel of 408 Indian publicly listed companies for the period during 2010–2018, a fixed-effect panel threshold regression model is adapted to study the threshold effects between foreign ownership and firm value. Tobin's Q is used as a proxy for firm value.FindingsThe study identifies three threshold levels, that is, four threshold regions in which foreign ownership changes its slope considerably. Various firm characteristics impact firm value differently in these four regions.Research limitations/implicationsThe study employs observations of the past nine years on variables identified as firm characteristics impacting firm value. Some variables are dropped due to the problem of multicollinearity. The employed variables may not be exhaustive in nature.Practical implicationsThe present study implies that there exists no impact of foreign ownership on the value of the firm. Foreign investors invest for financial considerations and not with the objective of governing the firms. The governance effect of foreign investments is negligible, so their activism in the firms needs to be encouraged.Originality/valueThe study employs a novel approach to study the impact of foreign ownership on firm value applying fixed effect panel data threshold regression, considering foreign ownership as a proxy of corporate governance.

Exploring vulnerability and resilience of shipping for coastal communities during disruptions: findings from a case study of Vancouver Island in Canada

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Samsul Islam ◽  
Floris Goerlandt ◽  
Mohammad Jasim Uddin ◽  
Yangyan Shi ◽  
Noorul Shaiful Fitri Abdul Rahman
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Disaster Preparedness ◽  
Service Providers ◽  
Vancouver Island ◽  
Coastal Communities ◽  
Mitigation Strategies ◽  
Content Type ◽  
The Impact

PurposeThis study aims to improve understanding of how coastal maritime transport system of Vancouver Island would be disrupted in disaster events, and the strategies could be used to address such risks. Any transport disruption at the maritime leg of the supply chain can affect the needs of vulnerable residents and thus, the supply of many goods to coastal communities.Design/methodology/approachThis case study focuses on the disruption that can be expected to occur for ferries that serves coastal communities of Vancouver Island in Canada. A landslide scenario in the Fraser River (which connects coastal communities) is developed, and interviews and focus groups are used to gain understanding of the vulnerability and resilience of shipping.FindingsThe findings show that the maritime leg of the supply chain for the coastal communities of Vancouver Island is resilient to a landslide disruption of ferries. Besides, there would be no impact on the operability of tugs and barges. This study also offers suggestions for creating the conditions for increasing resilience of maritime supply chains to any such disruption.Research limitations/implicationsA research gap exists with respect to minimizing disruption in maritime supply chains, mainly in regard to lessening the impact on the vulnerable residents of coastal communities. This study contributes to filling this gap in the literature.Practical implicationsThe findings have significant implications for maritime service providers and for people working on disaster preparedness, emergency response and recovery.Originality/valueStudies which focus on alleviating the impact of disruptions in the maritime supply chains and the mitigation strategies for coastal communities are scarce in the literature.

A purchasing portfolio model for humanitarian supply chain resilience: perspectives from a development aid context

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Narath Bhusiri ◽  
Ruth Banomyong ◽  
Puthipong Julagasigorn ◽  
Paitoon Varadejsatitwong ◽  
Nirpa Dhami
Keyword(s):  
Supply Chain ◽  
Humanitarian Aid ◽  
Development Aid ◽  
Mitigation Strategies ◽  
Holistic View ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Supply Disruptions ◽  
Humanitarian Supply Chain ◽  
The Impact

