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Article

Measuring Supply Chain Performance for Khanh Hoa Sanest Soft Drink Joint Stock Company: An Application of the Supply Chain Operations Reference (SCOR) Model

by
Tram Anh Thi Nguyen
1,
Thuy Lan Nguyen
2,
Quynh Trang Thi Nguyen
1,
Kim Anh Thi Nguyen
1 and
Curtis M. Jolly
3,*
1
Faculty of Economics, Nha Trang University, Nha Trang 57109, Khanh Hoa Province, Vietnam
2
Khanh Hoa Salanganes Nest Company, Nha Trang 57118, Khanh Hoa Province, Vietnam
3
Department of Agricultural Economics, Auburn University, Auburn, AL 36849-5406, USA
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(22), 16057; https://doi.org/10.3390/su152216057
Submission received: 21 September 2023 / Revised: 18 October 2023 / Accepted: 2 November 2023 / Published: 17 November 2023

Abstract

:
As Khanh Hoa Sanest Soft Drink Joint Stock Company attempts to satisfy consumer requirements and maintain market share in the salangane nest industry, it is important to monitor the efficiency of its supply chain (SC). This paper identified metrics to evaluate the firm’s SC performance, using secondary data from firm records, primary data from a survey of 200 sales agents, and the Supply Chain Operations Reference (SCOR) model. Production records revealed a manufacturing lead time of 11 days and a production time of 24 h plus 7 days for refrigeration and observation. Order fulfillment delivery times ranged from 13 to 16 days. About 86.0 percent of customers rated the product as good or very good, and 60.5 percent claimed benefits from consuming the product. SC management costs of goods sold were 75.27% of total costs, while production cost was 41.99% of total costs. Total assets increased 16.6% from 2019 to 2021, but profits declined by 32.9% for the same period, while return on assets fell 42.4%. To maintain a competitive advantage, the company should apply information technology to improve SC performance. The results showed that the SCOR model is appropriate for evaluating the performance of this firm and similar business enterprises.

1. Introduction

Supply chain (SC) coordination and performance evaluation employed to buttress enterprise effectiveness have taken center stage recently. New forms of business, such as virtual enterprises, international manufacturing and marketing, information management, and computerized logistics, develop and require constant evaluation and monitoring to be sustainable [1]. Currently, businesses that operate without frontiers [2,3] require greater emphasis on evaluating the performance of enterprise-level management of their supply chains to be successful [4,5]. Globalization has given rise to digitalization, advanced planning systems (APS), increased use of outsourcing, vendor-managed inventory, and increased demands for integration [6,7]. Hence, with revolutionary changes in business organizational structure and modes of communication to adjust to international demands, performance evaluation is becoming essential in supply chain management (SCM) to determine the efficiency of operations and provide a basis for decision making [8,9].
The salangane nest industry in Vietnam has recently entered the international market while maintaining strong domestic sales, using a combination of traditional and modern operational techniques. Therefore, Khanh Hoa Sanest Soft Drink Joint Stock Company can serve as an example firm where performance evaluation tools generate information for SCM decision making. The company has undergone numerous changes as it transitions from traditional to modern performance evaluation techniques. Modeling the performance of firms that use both traditional and modern business recording systems is difficult and produces results that are not easily comprehensible. Hence, it is important to search for a model that facilitates improved performance evaluation and communication along the SC.
There are numerous methods to measure or evaluate SCM performance, which can be classed as financial—activity-based, costing, and economic value added—or nonfinancial, such as the Supply Chain Balanced Scorecard and Supply Chain Operations Reference (SCOR) model [8]. The SCOR model was first developed by the Supply Chain Council (SCC) in 1996 [8,10,11] and has introduced methods, diagnostic tools, and benchmarks to help companies devise rapid improvements in SC operations evaluation. The model introduces a business process, framework, performance metrics, practice analysis, and techniques to support collaboration among SC actors to increase SC efficiency [12]. An integrated cross-functional framework links performance measures, best practices, and software requirements to a detailed business process model [13]. Hence, this model is ideal for evaluating the performance of a company with dual means of operation, traditional (manual operating logistical networks) and modern (computerized and digital operating platforms of interconnected networks), and to determine the efficiency of operation before and during a major event like the COVID-19 pandemic.
Khanh Hoa Sanest Soft Drink Joint Stock Company, which produces Edible Bird Nest (EBN) drinks, underwent several changes from 2017 to 2022 that improved the standing of the company nationally and as an emerging source of export revenue. Despite the growing economic importance of the EBN industry to Vietnam, studies on the SC of this industry are limited. By combining elements of business process engineering, the elements of product manufacturing and marketing, management skills, and a variety of metrics, into a succinct framework, SCOR makes it possible to locate core process areas in the SC that need optimization [14,15,16]. Hence, it is important at its present stage of development to perform a case study of the SC of Khanh Hoa Sanest Soft Drink Joint Stock Company.

