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Quality Management Costs in Logistics

Written By

Marieta Stefanova

Submitted: February 5th, 2022Reviewed: February 17th, 2022Published: March 21st, 2022

DOI: 10.5772/intechopen.103786

IntechOpen
Quality ControlEdited by Leo Kounis

From the Edited Volume

Quality Control [Working Title]

Dr. Leo Dimitrios Kounis

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Abstract

The minimization and elimination of deviations from quality that could cause a failure in the logistics system should be identified at an early stage in order to reduce the costs for recovering the system to its normal operation. The objective of this study is to analyze the contribution of prevention costs related to quality management to the total costs by focusing on the need to undertake priority preventive actions to ensure logistics services that meet the customer’s quality requirements. The methodology of the study includes the integrated application of conventional scientific methods for comparative analysis and Taguchi’s design for accounting regarding the primary costs for quality management with the predominant use of qualitative analysis. By applying these methods, the following groups of costs have been analyzed: prevention and avoidance of nonconforming quality; quality evaluation and control; and covering the costs for nonconforming quality of the logistics services. The contribution of the three groups of costs has been studied. Based on the analyses, this paper comes to the conclusion that the management of those costs by groups of factors for incurring them has the potential to contribute to the improvement of the quality of logistics.

Keywords

  • costs
  • logistics
  • nonconformities
  • quality

1. Introduction

The costs for maintaining the quality of the logistics services at the level of the customer’s expectation are associated with the achievement of high efficiency of the processes [1, 2], better quality of the incoming material flows [3], and performance of the equipment and inventories without failure [4, 5]. The achievement of the “Just-in-time”, JIT principle for all products delivered requires targeted managerial efforts for maintaining the continuity of the logistics processes [6, 7, 8, 9, 10], ensuring efficient human resource management [11, 12, 13], and optimal utilization of the warehousing potential [14, 15, 16, 17]. The identification, minimization, and elimination of deviations from set quality levels and the causes for failure of the system should be identified at the earliest possible stage in order to reduce the expenses for recovering the system to its normal operation. The level of quality has a positive impact on the implementation of the selected logistics strategy [18, 19, 20, 21], whereas the low level of quality is an indicator of the poor efficiency of the supply chain [22]. The main objective of the quality management processes is to ensure the effective performance of the logistics services. It has been concluded that when the quality management processes are operated as a system, they have a much more positive impact on the performance of the individual components of the system rather than the contrary. It has also been postulated that certain key areas of the logistics operations have a decisive impact on the efficiency of the logistics system, such as, for example, transportation and storage operations.

To analyze the costs for maintaining required quality levels, the components of those costs (Figure 1), need to be clarified:

Figure 1.

Quality assurance-specific costs.

Improvement of the logistics system efficiency is a key factor for ensuring products that meet demand and the flawless management of the organization [23, 24, 25, 26, 27]. Logistics operators that organize the supply chain by setting targets and results based on a limited budget manage to achieve growth in their revenues and assets, and, at the same time, reduce their operational costs [28, 29]. Due to the constantly emerging risks in the operations in the real economy where the logistics operations take place, it is often necessary to respond to the specific situation for overcoming the bottlenecks without considering the strategic guidelines for business development [30]. This is why the systems that are very flexible and capable of changing together with the market and the changes in the external environment are the most rapidly developing ones. In essence, the purpose of logistics operations can be defined as the effective and timely movement of goods to the places where the customer needs them at a reasonable price [31]. However, there are often restrictive conditions for the fulfillment of those purposes, and the appropriate equipment for loading and moving the transport vehicles is not always available when they are needed. In addition, the capacity of each logistics warehouse is strictly confined and fixed. There is competition in the sector of logistics, too. Therefore, the business needs to focus on its main competence and outsource to external contractors those services, the operation of which causes unjustified losses of resources, in order to achieve effective management of the costs for quality improvement. Actually, the main purpose of cost optimization is to practically [32, 33] satisfy the customer’s requirements by reducing the time for making the delivery. The main impediment to achieving this purpose is caused by the limited possibility to transfer and receive information about the actual demand in real-time.

