BULLWHIP EFFECT IN THE SERVICE SUPPLY CHAIN RESEARCH BASED ON MORTGAGE SERVICE MODEL

1. Introduction
1.1. Background
Organizations that seek to be leaders in their respective industries have relied on well-organized supply chains to remain competitive. The service industry has experienced a tremendous growth over the last three decades because of the economic globalization process (Zhang and Chen, 2015, p.485). In developed countries, the importance of the services business sector is immense as the industry has become one of the man drivers for the growth of the gross domestic product (GDP). The intangibility and lack of standardization of services has become an impediment towards the effective and efficient supply chain management in the service sector (Shahin, 2010, p.60). In specific, it is hard to apply various logistic activities to the service supply chains as this would require not only a high level of integration but also close interrelationships between the suppliers and the customers. One of the concepts which has been experienced in the service supply chain is the “bullwhip effect.” In specific, consumer demand; which is slow moving, has created large swings of production for the suppliers. As such, according to Zhang and Chen (2015, p.485), there has been a variance and demand amplification. In the banking industry, various simulations models have been adopted to predict the demand for mortgage services. However, the “bullwhip effect” resulting from the irrational behaviors of the parties involved has not only been costly but also a source of loss for some organizations.
The existence of the “bullwhip effect” has various adverse consequences in the supply chain of the both products and service providers. One of those is that they have resulted in the organizations incurring the costs of holding too much stock which has resulted in increased inventory holding costs (Sampson, 2012, p.60). Additionally, the amplification of demand has led to unfulfilled orders and ultimately poor customer service. Moreover, the cost of the “bullwhip effect” on organizations’ supply chains is that it has resulted in massive wastes especially when the supply does not realistically match the demand (Hohmann and Zelewski, 2013, p.167). In some other cases, insufficient inventory has led to not only a poor customer experience but also lost business for organizations. For businesses that do not have a reserve inventory; which acts as a buffer against the demand fluctuations, they have found the “bullwhip effect” to be averse to their profitability goals (Zotteri, 2013, p.489). Although the effects of bullwhip effect on the product supply chain is well established, it is not clear how the effect can be reduced in the service industry (Bhattacharya and Bandyopadhyay, 2011, p.1245). As such, it is vital to investigate how the bullwhip effect occurs in the service supply chain and provide recommendations for its reduction and ultimately the provision of quality services.
1.2. Aims and Objectives
This research aims at achieving the following aims and objectives: –
i. To investigate whether bullwhip effect exists in the service supply chain.
ii. To explore the causes of bullwhip effect on service supply chain.
iii. To prove the existence of the bullwhip effect ion service supply chain by simulation modelling.
1.3. Purpose of The Study
The purpose of this study is to conduct an analysis of the “bullwhip effect” in the service supply chain and build a simulation model pegged on the mortgage service game proposed by Anderson (1999). The study will start by the exploration of ways that the bullwhip effect affects the service supply chain and the various factors and activities which are responsible for the effect in the service industry. In the next step, the author will prove that through the simulation modeling game, the “bullwhip effect” actually exists in the service industry. Moreover, recommendations will be made in the study as to the various strategies which can be deployed by organizations in the service industry to reduce the bullwhip effect and ensure the reduction of wastes and the provision of high-quality services to the customers.
1.4. Significance of The Study
This study will be significant not only for academic purposes but also to organizations in the service industry and the consumers. Notably, although it is well established that the causes of the bullwhip effect in the product supply chain include irrational behaviors such as amplified demands as well as operational decisions, it is unclear as to the causes of the effects in the service industry. As a result, organizations in the service sector have found it hard to manage their inventories and reduce wastes. This study will be beneficial to such organizations as it will demonstrate how the “bullwhip effect” happens in the service industry as well as its root causes. Business organizations in the service sector will find this study vital in informing them on ways that they can reduce the “bullwhip effect.” Consumers will also benefit from this study. In specific, through the recommendations on ways to reduce wastes associated with the “bullwhip effect,” customers will be provided with services at the right time, in the right amount, and services of the highest quality.
2. Literature Review
A review of literature was conducted with various scholarly articles being examined. The information gathered from the various studies was used in the establishment of the research gap.