1.1. Khanh Hoa Salanganes Nest Company and EBN Products

Khanh Hoa Sanest Soft Drink Joint Stock Company belongs to the Khanh Hoa Salanganes Nest Company. It makes soft drinks from edible nests produced by salangane birds, insectivorous swiftlets of the family Apodidae that inhabit limestone caves in many parts of Southeast Asia [17,18,19]. A precious natural product served at the banquets of feudal dynasties, these EBNs are highly sought after due to their purported nutritional, aphrodisiac, and health benefits [19,20,21], which include toning the organs of the body, relieving gastric problems, and aiding kidney function [17]. The EBN soft drink is high in protein and contains 18 amino acids. Increased demand for the product has led producers to move from ranching [19] to the construction of numerous large buildings to house colonies of the birds, which may have an adverse effect on the overall population of swiftlets [22,23] and the SC.
The Salanganes Nest Company SC goes from source to production, inventory, and delivery to customers. After 17 years of establishment and development, the factory has built a trademark and a strong reputation and occupied most of the domestic market in a volatile business environment. Fierce competition before and after the COVID-19 pandemic from domestic and international EBN brands, plus technological advances, has shortened the product life cycle. The Industrial Revolution 4.0 has increased the complexity and geographical fragmentation of SC management for such a distinct product and is forcing suppliers to modernize. Therefore, it is essential to improve the SC to maintain the company’s competitive advantage. Performance measurement helps producers identify SC weaknesses and determine where improvement is needed. The SCOR framework is an appropriate tool to evaluate SCM at the industry or enterprise level because it can help businesses evaluate, communicate, and optimize decisions. Khanh Hoa Sanest Soft Drink Joint Stock Company was selected for this case study because of its structure, industry growth, and desire to operate in the global market.

1.2. Objective

In today’s volatile market environment, firms such as Khanh Hoa Sanest Soft Drink Joint Stock Company face many challenges to satisfy consumer requirements, penetrate the soft drink market, and maintain their market share globally. Hence, it is important that firms remain competitive and that they measure and monitor the levels of efficiency at each node of the SC. That means choosing metrics and models that evaluate firms adhering to traditional and modern techniques of SCM. The objectives of the study were to:
Identify metrics for measuring the efficiency of the EBN SC which employs traditional and modern forms of SCM.
Evaluate the SCOR as an appropriate model to analyze and measure the performance of the Salanganes Nest product SC.

1.3. Scope

The paper identifies the various processes of product manufacturing and uses financial and nonfinancial indicators and the SCOR model to evaluate the SC efficiency of the business entity, considering changing trends from 2017 to 2022. The literature, however, offers scant advice on the appropriate models to conduct an evaluation of the SC which may suggest whether the current firm strategy of maintaining a combination of traditional and modern techniques of SCM to maintain competitiveness is opportune, given present changes in the product life cycle. The use of the SCOR model may allow the manager of the company and other managers of similar enterprises to extrapolate general lessons from this empirical study to determine specific SC performance measurement approaches applicable to their firms. The information generated from the paper will be helpful in the critical analysis and performance management of the SC to enhance global competitiveness. The paper continues with materials and methods, results, and a conclusion.

2. Materials and Methods

The study design intended to capture and test the basic underlying principles of the SCOR model in four stages (Figure 1). Stage I involved a serious and thorough review of the literature on the SCOR model, SC performance management, and the production process of the EBN drinks. The purpose of the thorough literature exploration was to find other research applying the SCOR model that could guide the study in secondary data collection and in Stage II for evaluating Khanh Hoa Sanest Soft Drink Joint Stock Company. We used the Google Scholar search engine and searched publishers such as Springer, Elsevier, and Emerald. Because the SCOR model underwent a major revision in 2022, the literature review focused on the period between 2004 and 2022.
Stage II began with the collection of secondary data from company business records from 2017 to 2021. These data covered planning and order processing, purchasing, the production process, packaging cost of defective products, sales for each market, distribution and consumption situation, number of deliveries, number of contracts and contract performance, income statements, and other financial statements. An evaluation of the secondary data informed the researchers the need for survey data in Stage III.
Stage III involved interviews with the managers of Khanh Hoa Sanest Soft Drink Joint Stock Company, specifically on (1) the company’s measurement of its business performance; (2) whether the company measured its supplier-to-customer time for product delivery; and (3) the extent to which information technology applied. The study employed a two-pronged approach: secondary data on customer-facing performance (reliability, responsiveness, and agility) which supported customer interviews to obtain information on their perception of the product and production systems, while internal-facing (costs and assets) performance attributes were derived from the enterprise resource planning (ERP) system.
We conducted a survey of 200 agents or sales managers out of 900 at the company’s customer appreciation conference held each year to honor agents in the country. Agents play an important role in the evaluation because they have knowledge and information about the products. The company wanted to understand their customers’ perception and expectations of the company’s reaction in handling their requests. The survey content covered product quality, prices, sales policy, and brand awareness, feedback mechanisms from agents in receiving information on product quality and services. The company’s customers include agents, supermarkets, retailers, and consumers. All secondary and primary data were prepared for analysis in stage IV.
Stage IV included data entry using an Excel spreadsheet and data analysis. The data analysis involved the calculation of simple descriptive statistics and financial ratios. Based on these data, we analyzed and measured the performance of the salangane nest product SC at Level 1 to evaluate the effectiveness of the five SC processes: Plan, Source, Make, Deliver, and Return. The final step was the preparation of the paper.