The main problem about minimizing the costs for achieving the logistics purposes is related to the understanding about the management of the system itself as one that distributes the cargo (“push”) and one that requires distribution of the cargo where necessary and based on a customer’s order (“pull”) [34]. The first type of system is more appropriate in the case where no exact information about the need of goods is available. However, in this case, if demand is significantly higher than supply, distribution of scarce goods and priority servicing of selected customers is needed. The use of mathematical methods for planning routes, occupation of the warehousing facilities, and temporary hiring of workers can help to reduce costs. When accounting for the total operational overheads, the expenses for handling, storage, and transportation of the goods should be accounted for based on the main cost items. This can be done by identifying all the resources (including human resources), the packaging and repackaging operations performed, the processes, and the methods used for evaluation and control in order to ensure the overall performance of the process. In other words, the total costs for logistics are the sum of all costs incurred for the management and implementation of all processes and operations related to the logistics operations. Generally, the total costs can be divided into the following three groups:

  • costs associated with the operations,

  • costs related to with the management of the logistics system and,

  • costs associated with the application of possible logistics risks.

There is an interesting approach in the control of quality management costs, which was developed by Taguchi [35]. This method focuses on the causes for deviations from the quality and on establishing clearer criteria for defining the critical boundary that distinguishes between conforming and nonconforming services [36]. Taguchi’s contribution to quality management is related to the following principle that any variations and deviations in the function of quality are the results of random and nonrandom factors and losses are observed when the variation results in conditions where the product or service is on the exact boundary of the target conformity value [37]. This is the quadratic loss function since it is assumed that when the product or service is at its target value, the loss will be zero. According to Diallo, Khan, and Vail, the relationship between quality improvement by decreasing the variations and the costs can be analyzed by using Taguchi’s function. Many researchers have also applied Taguchi’s method in the field of logistics services [38, 39, 40, 41].

The contribution to the reduction of the total operational costs for prevention of nonconforming logistics services as compared to the increase in the costs for their management and their relationship to the costs for monitoring and control in logistics services has not been studied. A number of logistics organizations have not focused on this analysis and, as a result, perform restructuring or investments which do not yield the expected positive outcome. It is the author’s view that logistics service providers should draw their attention to investment in quality management related to the prevention of nonconformities. At the same time, logistics service providers should exercise more effort on the potential opportunities for the development of the actual logistics services and the service processes. This study offers a practical solution for management and analysis for measuring these qualitative changes.

The objective of the study is to analyze the contribution to total costs of the expenses for prevention related to quality management in logistics by focusing on the need to undertake priority preventive actions to ensure the provision of logistics services that meet the customer’s quality requirements. By using the applied methods, this study analyses the contribution to quality improvement of the costs attributed to the prevention and avoidance of nonconforming quality, for quality evaluation and control, and for covering the expenditures for nonconforming quality of the logistics services. The relationship between these groups of costs in quality management has been identified by means of structural modeling, which helps to establish the contribution of the costs to the achievement of sustainable quality of the logistics services.

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2. Research methods

The primary method for data analysis that has been used is Taguchi’s method, which defines quality from the perspective of cost minimization and the subsequent loss to society. Based on his definition about quality management, continuous, consistent, and targeted actions are required to achieve minimum variability of the logistics services offered. According to Taguchi, the efforts should focus on the following two aspects: defining the combination of factors that have the lowest impact on any deviation from quality, and adjusting those factors that are the cause for the deviation from the set target of the logistics services. Based on the results obtained from Taguchi’s loss function, the contribution of the different factors that could have an effect on the deviation from the customer’s expectations for high-quality logistics services can be quantified. This can be used for initiating improvements that could have a positive impact in terms of satisfying those expectations.

2.1 Stages of Taguchi’s method application for this study

Taguchi’s method was applied in two stages:

  1. A model generation stage, which allows the selection of those controllable levels of the factors that have the greatest contribution to the achievement of the logistics services quality level expected by the customers (studied dependence) and the respective significance levels.

  2. Performing the actual analysis (Taguchi’s design) to identify the parameters of the analyzed factors that minimize the variation in the deviations. The calculation of the tolerances that contribute to the reduction of deviations from the expected quality level of the logistics services is performed using the software Microsoft Excel XLSTAT 2021® [42].