2.1. Bullwhip Effect
2.1.1. Definition
The “bullwhip effect” is one of the critical factors which has been found to amplify the demand variability as well as the passing of customer order upstream through the successive tiers of the supply chain. Wang and Disney (2016, p.691) defines the “bullwhip effect” as a phenomenon whereby the effects of slow-moving demand create various large swings in the production process for the suppliers in the other end of the supply chain. However, Buchmeister, Friscic, and Palcic (2014, p.64) argue that the “bullwhip effect” is a representation of demand distortion in the supply chain as orders to the suppliers tend to have a large degree of variation compared to the sales to the buyers which leads to the propagation of the upstream end in an amplified manner. Similarly, Moll and Bekker (2013, p.1) assert that the bullwhip effect is observed when; in the supply chain management, the demand from the customers leads to increasingly large variations in demand as one moves up the supply chain. Some of the three characteristic which are evidenced during a bullwhip effect include amplification, oscillation, and the phase-lag. According to Lee et al. (2014, p.35), the occurrence of oscillations and amplifications are due to boom and bust over a specific period and hence leads to excessive inventories and thus a difference in the size of orders as they move upstream in the supply chain. However, the phase-lag part of the “bullwhip effect” comes into play when the levels of inventory peak followed by potential backlogs which are delayed to some extent at various tiers in the supply chain. The “bullwhip effect” can be quantified by determining the variance of the orders placed by the retailer to the producer compared to the variations in demand faced by the retailer. As a result: –
qt = yt − yt−1 + Dt−1.
2.1.2. Causes
Traditionally, the “bullwhip effect” has been attributed to the irrational behavior of individuals. However, according to Moll and Bekker (2013, p.15), four high level operational causes can be attributed to the bullwhip effect. These include rational and shortage gaming, demand signal processing, order batching, and price fluctuation. However, the behavioral and irrational decision-making of individuals also have a significant role to play in the cause of the “bullwhip effect”. In specific, the decision logic of people responsible for demand leads to the creation of a tendency to over-spend which either increases of decreases demand in terms of the placed orders in the immediate upstream (Shahin, 2010, p.60). On the operational causes, the rational and shortage gaming occurs when after the demand for a specific service or product exceeds supply, and then manufacturers ration their products to the customers leading to the retailers anticipating potential shortages and exaggerating their real needs when making an order (Moll and Bekker, 2013, p.27). Price fluctuations as an operational cause of bullwhip effect entails “forward buying” from the companies in advance of their requirements which lead to price fluctuations because of some special promotions such as coupons, price discounts, and quantity discounts and ultimately distorting the immediate needs (Moll and Bekker, 2013, p.25). Order batching; on the other hand, involves companies in the supply chain batching or accumulating demands before the issuance of an order as opposed to ordering frequently. According to Udenio, Fransoo, and Peels (2015, p.34), the “bullwhip effect” can also arise due to demand signal processing especially in the beer game setting where product forecasting is done based on order history from the downstream of a company’s immediate neighbor.
2.1.3. Remedies
In the quest to counter the various causes of the “bullwhip effect,” Moll and Bekker (2013, p.31) argues that companies should use the remedies of collaboration, replenishment smoothing, and operational efficiency. In specific, collaboration between the supply chain members can transform the suboptimal solutions to individual links into comprehensive solutions via the sharing of both customer and operational information. According to, Udenio, Fransoo, and Peels (2015, p.35), collaboration can lead to the resolution of the amplification of order in the upstream direction through the reduction of inventory holding costs and improvement of customer service levels. The “bullwhip effect” can also be remedied using replenishment smoothening through a period review policy. For instance, Moll and Bekker (2013, p.33) opine that at each review period, the inventory should be reviewed and quantity ordered to bring the levels of the valuable inventory to an optimum. The adoption of the remedy of smoothing replenishment is effective in demand signal processing because of the manner in which it limits overreactions and underreactions to any changes in demand (Udenio, Fransoo, and Peels, 2015, p.37). Elsewhere, operational efficiency along the supply chain using the “just-in-time management” (JIT) can lead to the elimination of the storage of unused inventory which is a waste of resources. Although the operational efficiency using JIT can lead to a small disruption in the supply chain, in the end, it will lead to the supply of the right products and services at the right time, at the right places, and in the exact amount desired.
2.2. Service Supply Chain
2.2.1. Definition
Although the bullwhip effect has mostly been examined in the context of the product supply chain, in the recent past, scholars have started to examine the concept in the service supply chain. According to Elgazzar and Elzarka (2017, p.119), the service supply chain (SSC) involves a network of various actors in the supply chain such as the suppliers, customers, service providers, and other supporting units who perform functions of transaction of resources to produce services and transform resources into aiding the delivery of core services to the customers. As such, SSC is focused on the management of information, processes, service performance risks, and capacities. However, Akkermans and Voss (2013, p.768) hold that the service supply chain as concerned with the management of not only information and processes, but also capacity and funds from the earliest supplier to the ultimate customer. In the recent past, scholars in the realm of service operations management; as opposed to those from supply chain management, have begun to address the service supply chain. In specific, according to Sampson (2012, p.182), the service supply chain is not as linear as that from the traditional product supply chain. Additionally, in the service supply chain, there is more customer contact in the service processes and a co-creation of value between the manufacturers, suppliers, and the ultimate consumers (Udenio, Fransoo, and Peels, 2015, p.38). The interactions lead to two-way flows between the suppliers and the customers. The service supply chain is a producer-consumer interaction process characterized by a network of interdependent service processes which span across diverse process entities (Akkermans, and Voss, 2013, p.765). Some of the participants in the processes include firms/companies, customers, agents of customers, and other key players in the supply chain for different services.