2.1. Literature Review and Research Overview

The review defines SC, SCM, and SC performance measurement (SCPM) to provide a background for the SCOR model. It also covers the identification of metrics and the application of the SCOR model.

2.1.1. What Is SCM?

An SC consists of all parties involved, directly or indirectly, in fulfilling a customer request. It depends on strategies for the efficient management of sourcing inputs, production, and distribution of outputs in partnerships with suppliers and distributors to move a product from producer to consumer [24,25]. Thus, the SC includes the manufacturer and suppliers, transporters, warehouses, retailers, and even the customers themselves [26]. The management of relationships across the SC is the SCM. Hence, SCM deals with total business process excellence and represents a new way of managing the business and relationships with other members of the SC [26].

2.1.2. Measuring SC Performance

SCM is the incorporation of key business processes from the original supplier to the end user that provides products, services, and information to add value for customers and other stakeholders [25]. It employs a set of approaches to efficiently integrate suppliers, manufacturers, warehouses, and stores along the SC so that the product is produced and distributed in the right quantities, to the right location, and at the right time to minimize system-wide costs while satisfying service level requirements [27,28]. SCPM indicates whether a firm is meeting the goals set for its survival and growth. The basic objective of SCM is to “optimize performance of the chain to add as much value as possible for the least cost possible”. In other words, it aims to link all the SC agents to cooperate jointly within the firm to maximize productivity in the SC and deliver the most benefits to all related parties [29].
SCM is becoming a difficult challenge because of severe international and domestic competition, management’s drive to maintain market share, and changes in market demands [30]. Hence, it is imperative to measure and monitor supply chain performance (SCP) to enable company survival. Performance measurement is the process of quantifying the efficiency and effectiveness of action by means of a set of metrics [31]. Measuring SCP can facilitate a greater understanding of the SC, positively influence actors’ behaviors, and improve overall performance. The metrics used must be reckonable but contain intangible dimensions representing customer-facing performance as well as financial indicators representing internal-facing performance. They must be measurable and observable as well as capturing the company’s operating environment [32].
Firm reliability, responsiveness, flexibility, and agility are consumer-oriented attributes, while cost and asset management efficiency are internal-oriented attributes [33] (Table 1). Performance metrics that can be implemented in an organization, such as quality, flexibility, cost, supplier reliability, innovation, responsiveness, order delivery lead time, final product delivery reliability, product variety, and asset management [9], are used to measure specific strategies of the firm, depending on the approach employed [34]. There are three types of approaches to SCPM: process-based approaches, perspective-based approaches, and hierarchy-based approaches [35].
Process-based approaches: SCM is the integration of processes and activities involved in transferring products and services from the supplier to the end customer. Many researchers have considered the key operational processes of the SC to develop performance measurement frameworks such as Six Sigma metrics [35,37], the four SC processes (plan, source, make, and deliver), and an integrated model to measure the three echelons (supplier, manufacturer, distributor). An internal process approach examines factors such as integration with SC partners, rework, supplier rejection rate, cash flow time, supplier lead time against industry norms, product development cycle time, and effectiveness of master production schedule [38].
Perspective-based approaches: There are six main perspectives for measuring SCM: system dynamics, operations research, logistics, marketing, organization, and strategy [9,35]. These approaches assemble generic performance measures and provide the interrelationship among the performance measures. There are two main perspective models: Balanced Scorecard models and SCOR models.
Hierarchical-based approaches: In hierarchical-based models, measures are classified as strategic, tactical, or operational [9,30,39]. Hierarchical-based models are useful to measure SCP at different levels of hierarchy. A manager requires the right measures at the right time to make the right decision at each level of the SC (strategic, tactical, and operational). Many studies have used these models to evaluate SCP through, for example, applying a measurement model with strategic, tactical, and operational level indicators; measuring performance indicators in an international environment; and assessing the level of safety, risk, and capacity of chain operations [40,41,42].

