Customer–Supplier Relationships and Abnormal Accruals

2020 ◽  
Vol 23 (04) ◽  
pp. 2050027
Author(s):  
May Xiaoyan Bao ◽  
Matthew T. Billett ◽  
Yixin Liu
Keyword(s):  
Supply Chain ◽  
Coefficient Of Variation ◽  
Bullwhip Effect ◽  
Transmission Channel ◽  
Customer Demand ◽  
Demand Shock ◽  
Supplier Relationships ◽  
Amplification Ratio ◽  
Abnormal Accruals ◽  
The Impact

We investigate the relationship between customer and supplier firms’ abnormal accruals to examine whether the supply chain is an important transmission channel of abnormal accruals. We propose “earnings management” hypothesis and “customer demand shock” hypothesis. Empirically, we examine the relation between a supplier’s estimated abnormal accruals and those of its major customers using Compustat Business Segment Files over the period 1987–2015. To further explore the demand shock channel, we directly test the impact of the bullwhip effect (BWE) on the linkage in abnormal accruals along the supply chain. Following the literature in operation management, we construct the amplification ratio, measured as the coefficient of variation of a firm’s orders divided by the coefficient of variation of the firm’s demand. We find that customer firms’ demand shocks link customer and supplier abnormal accruals as they propagate along the supply chain, via the BWE. Our evidence supports “customer demand shock” hypothesis. Consistent with the view that improving predictions on orders from their customers would mitigate this BWE, we find that a customer’s abnormal accruals have a much smaller impact on those of its suppliers whose auditors have expertise in the customer’s industries. Overall, our results suggest that the supply chain is an important transmission channel of abnormal accruals, and auditor expertise serves to reduce information opaqueness during this process. Our paper contributes to the literature examining the impact of BWEs on firms’ financial performance and the role of auditors’ expertise in reducing information opaqueness in supply chain.

scholarly journals Reading on and between the lines: risk identification in collaborative and adversarial buyer–supplier relationships

2018 ◽  
Vol 23 (4) ◽  
pp. 351-376 ◽  
Author(s):  
Yiyi Fan ◽  
Mark Stevenson
Keyword(s):  
Social Capital ◽  
Supply Chain ◽  
Risk Identification ◽  
Social Capital Theory ◽  
Future Research ◽  
Supplier Relationships ◽  
Content Type ◽  
Signalling Theory ◽  
Multi Level ◽  
The Impact

Purpose This paper aims to investigate how supply chain risks can be identified in both collaborative and adversarial buyer–supplier relationships (BSRs). Design/methodology/approach This research includes a multiple-case study involving ten Chinese manufacturers with two informants per organisation. Data have been interpreted from a multi-level social capital perspective (i.e. from both an individual and organisational level), supplemented by signalling theory. Findings Buyers use different risk identification strategies or apply the same strategy in different ways according to the BSR type. The impact of organisational social capital on risk identification is contingent upon the degree to which individual social capital is deployed in a way that benefits an individual’s own agenda versus that of the organisation. Signalling theory generally complements social capital theory and helps further understand how buyers can identify risks, especially in adversarial BSRs, e.g. by using indirect signals from suppliers or other supply chain actors to “read between the lines” and anticipate risks. Research limitations/implications Data collection is focussed on China and is from the buyer side only. Future research could explore other contexts and include the supplier perspective. Practical implications The types of relationships that are developed by buyers with their supply chain partners at an organisational and an individual level have implications for risk exposure and how risks can be identified. The multi-level analysis highlights how strategies such as employee rotation and retention can be deployed to support risk identification. Originality/value Much of the extant literature on supply chain risk management is focussed on risk mitigation, whereas risk identification is under-represented. A unique case-based insight is provided into risk identification in different types of BSRs by using a multi-level social capital approach complemented by signalling theory.

scholarly journals A Model for understanding supply chain networks

2005 ◽  
Vol 5 (2) ◽  
pp. 55-63 ◽  
Author(s):  
Carlos Brito ◽  
Catarina Roseira
Keyword(s):  
Supply Chain ◽  
Conceptual Framework ◽  
Supply Management ◽  
Organisational Performance ◽  
Supplier Relationships ◽  
Supply Chain Networks ◽  
The Impact ◽  
The Way

Organisational performance tends to be highly dependent on suppliers' actions and on the way the relationships with them are managed by the buying company. Researchers have conducted extensive and valuable studies on the impact of supplier relationships in a network context. However, some important issues regarding supply management and its effects on the strategy of the buying firm have not been fully investigated. This article presents a model of supply chain networks developed on the basis of the conceptual framework of the IMP group. The aim is to contribute toward a better understanding of supply management through the integration of both relational, portfolio and network issues.