2.2.2. Key Service Supply Chain Processes
Elgazzar and Elzarka (2017, p.119) argue that the service supply chain consists of 8 key processes of customer relationship management, information flow management, demand management, capacity and skills management, supplier relationship management, cash flow management, and service delivery management. Customer relationship management (CRM) is based on the assumption that without a satisfied customer, then a supply chain strategy cannot be deemed to be effective. Although the measurement of the CRM performance is a problematic aspect based on the intertwined nature of the CRM with other functions, the focus should be on ensuring the customer knowledge, customer interaction, customer value, and finally, customer satisfaction (Elgazzar and Elzarka, 2017, p.120). However, information flow management is the process for the linkage of all members of the SSC to information through not only the collection but also the transmission and processing of data with the goal of creating information needed to support the other processes in the management. Elsewhere, supplier relationship management is a process of service supply chain which ensures that customer and suppliers develop and even maintain close as well as long-term working relationships. However, according to Cho et al. (2012, p.801), demand management is an aspect of the service supply chain that entails the balancing of the requirements of the customers with the capabilities of the supply chain and hence a reduction in variability and uncertainty and ultimately, the increment of flexibility. Cash flow management in the service supply chain ensures that there is an efficient flow of funds across the supply chain. Finally, capacity and skills management involve ensuring that intangible services that a firm provides differentiate themselves from competition (Elgazzar and Elzarka, 2017, p.122).
2.2.3. Types and Examples of SSCs
The service supply chain is a new supply chain which has even been extended further to include Product Service Supply Chains (PSSCs) and Service Only Supply Chains (SOSCs). According to Liu et al. (2017, p.2), the service supply chain system is composed of the customer, the retail service provider, and the service producer for infrastructure. The real-world examples of the service supply chains include those used in the finance and banking industry, telecommunication, internet service provision, tourism, and mobile apps. Whereas the PSSCs manage both physical products as well as consideration of various services, the SOSC are purely concerned with the provision of pure services. One of the aspects which have led to the popularity of the service supply chain include the global service outsourcing. However, according to Liu et al. (2017, p.3), the specific characteristics of the services provided as well as intangibility, labor intensity, and inseparability has led to various problems arising. Such restraints care caused by the environment, the society, and economics which trickle down to the development of the service supply chain. For instance, some of the conflicts which have arisen on environmental overconsumption and the increment in the social problems have been restricting the growth of the service supply chain compared to the traditional product supply chain (Cho et al., 2012, p.801). As demonstrated, the service supply chain has been adopted in the banking institutions among other industries in the quest to ensure the provision of competitive and high-quality services to the consumers.
2.3. Mortgage Service Model
2.3.1. Origins
Anderson and Morrice (2000) conducted a research on the supply chain and established the bullwhip effect of the service supply chain. Additionally, Anderson and Morrice (2000), proposed the mortgage service model. Mortgage service games are simulations of real mortgage services. This model simplifies the actual activities and makes the behavior easy to understand. Each mortgage application goes through four consecutive phases: initial processing, credit checks, investigations, and confirmation checks. These four phases are serviced by four different service providers. In the first phase, each customer submits a mortgage application. The applicant’s loan officer handles the application form at the initial stage. Through the first phase of the loan officer will process the application to enter the second stage, the credit check. Employees and customers begin the second phase of contact while confirming and reviewing credit history information. After the second phase is passed, the reputation check phase passes the order request to the investigation phase (i.e., investigating the customer’s property to check its value and any violations in the partition code or adjacent property) and confirming that the property owner is undisputed and no lien. These four stages can determine the level of customer engagement based on the nature of the service, but basically, all four stages require customer involvement. At each stage, inventory is not fundamental to customer demand and therefore cannot be a buffer for changes in demand for manufactured goods.
2.3.2. Bullwhip Effect on Mortgage Services
In mortgage services, each stage needs to control the backlog of the stage by managing the number of workers it employs, thereby improving its service level. Each stage of the service provider sets the target processing capacity according to specific rules and adjusts the number of workers through recruitment and dismissal so that the actual processing power changes toward the target processing ability. However, since it takes some time for the company to recruit employees (including promotion, interviews, recruitment, training.) and dismissal (including notification, dismissal, and so on.), there is a time lag in the actual processing capacity changes. Since the service does not have the same inventory as the finished product, the order accumulation and service capability parameters can be choosing between to measure whether there is a “bullwhip effect” in the supply chain of this service. At the same time, another goal of the service supply chain is to minimize the total cost of staff costs and service delays throughout the supply chain. This goal can provide more optimized target processing capabilities and can be further researched in the future.