2.2 Method for collection of data for analysis

The proposed data to be evaluated have been taken from the annual financial statements of an operating logistics company in the food sector and have been subsequently divided into three main groups: for prevention and avoidance of nonconforming quality; for quality evaluation and control; for covering the costs for nonconforming quality of the logistics services. The information collected about the last two-year period has been summarized in tables in order to visually illustrate the potential impact and the actual improvement of the economic result. After the final data from the studied two-year period were collected (before and after the introduction of the changes in the cost structure), those data were summarized and presented in Table 1.

Short nameNbr. Of categoriesPeriod of time before implementation of the changes in the cost structurePeriod of time after implementation of the changes in the cost structure
Prevention costs2450 (in thousand euro) (450 k€)500 (in thousand euro)
Evaluation and control costs2200 (in thousand euro)250 (in thousand euro)
Cost of nonconformities2100 (in thousand euro)50 (in thousand euro)

Table 1.

Variable information.

By observing Table 1, it can be seen that the costs for improvements after the introduction of the changes are two times greater than the costs for prevention and control, whereas the costs for covering losses as a result of nonconforming logistics services have decreased by half as compared to the period before the implementation of the changes. The change in the cost structure based on the pre-defined three groups has allowed for the practical application of Taguchi’s principle that the nonconforming logistics service cannot be improved through the process of control or covering the losses from the nonconformity after the service has been provided. The application does not have the potential to create a conforming service, but just to identify the conforming and nonconforming services. Based on the data obtained, the experimental design was built and a questionnaire was generated.

2.3 Evaluation collection method and discussion method

The data collection for the study was performed via telephone and online meetings in focus groups by taking into account all the restrictions imposed in relation to the pandemic. All participants in the study are currently managers in organizations where the main scope of business is the provision of logistics services in the field of trade and delivery of food products to wholesalers.

The participants in the study were selected based on their management experience and, in particular, their experience in the field of logistics services quality management costs. The required criterion for participation was at least 10 years of experience. Initial informative telephone conversations about the study and its methods, including the observation of all requirements of the relevant legislation related to personal data protection, were performed with potential participants in the study. Only 5 out of a total number of 20 potential participants did not agree to participate. The participants who confirmed participation received a questionnaire. The main purpose of this questionnaire was to study the potential attitudes and evaluations of the participants regarding the need of change in the structure of quality management costs. The study was performed in two consecutive panels in online meetings with a discussion in focus groups held in-between. The evaluation of the participants’ opinion was performed based on a 100-point scale ranging from 1 to 100. The questionnaire of the study is presented in Table 2.

By using the 100-point scale (where 1 is the lowest value and 100 is the response with the highest value), please, evaluate which, in your opinion, would be the most suitable cost structure for logistics services quality management represented in 8 different categories.
ObservationsPrevention costsEvaluation and control costsCost of nonconformitiesRespondents’ answers in the two panels
Obs1450200100
Obs245020050
Obs3450250100
Obs445025050
Obs5500200100
Obs650020050
Obs7500250100
Obs850025050

Table 2.

Questionnaire of the study.

After the study, the participants’ responses were averaged and summarized for further analyses using Taguchi’s method.

The method used allows on one hand a comparison to be made, while on the other to quantify the difference between the target function (optimum ratio between the quality management costs) and its actual manifestation. The objective was to find a solution for minimizing deviations from the target function for logistics services in the food sector.

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3. Results

In the course of the study, Taguchi’s principles and methods for quality management were used to identify the optimum ratio between the quality management costs. The first principle that was applied is related to the statement that quality should be designed in the logistics service before offering that service on the market and, respectively, a strategy should be undertaken to increase the prevention costs (designing conforming quality) at the expense of the other costs.

Based on the experimental design, further calculations were made to find the contribution of the increased or decreased share of certain overheads to the achievement of a conforming service impacted to the lowest possible extent by the other factors. The data obtained from the two focus group sessions held were averaged and entered in Table 3.