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.

Analysis and Verification of Bullwhip Effect Based on System Dynamics

2013 ◽  
Vol 340 ◽  
pp. 312-319
Author(s):  
Fu Xin Yang ◽  
Bai Lan Zhang ◽  
Zhi Yuan Su
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Correlation Coefficient ◽  
Lead Time ◽  
Process Model ◽  
Autoregressive Process ◽  
Bullwhip Effect ◽  
Simulation Software ◽  
Simulation Results ◽  
The Impact

To study the bullwhip effect (BWE) in supply chain (SC), this paper built two system dynamics (SD) models strictly referring to the AR(1) (autoregressive process) model constructed by Frank Chen. Using Vensim simulation software, it analyzed the impact of the correlation coefficient of demand, lead time, smoothing time of demand and information to BWE, and then put forward some proposals on how to reduce BWE. By contrasting the simulation results of SD models with the AR(1) models', it verifies the validity of the AR(1) model of Frank Chen from a simulation perspective. It also shows SD model combined with AR(1) model can analyze BWE in SC reliably and powerfully.

scholarly journals Exploring the Bullwhip Effect and Inventory Stability in a Seasonal Supply Chain

10.5772/56833 ◽  
2013 ◽  
Vol 5 ◽  
pp. 23 ◽  
Author(s):  
Francesco Costantino ◽  
Giulio Di Gravio ◽  
Ahmed Shaban ◽  
Massimo Tronci
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Performance Measures ◽  
Moving Average ◽  
Bullwhip Effect ◽  
Fill Rate ◽  
Supply Chain Dynamics ◽  
Effect Ratio ◽  
The Impact ◽  
Demand Seasonality

The bullwhip effect is defined as the distortion of demand information as one moves upstream in the supply chain, causing severe inefficiencies in the whole supply chain. Although extensive research has been conducted to study the causes of the bullwhip effect and seek mitigation solutions with respect to several demand processes, less attention has been devoted to the impact of seasonal demand in multi-echelon supply chains. This paper considers a simulation approach to study the effect of demand seasonality on the bullwhip effect and inventory stability in a four-echelon supply chain that adopts a base stock ordering policy with a moving average method. The results show that high seasonality levels reduce the bullwhip effect ratio, inventory variance ratio, and average fill rate to a great extent; especially when the demand noise is low. In contrast, all the performance measures become less sensitive to the seasonality level when the noise is high. This performance indicates that using the ratios to measure seasonal supply chain dynamics is misleading, and that it is better to directly use the variance (without dividing by the demand variance) as the estimates for the bullwhip effect and inventory performance. The results also show that the supply chain performances are highly sensitive to forecasting and safety stock parameters, regardless of the seasonality level. Furthermore, the impact of information sharing quantification shows that all the performance measures are improved regardless of demand seasonality. With information sharing, the bullwhip effect and inventory variance ratios are consistent with average fill rate results.

scholarly journals Study of the Bullwhip Effect in a Multistage Supply Chain with Callback Structure considering Two Retailers

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Junhai Ma ◽  
Liqing Zhu ◽  
Ye Yuan ◽  
Shunqi Hou
Keyword(s):  
Supply Chain ◽  
Moving Average ◽  
Bullwhip Effect ◽  
Lead Times ◽  
Chain Model ◽  
Supply Chain System ◽  
Forecasting Method ◽  
Supply Chain Model ◽  
The Impact ◽  
Demand Processes

With the purpose of researching the bullwhip effect when there is a callback center in the supply chain system, this paper establishes a new supply chain model with callback structure, which has a material supplier, a manufacture, and two retailers. The manufacture and retailers all employ AR(1) demand processes and use order-up-to inventory policy when they make order decisions. Moving average forecasting method is used to measure the bullwhip effect of each retailer and manufacture. We investigate the impact of lead-times of retailers and manufacture, forecasting precision, callback index, and marketing share on the bullwhip effect of both retailers and manufacture. Then we use the method of numerical simulation to indicate the different parameters in this supply chain. Furthermore, this paper puts forward some suggestions to help the enterprises to control the bullwhip effect in the supply chain with callback structure.