2.3.3. The Mortgage Service Model
According to the research on the definition and structural model of the service supply chain and the abstract generalization of the model in the product supply chain, the model of service supply chain can be summarized as follows: considering a single multi-part supply chain, there is only one participant in each stage. At any given stage one, the behaviour of the participant can be described as follows: before the end of each time cycle t, the demand Di,t of the participant has been realized, and the participant satisfies the demand with its service capability Ci,t as the upper limit. The unsatisfied demand becomes backlog Bi,t, and is deferred. In the above model, the order of one stage is directly transformed into the demand of the previous stage, so Di,t+1 = Ri,t. In each stage, the target capability Ci, *t, guiding Ci, t changes to Ci, *t every k cycles.
The assumptions of the model can be summarized as follows:
A. The supply chain is a single-item multi-stage supply chain, with only one participant in each stage and different subjects in each stage;
B. The needs of the end customers are not independent, but interrelated;
C. The capacity to target services at all levels is projected based on the backlog at that stage;
D. It takes time for the actual service capability to change to the target service capability; E. Unmet demand in the supply chain will be postponed indefinitely.
Based on the understanding of mortgage game model and the concept proposed by Anderson and Morrice (2000), the following formula can be concluded:
(1)B_(i,t+1)=B_(i,t)+R_(i-1,t)-R_(i,t)
(2)R_(i,t)=min⁡(C_(i,t),B_(i,t)+R_(i-1,t))
(3)C_(i,t+1)=C_(i,t)+1/τ(C_(i*t)-C_(i,t))
(4)C_(i,t)=αR_(0,t)+(1-α)B_(i,t)/φ
(5)C_(i,t)=C_(i,*t-1)
Bi,t — the backlog on day t of stage I;
Ri,t — the actual processing capacity of stage I on day t;
Ci,t — actual processing capacity of stage I, day t;
Ci,*t — target processing capacity of stage I and day t;
τ–ability to adjust time;
φ- – average service delay time;
T — target capability adjustment cycle;
α– a factor that determines to what extent the new application rate is used to determine the target processing power, 0<α<1. Formula (1) indicates that the input of each stage comes from the completion amount of the previous stage, and at the same time, the backlog accumulated the day before this stage should be given priority. Its output is its completion. Therefore, the backlog at t+1 day of stage I is equal to the backlog at the previous day of the stage plus the amount actually processed the day before the previous stage (that is, the amount faced by t+1 day, which needs to be completed), minus the amount actually processed the day before the stage. Formula (2) indicates that each service provider can only meet the demand of the day based on its actual processing capacity. If the demand for the day is small, there will be excess capacity. Thus, the number of backlogs that can be processed on day t of phase I depends on the actual processing capacity on the day of the phase and the smaller of the amounts available for processing on that day. Formula (3) illustrates that every week, according to the backlog of an investigation, to decide to hire or fire employees, set the targetability of the system. However, in practice, the average processing power will lag the target investigation power by some time. Therefore, the target processing capability rule is formulated as follows: the change rate of the actual processing capability in stage I is equal to the change rate of the actual processing capability in the day I towards the target processing capability (evenly changing in the capacity adjustment time). Formula (4) shows that for some reason, each service provider cannot adjust the target capability every day, and following equation will determine the target capability: the target processing capability is adjusted every T day. When t is divisible by t, check the backlog of the day and take the following action: adjust the target to be able to handle the backlog within the allowable delay period; And in the rest of the time, the target processing power is not adjusted. Formula (5) represents the other cases in formula (4) where t is not divisible. Overall, the existence of the bullwhip effect in the service supply chain has been proved. In the original paper of Anderson and Morrice, D. (ibid), a series of parameters set by it have been simulated and 2.4. Research Gap The review of literature has demonstrated that the bullwhip effect has the effect of amplifying demand and can lead to poor inventory management and wastes. Additionally, the studies examined in the previous parts have demonstrated that the causes of bullwhip effect include operational aspects and irrational behaviors. Some of the remedies which have been adopted in the product supply chain to reduce the amplification of demand include the collaboration between the suppliers and the consumers. However, a majority of the research has been focused on the causes and remedies of the bullwhip effect on the product industry. As a result, a gap exists in the service industry where the causes and occurrence of bullwhip effect has not been extensively explored. This research filled the gap by exploring the incidence of bullwhip effect in the service industry with a specific focus on the provision of mortgage services.  List of References Akkermans, H. and Voss, C., 2013. The service bullwhip effect. International Journal of Operations & Production Management, 33(6), pp.765-788. Anderson Jr, E.G. and Morrice, D.J., 2000. 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