ObservationsPrevention costsEvaluation and control costsCost of nonconformitiesResponse 1Response 2
Obs145020010075.00076.000
Obs24502005080.00082.000
Obs345025010078.00080.000
Obs44502505084.00085.000
Obs550020010085.00084.000
Obs65002005098.00097.000
Obs750025010088.00096.000
Obs85002505099.00099.000

Table 3.

Experimental design (response 1 and 2).

Based on the results from Table 3, the experts have given a significantly lower number of points to the ratio of costs in the cases where there is an increase in the costs for operations associated with the rectification of problems, rather than preventive actions. It was concluded that this was the right approach; however, despite this, it is the author’s view that logistics organizations practically continue using their entire potential not for the development of the types of services offered on the market, but for the rectification of problems that have occurred in the course of providing those services. The reasons for that could be related to the fact that often when designing the actual services, the processes are dragged over time, which in turn, may lead to a delay. Therefore, this process often needs to be compensated by reducing the time limits under signed contracts and by adjusting all the details and parameters related to the negotiation of the logistics service. As a result, certain logistics operations are skipped, which are subsequently performed without actually specifying their parameters. This, on the other hand, creates more favorable conditions for customer claims and undertaking actions to increase the control in order to avoid such nonconformity in the future. The higher level of control leads to an increase in costs and does not guarantee that the services will be conforming if the conditions that lead to the presence of claims remain unchanged.

The analysis of controllable factors that create conditions for deviations in the logistics services has been studied with respect to the contribution of costs for the different operations to the total operational costs. These costs include both the costs for planning the logistics services and the costs related to the control of those services and compensations to customers related to claims and returns, replacement, or repeated implementation of the logistics operations. It is the author’s view that claims could be minimized by designing logistics services that are needed by the customer rather than services that the organization is capable to provide. A number of studies have come to the conclusion that the prevention of claims is more efficient than covering the costs once a claim has been filed and, respectively, could result in greater customer satisfaction [43, 44, 45, 46, 47].

Based on the data collected, Taguchi’s model has been created, where the ratio LS means (Signal-to-Noise ratios) has been calculated. It defines the ratio between the mean value of the share of each cost from the total costs and the standard deviation. The variability of the analyzed indicators considered significant by the experts for the provision of a conforming service, defined by their standard deviation from the average value, is presented in Figure 2.

Figure 2.

Signal-to-noise ratios.

The results presented in Figure 2 show that prevention costs have been evaluated as the most significant factor with positive impact, followed by the positive impact of the costs for control. The influence of the increase in the costs for nonconforming logistics services has been assessed as negative. The multiple criteria used by the logistics operators for calculation of the services are related to the satisfaction with their expected quality and are hard to quantify. The studies performed so far show that investing in the design of services has a significantly more positive impact on the expected quality than investment in a higher level of control on the performance of those services (the prevention costs and the costs for control are equally increased by 50 units).

Taguchi’s approach thus requires seeking an appropriate solution for reducing the variations applied to the expected quality of the logistics operations and provides an opportunity to find results for lower deviation from the target function. The model these decisions can be based on, so that the variations in the logistics services are lower than expected, is presented in Table 4.

SourceValueStandard errortPr > |t|Lower bound (95%)Upper bound (95%)
Intercept39.1840.136287.649<0.000138.80539.562
Prevention costs-450−1.3170.136−9.6660.001−1.695−0.939
Prevention costs-5000.0000.000
Evaluation and control costs-200−0.4020.136−2.9520.042−0.780−0.024
Evaluation and control costs-2500.0000.000
Cost of nonconformities-500.7750.1365.6900.0050.3971.153
Cost of nonconformities-1000.0000.000

Table 4.

Model parameters (standard deviations).

The studied factors are statistically significant (at 0.05), which allows an optimum ratio to be set between the studied costs so that the deviation from the target function is as low as possible. Table 4 equally shows the statistical significance of each type of costs and their contribution to the achievement of an optimum combination of those costs. According to the feedback provided by the questionnaires, the most important factor in quality management is cost prevention because the absolute value of this factor is the highest. It can be stated that the prevention costs and the costs for control on the processes in the specific case that was studied were increased by the same number of units; however, the prevention costs demonstrated a much higher effect on the target function.