scholarly journals IDENTIFICATION EXISTENCE OF BULLWHIP EFFECT ON SUPPLY CHAIN PT. ABC

2016 ◽  
Vol 9 (1) ◽  
pp. 91
Author(s):  
Yulie Megawati
Keyword(s):  
Supply Chain ◽  
Bullwhip Effect ◽  
Raw Material ◽  
Research Model ◽  
Model Data ◽  
Material Supply ◽  
The Right ◽  
High Level ◽  
The Impact ◽  
A Company

Bullwhip effect is the main evidence of inefficiency in the supply chain of a company. Bullwhip effect describes the tendency of increasing the number of purchases of raw material supply chain<br />as a result of the inability to predict the increase in the number of requests. This study is the high level of inventory, whether as a result of the bullwhip effect or was due to an increase in demand. The purpose of this study was to determine the contribution of each factor causes of the bullwhip effect, identify the factors that provide the greatest impact on supply chain performance and find solutions to reduce the impact caused. The approach of this research is done by collecting data for inventory movement in the period 2003-2007, analyzing the interaction between members in the supply chain. Theory - the theory was used to create a research model. Data analysis is done by analyzing graphs and statistical analysis for the right to draw conclusions from this research. Results from this study that the coordination of “end to end” supply chain to reduce the impact of<br />bullwhip effect in supply chain

scholarly journals Pengurangan Efek Bullwhip Pada Vendor Tunggal dan Eceran Multi Di PT. XYZ

2019 ◽  
Vol 2 (4) ◽  
Author(s):  
Meilita Tryana Sembiring ◽  
Feby Sanna Sibarani
Keyword(s):  
Supply Chain ◽  
Moving Average ◽  
Linear Method ◽  
Bullwhip Effect ◽  
Exponential Smoothing ◽  
Glass Bottle ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
The Impact ◽  
A Company

PT. XYZ merupakan perusahaan yang bergerak dalam produksi produk – produk olahan teh. Perusahaan telah memproduksi berbagai varian the yakni bentuk mau pun jenis teh. Objek penelitian ini ialah the dalam kemasan botol kaca dengan ukuran 220 ml. Ukuran the tersebut dipilih berdasarkan akumulasi dari penjualan the tertinggi. Terdapat perbedaan pada prediksi jumlah produksi yang akan dilakukan. Prediksi jumlah produksi dapat dilakukan dengan melakukan peramalan permintaan serta penggunaan metode yang tepat. Rantai pasok yang diteliti pada PT. XYZ terdiri atas Manufaktur (Vendor), Kantor Penjualan, dan Dister. Awalnya peramalan dilakukan pada masing – masing level rantai pasok dengan metode peramalan yang berbeda – beda. Maka, diperlukan penyeragaman metode peramalan pada masing – masing pelaku rantai pasok. Berdasarkan pengujian metode peramalan yang dilakukan yakni metode Linear, Exponential Smoothing, Moving Average, dan Winter’sMethod. Diperoleh bahwa error terkecil terdapat pada metode peramalan Winter’s Method dengan parameter Level sebesar 0,5, Trend sebesar 0,2 dan Seasonal sebesar 0,6. Parameter error yang digunakan ialah MAPE, MAD, dan MSD. Hasil penelitian menunjukkan bahwa penggunaan metode peramalan yang tepat akan mengurangi dampak dari bullwhip effect yang terjadi pada PT. XYZ.   PT. XYZ is a company engaged in the production of processed tea products. The company has produced various variants of tea, that is the shape and type of tea. The object of this research is the 220 ml glass bottle packaging. The size of the tea is chosen based on the accumulation of the highest tea sales. There is a difference in the prediction of the amount of production to be carried out. Prediction of the amount of production can be done by forecasting demand and using appropriate methods. The supply chain studied at PT. XYZ consists of Manufacturing (Vendors), Sales Offices, and Disters. Initially forecasting is done at each level of the supply chain with different forecasting methods. Therefore, uniform forecasting methods are needed for each supply chain actor. Based on testing the forecasting method that is done namely the Linear method, Exponential Smoothing, Moving Average, and Winter’s Method. Obtained that the smallest error is found in the Winter’s Method forecasting method with a Level parameter of 0.5, a Trend of 0.2 and a Seasonal of 0.6. The error parameters used are MAPE, MAD, and MSD. The results showed that the use of appropriate forecasting methods would reduce the impact of the bullwhip effect that occurred at PT. XYZ

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