PurposeThe impact of supply disruptions from unplanned events can cause goods shortage, limited responsiveness and high opportunity cost thus compromising development aid programmes' achievement targets. These situations force humanitarian aid agencies to develop new strategies for effectively managing their supplies. The purpose of this paper is to illustrate the foundation of humanitarian supply chain resilience through the development of an adapted Kraljic portfolio model.Design/methodology/approachAction research was used to adapt and validate the Kraljic portfolio model to the development aid context. The research team worked with a humanitarian aid agency in developing criterions and used Analytical Hierarchical Process (AHP) in weighting those key criterions.FindingsThe adapted portfolio model was able to evaluate purchases done by the aid agency by incorporating different perspectives related to the strategic importance of purchase and supply vulnerability. In particular, development aid programmes require large supplies annually. Better classification offers improved visualisation of purchases, leading to a more precise adoption of mitigation strategies and policies to minimise supply disruption risks.Research limitations/implicationsAdapting the Kraljic portfolio model is a stepping-stone to building humanitarian supply chain resilience. The proposed humanitarian supply chain resilience framework is based on the foundation that current humanitarian supply chain needs to be re-engineered. In order to re-engineer, the supply base strategy must first be revisited.Practical implicationsMany aid agencies do not have a holistic view on their purchases and commonly apply a transactional classification of purchases that only considers the consumption values. Purchasing strategies mostly focus on cost minimisation, whereas risk mitigations have been disregarded. The proposed portfolio model overcomes these drawbacks. Societal impact may be limited but development aid agencies will be able to offer more reliable aid delivery as part of their mandate.Originality/valueThe proposed portfolio model is among the first tool to guide humanitarian aid agencies to develop procurement strategies to alleviate supply disruptions and increase development aid programmes resilience.

Supply chain risk mitigation strategies during COVID-19: exploratory cases of “make-to-order” handloom saree apparel industries

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vishwas Dohale ◽  
Priya Ambilkar ◽  
Angappa Gunasekaran ◽  
Priyanka Verma
Keyword(s):  
Supply Chain ◽  
Risk Mitigation ◽  
Apparel Industry ◽  
Mitigation Strategies ◽  
Supply Chain Risk ◽  
Content Type ◽  
Make To Order ◽  
Risk Mitigation Strategies ◽  
Multiple Case ◽  
The Impact

PurposeThis study attempts to identify the supply chain risks (SCRs) induced during the COVID-19 disruption in an Indian handloom saree industry and determine suitable risk mitigation strategies (RMSs) to overcome the impact of the epidemic disruption.Design/methodology/approachThis work determined 11 SCRs through an extensive literature review in the context of the handloom apparel industry and validated through the experts. Further, a multiple case-based approach is used in this research. Within case and cross-case analyses of four relevant Indian handloom “make-to-order” saree manufacturing firms are conducted to determine the severity of the SCRs considering the pandemic situations to identify appropriate strategies to mitigate the shock of SCRs.FindingsThis study identified the critical SCRs in the context of the Indian handloom “make-to-order” saree industries that emerged during the COVID-19 and proposed a risk mitigation strategy matrix (RMSM) to address the SCRs based on their criticality and predictability dimensions.Research limitations/implicationsThe study provides a novel contribution to the body of knowledge on supply chain risk management (SCRM) in the form of the RMSM tool. Supply chain managers from the different sectors can extend the proposed RMSM to overcome the SCRs. Multiple case analyses facilitate supply chain professionals working in handloom apparel industries to benchmark and adopt the proposed RMSs in their firm.Originality/valueThis research is one of its kind that carried exploratory investigation of the handloom apparel industry cases to assess and determine the strategies for mitigating the SCRs caused during a pandemic outbreak.

The push effect of risks on supply chain performance: service-oriented firms

2019 ◽  
Vol 25 (7) ◽  
pp. 1734-1758
Author(s):  
Huy Truong Quang ◽  
Yoshinori Hara
Keyword(s):  
Supply Chain ◽  
Risk Mitigation ◽  
Mitigation Strategies ◽  
Content Type ◽  
Demand Chain ◽  
Road Map ◽  
Competitive Model ◽  
Service Oriented ◽  
Risk Mitigation Strategies ◽  
The Impact