These results are confirmed by the main effects graphs in Figure 3.

Figure 3.

LS means (means prevention costs, control costs, cost of nonconformities).

Logistics organizations should invest in operations for the prevention of nonconformities in order to decrease the variability in the target function, even if the causes of the variations are not eliminated.

It has been practically demonstrated that the costs for eliminating the variation in the target function are very high. A more feasible and practical solution is to just change the structure of the costs or to control the factors that are more significant and have a greater impact on the target function. This can be achieved without increasing the total expenses or with a minimum increase resulting just from the redistribution of costs in the proper direction. Furthermore, the overheads that do not have a positive impact on the variations in the target function could be decreased and thus invested properly, in areas where their impact could be more favorable. This is what the application of Taguchi’s method on the structure of quality management costs in logistics allows the user to do – to calculate the contribution of the three cost groups in order to achieve an optimum effect in the target function.

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4. Conclusion

During the study, the change in the structure of quality management costs was analyzed based on the significant factors for achieving customer satisfaction defined by the experts. Data from the expenses incurred by the logistics company operating in the food sector were analyzed, which were divided into three groups of costs and described in the methodology. The road to improvement was found to be associated with the following:

  • cost reduction for nonconforming services after delivery,

  • keeping a relatively stable level of the expenditures for control and,

  • to distribute the highest share of expenses for prevention by investing in the improvement of the processes for designing conforming logistics services.

Based on the analyses, it was concluded that even a change in the cost structure could contribute to a higher level of customer satisfaction with the studied logistics services in the food sector. Reducing the variation around the target function could not only contribute to higher customer satisfaction; moreover, it could reduce the overheads for nonconformities after delivery which are caused in particular by such a variation. Indeed, higher customer satisfaction could be achieved, if there is less variation with respect to the service wanted by the customer and delivered on time.

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Acknowledgments

First, I would like to thank my children, without whose support I would not have been able to realize this idea.

I also thank all the logistics companies and logistics managers who participated in the survey and shared their experiences.

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Conflict of interest

The author declares no conflict of interest.

References

  1. 1.Pauliková A, Lestyánszka Škůrková K, Kopilčáková L, Zhelyazkova-Stoyanova A, Kirechev D. Innovative approaches to model visualization for integrated management systems. Sustainability. 2021;13:8812. DOI: 10.3390/su13168812
  2. 2.Dimitrakieva S, Kostadinov O, Atanasova K. Multilevel demand for sea transportation; correlation between Baltic dry index (BDI) and coaster shipping prices for sea routes between Baltic seaports and Mediterranean seaports. Pedagogika-Pedagogy. 2021;93:141-148. DOI: 10.53656/ped21-7s.12corr
  3. 3.De Marco A, Mangano G. Relationship between logistic service and maintenance costs of warehouses. Facilities. 2011;29:411-421. DOI: 10.1108/02632771111146323
  4. 4.Waeyenbergh G, Pintelon L. A framework for maintenance concept development. International Journal of Production Economics. 2002;77:299-313. DOI: 10.1016/S0925-5273(01)00156-6
  5. 5.Stank T, Keller B, Closs J. Performance benefits of supply chain logistical integration. Transportation Journal. 2001;41:32-46
  6. 6.Yang J, Xie H, Yu G, Liu M. Achieving a just–in–time supply chain: The role of supply chain intelligence. International Journal of Production Economics. 2021;231:107878. DOI: 10.1016/j.ijpe.2020.107878
  7. 7.Taguchi G, Rafanelli AJ. Taguchi on robust technology development: Bringing quality engineering upstream. Journal of Electronic Packaging. 1994;116:161. DOI: 10.1115/1.2905506
  8. 8.Hussein M, Zayed T. Critical factors for successful implementation of just-in-time concept in modular integrated construction: A systematic review and meta-analysis. Journal of Cleaner Production. 2021;284:124716. DOI: 10.1016/j.jclepro.2020.124716
  9. 9.Si T, Li HX, Lei Z, Liu H, Han S. A dynamic just-in-time component delivery framework for off-site construction. Advances in Civil Engineering. 2021;2021:e9953732. DOI: 10.1155/2021/9953732
  10. 10.Asikhia A, Osinowo O, Kassim S. Integrating just in time theory, resource based view theory, and rational choice theory in enhancing managements’ efficiency. South Asian Research Journal of Business and Management. 2021;3:14-22. DOI: 10.36346/sarjbm.2021.v03i01.002
  11. 11.Dimitrakieva S, Koritarov AK. The human element as a factor for sustainable development of the offshore oil industry. Scientific Works - Naval University N Y Vaptsarov. 2018;32:65-68
  12. 12.Kanev D, Toncheva S, Terziev V, Narleva K. Specific Aspects of Motivation of Seafarers. Rochester, NY: Social Science Research Network; 2017. DOI: 10.2139/ssrn.3144743. Available from:https://web.archive.org/web/20220111123810/https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3144743
  13. 13.Mednikarov B, Tsonev Y, Lazarov A, Lazarov A. Analysis of cybersecurity issues in the maritime industry. Information & Security: An International Journal. 2020;47:27-43. DOI: 20200924053840237
  14. 14.Trichai P et al. Developing warehouse employee performance by applying the principles of 7R in logistics. Turkish Journal of Computer and Mathematics Education (TURCOMAT). 2021;12:4121-4126
  15. 15.Nantee N, Sureeyatanapas P. The impact of logistics 4.0 on corporate sustainability: A performance assessment of automated warehouse operations. Benchmarking. 2021;28:2865-2895. DOI: 10.1108/BIJ-11-2020-0583
  16. 16.Maddikunta PKR, Pham Q-V, Prabadevi B, Deepa N, Dev K, Gadekallu TR, et al. Industry 5.0: A survey on enabling technologies and potential applications. Journal of Industrial Information Integration. 2021;26:100257. DOI: 10.1016/j.jii.2021.100257
  17. 17.Stoyanov V. Psihichen Stres v Organizatsiyata. 1st ed. Varna, Bulgaria: VSU Chernorizets Hrabar; 2011
  18. 18.Diallo A, Khan ZU, Vail CF. Cost of quality in the new manufacturing environment. Management Accounting (USA). 1995;77:20-26
  19. 19.Dimitrakiev D, Molodchik A. Digital platforms as factor transforming management models in businesses and industries. Journal of Physics: Conference Series. 2018;1015:042040. DOI: 10.1088/1742-6596/1015/4/042040
  20. 20.Zafirova T. Impact of changes in the environment on the strategic aspects of crisis management. Izvestia Journal of the Union of Scientists - Varna Economic Sciences Series. 2021;10:184-192
  21. 21.Zafirova T. Integration of the processes of strategic and crisis management in the conditions of crisis. Известия на Съюза на учените - Варна Серия Икономически науки. 2021;10:158-168
  22. 22.Stoykova T, Zlateva D, Pashova S. Commodity science in modern market conditions. Economic Science, Education and the Real Economy: Development and Interactions in the Digital Age. 2020:427-439