Purpose The purpose of this paper is to examine the push effect of risk on supply chain (SC) performance, a new concept in the SC risk body of literature, at service-oriented firms. Design/methodology/approach Two models were compared: first, contains relationships between risks that show the mechanism of the push effect, i.e. the theoretical model. The other, only exists in direct effects of risks on SC performance, i.e. the competitive model. Findings Test results proved that the mechanism of the push effect can increase the degree of impact of each and all risks on outputs. By the push effect, risks can explain up to 65 percent variance of SC performance compared with 52 percent of the model without push effect. Moreover, the research found two kinds of the push effect: positive – increasing the impact of “pushed” factors on outputs and vice versa for negative. Research limitations/implications The mechanism of the push influence will be broken if mutual interaction among risks was minimized. Practitioners and managers can apply the resultant model as a “road map” in their context to achieve this purpose. Originality/value Vargo and Lusch (2008) argued that service-oriented firms will be a new trend since the modern-day industry tends to more focus on customer demand. SC management gradually shifted toward demand chain management that organizations will not make and sell units of output but producing customized services to customers (Walters, 2008). This transformation has led to the emergence of new risks, the impact of risk on the SC also varies and the mismatch of the current risk mitigation strategies (Lusch et al., 2007). Dealing with these changes is the purpose of this research.

Classification of Operational and Financial Variables Affecting the Bullwhip Effect in Indian Sectors: A Machine Learning Approach

2019 ◽  
Vol 12 (3) ◽  
pp. 171-179 ◽  
Author(s):  
Sachin Gupta ◽  
Anurag Saxena
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Product Life Cycle ◽  
Consumer Preference ◽  
Bullwhip Effect ◽  
Machine Learning Techniques ◽  
Chain Management ◽  
Financial Variables

Background: The increased variability in production or procurement with respect to less increase of variability in demand or sales is considered as bullwhip effect. Bullwhip effect is considered as an encumbrance in optimization of supply chain as it causes inadequacy in the supply chain. Various operations and supply chain management consultants, managers and researchers are doing a rigorous study to find the causes behind the dynamic nature of the supply chain management and have listed shorter product life cycle, change in technology, change in consumer preference and era of globalization, to name a few. Most of the literature that explored bullwhip effect is found to be based on simulations and mathematical models. Exploring bullwhip effect using machine learning is the novel approach of the present study. Methods: Present study explores the operational and financial variables affecting the bullwhip effect on the basis of secondary data. Data mining and machine learning techniques are used to explore the variables affecting bullwhip effect in Indian sectors. Rapid Miner tool has been used for data mining and 10-fold cross validation has been performed. Weka Alternating Decision Tree (w-ADT) has been built for decision makers to mitigate bullwhip effect after the classification. Results: Out of the 19 selected variables affecting bullwhip effect 7 variables have been selected which have highest accuracy level with minimum deviation. Conclusion: Classification technique using machine learning provides an effective tool and techniques to explore bullwhip effect in supply chain management.

An empirical examination of firm financial performance along dimensions of supply chain resilience

2017 ◽  
Vol 40 (3) ◽  
pp. 254-269 ◽  
Author(s):  
Xun Li ◽  
Qun Wu ◽  
Clyde W. Holsapple ◽  
Thomas Goldsby
Keyword(s):  
Supply Chain ◽  
Financial Performance ◽  
Three Dimensions ◽  
Empirical Examination ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Critical Dimensions ◽  
Firm Financial Performance ◽  
Supply Chain Agility ◽  
The Impact

Purpose This paper aims to investigate the impact of three critical dimensions of supply chain resilience, supply chain preparedness, supply chain alertness and supply chain agility, all aimed at increasing a firm’s financial outcomes. In a turbulent environment, firms require resilience in their supply chains to prepare for potential changes, detect changes and respond to actual changes, thus providing superior value. Design/methodology/approach Using survey data from 77 firms, this study develops scales for preparedness, alertness and agility. It then tests their hypothesized relationships with a firm’s financial performance. Findings The results reveal that the three dimensions of supply chain resilience (i.e. preparedness, alertness and agility) significantly impact a firm’s financial performance. It is also found that supply chain preparedness, as a proactive resilience capability, has a greater influence on a firm’s financial performance than the reactive capabilities including alertness and agility, suggesting that firms should pay more attention to proactive approaches for building supply chain resilience. Originality/value First, this study develops a comparatively comprehensive definition for supply chain resilience and explores its dimensionality. Second, this study provides empirically validated instruments for the dimensions of supply chain resilience. Third, this study is one of the first to provide empirical evidence for direct impact of supply chain resilience dimensions on a firm’s financial performance.

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