  23. 23.Christopher M. Logistics and supply chain management: Strategies for reducing cost and improving service. International Journal of Logistics Research and Applications. 1999;2:103-104. DOI: 10.1080/13675569908901575
  24. 24.Cooper JC. Logistics strategies for global businesses. International Journal of Physical Distribution & Logistics Management. 1993;23:12-23. DOI: 10.1108/09600039310041473
  25. 25.Mckinnon A. Integrated logistics strategies. In: Brewer AM, Button KJ, Hensher DA, editors. Handbook of Logistics and Supply-Chain Management. Vol. 2. Bingley: Emerald Group Publishing Limited; 2017. pp. 157-170
  26. 26.Rao KR, Stenger AJ, Wu H-J. Training future logistics managers: Logistics strategies within the corporate planning framework. Journal of Business Logistics. 1994;15(2):249
  27. 27.Kanev D. Commitment as a constraint to the pursuit of self-interest. Economics. 2017;1:3-20
  28. 28.McGinnis MA, Kohn JW. A factor analytic study of logistics strategy. Journal of Business Logistics. 1990;11(2):41
  29. 29.Waters D, Rinsler S. Global Logistics: New Directions in Supply Chain Management. London: Kogan Page Publishers; 2014
  30. 30.Zafirova T. Strategic decisions in the crisis stages of the organization. Izvestia Journal of the Union of Scientists - Varna Economic Sciences Series. 2020;9:100-108. DOI: 10.36997/IJUSV-ESS/2020.9.1.100
  31. 31.Tan K, Kannan VR, Handfield RB, Ghosh S. Supply chain management: An empirical study of its impact on performance. International Journal of Operations & Production Management. 1999;19:1034-1052. DOI: 10.1108/01443579910287064
  32. 32.Drury CM. Management and Cost Accounting. New York, NY: Springer; 2013
  33. 33.Banerjee B. Cost Accounting: Theory and Practice. Delhi: PHI Learning Pvt. Ltd.; 2021
  34. 34.NG T, Chung W. The roles of distributor in the supply chain–push-pull boundary. International Journal of Business and Management 2009;3:28-39. DOI: 10.5539/ijbm.v3n7p28.
  35. 35.Taguchi G. Quality engineering in Japan. Communications in Statistics - Theory and Methods. 1985;14:2785-2801. DOI: 10.1080/03610928508829076
  36. 36.Taguchi G. Robust technology development. Mechanical Engineering-CIME. 1993;115:60-63
  37. 37.Taguchi G, Chowdhury S, Wu Y, Taguchi S, Yano H. Taguchi’s Quality Engineering Handbook. Hoboken, N.J.: Livonia, Mich: John Wiley & Sons ; ASI Consulting Group; 2005
  38. 38.Shang JS, Li S, Tadikamalla P. Operational design of a supply chain system using the Taguchi method, response surface methodology, simulation, and optimization. International Journal of Production Research. 2004;42:3823-3849. DOI: 10.1080/00207540410001704050
  39. 39.Shukla SK, Tiwari MK, Wan H-D, Shankar R. Optimization of the supply chain network: Simulation, Taguchi, and Psychoclonal algorithm embedded approach. Computers & Industrial Engineering. 2010;58:29-39. DOI: 10.1016/j.cie.2009.07.016
  40. 40.Roy RK. Design of Experiments Using the Taguchi Approach: 16 Steps to Product and Process Improvement. New York: Wiley; 2001
  41. 41.Kumar RS, Choudhary A, Babu SAKI, Kumar SK, Goswami A, Tiwari MK. Designing multi-period supply chain network considering risk and emission: A multi-objective approach. Annals of Operations Research. 2017;250:427-461. DOI: 10.1007/s10479-015-2086-z
  42. 42.Addinsoft. XLSTAT 2021.3.1 Data Analysis and Statistics Software for Microsoft Excel. Paris, France: Addinsoft; 2021
  43. 43.Christopher M. Logistics and Supply Chain Management. 1st ed. London: Financial Times/Irwin Professional Pub; 1992
  44. 44.Kanev D. The Paradox of Information. Economics and Management. Vol. 14. BLAGOEVGRAD: Faculty of Economics, SOUTH-WEST UNIVERSITY “NEOFIT RILSKI”; 2018. pp. 59-73
  45. 45.Sutrisno A, Andajani E, Widjaja F. The effects of service quality on customer satisfaction and loyalty in a logistics company. KnE Social Sciences. 2019;2019:85-92
  46. 46.Thai V. Logistics service quality: Conceptual model and empirical evidence. International Journal of Logistics Research and Applications. 2013;16:114-131. DOI: 10.1080/13675567.2013.804907
  47. 47.Wee HM, Blos MF, Yang W-H. Risk management in logistics. In: Lu J, Jain LC, Zhang G, editors. Handbook on Decision Making. Vol. 33. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012. pp. 285-305. DOI: 10.1007/978-3-642-25755-1_15. Available from:https://web.archive.org/web/20180618045623/https://link.springer.com/chapter/10.1007%2F978-3-642-25755-1_15

Written By

Marieta Stefanova

Submitted: February 5th, 2022Reviewed: February 17th, 2022Published: March 21st, 2022