2.1.3. Measuring SCP Using the SCOR Model

SCOR is a process reference model and a management tool used to address, communicate, and evaluate management decisions [41]. The framework of the SCOR model consists of five processes: Plan, Source, Make, Deliver, and Return. These processes repeat reiteratively along the SC to enable continuous improvement (Figure 2).
SCOR analyzes and measures SCP of companies at three levels: Level 1—strategic level (process types), Level 2—configuration level (process categories), and Level 3—process element level (decompose processes), where the latter is diagnostic for the former [41]. In this case study, we applied Level 1 of the SCOR model to study the case of the EBN product SC at Khanh Hoa Sanest Soft Drink Joint Stock Company. The SCOR Level 1 model identifies five performance attributes and measures them in two groups: customer-facing and internal-facing groups (Table 1) [41].
SCOR is a management tool that SCC encourages businesses to use to measure performance and SCM. Based on the measurement indicators of the SCOR model, an administrator can sketch a picture of the company’s performance to optimize management decisions. Khanh Hoa Sanest Soft Drink Joint Stock Company has two decades of experience in the field of salangane nest products, but the company still manages some of its activities along the SC using traditional methods. As part of the company’s transition to modern management, SCOR is an effective model to help the company measure performance from input to output.
The five management processes—Plan, Source, Make, Deliver, and Return—are discussed first (Figure 2). Plan processes balance customer demand, the company’s capacity to furnish the product, and a course of action that best meets the business goals. Plan processes include planning the SC. The Source processes include procurement of inputs, raw materials, and other services. The Make process includes functions that convert raw materials to finished goods and services, as well as the jobs of requesting and receiving material and safely manufacturing a quality product. Deliver processes supply inputs and provide packaged, quality products to satisfy customers’ demand. Return deals with managing the reverse flow of material, products, funds, and information related to defective and surplus products. This includes authorizing, scheduling, receiving, verifying, disposing, and a replacement or credit for the above types of materials.
The SCOR model then allows the use of data to measure performance, provide information to improve the industry structure, and supply a better product to the customer. Each interaction of two execution processes is a link in the SC. The first process, Plan, perches at the top of these links and manages them.
As previously mentioned, the SCOR model contains three levels of process detail. Level 1 is the top level that deals with process types, and we will concentrate our efforts on that level (Figure 3). The SCOR model simulates the processes of the production and delivery of the salangane nest products and can facilitate the identification of operational and management performance and suggest ways to improve customer satisfaction.
The SCOR model has attained success in many sectors, including the pharmaceutical industry, digital technology, and manufacturing, to identify efficient supplier solutions [40]. The SCOR model is often used with multicriteria decision-making tools, the analytical hierarchical model, and methods to facilitate supplier selection [41,42]. Erkan and Bac [43] studied the applicability of the SCOR model to measure SCP at a steel manufacturing company in Turkey. They focused on the compatibility and sustainability of the SCOR model and defined the five processes as Planning, Generating, Production, Delivery, and Returns.
Another study by any et al. [44] used SCOR model metrics combined with enterprise resource planning research and an analytic hierarchy process in the Ecuadorian flower industry. Kusrini et al. [28] ranked SC process metrics on the following scale: less than 40 (poor), 40–50 (marginal), 50–70 (average), 70–90 (good), and greater than 90 (excellent). Based on this scale [28], Manay et al. [44] studied the SCs of 29 companies in the Ecuadorian flower industry in several steps. They first determined the weights of five processes: Planning (0.405), Procurement (0.198), Production (0.173), Delivery (0.138), and Returns (0.084). Then, they calculated the average value of the indexes of these processes respectively: Planning (0.86), Procurement (0.88), Production (0.79), Delivery (0.88), and Returns (0.80). When looking at the SCOR processes at the industry level, the research showed a large gap between expected results and actual results for Planning, Production, Procurement, Delivery, and Returns (0.06; 0.04; 0.02; 0.02; 0.02, respectively). Based on these results, the authors recommended that flower companies in Ecuador focus on improving their planning and production processes. This research helps managers, consultants, the manufacturing industry, and government to improve SCs and increase competitiveness in international markets.
Figure 3. Simulation model of Salanganes Nest Company. Source: Formulated by the authors, with inspiration from Huang et al. [45,46] in Saleheen et al. 2018.
Figure 3. Simulation model of Salanganes Nest Company. Source: Formulated by the authors, with inspiration from Huang et al. [45,46] in Saleheen et al. 2018.
Sustainability 15 16057 g003

3. Research Results and Discussion

3.1. Salangane Nest Product Supply Chain

Figure 4 illustrates the complexity of the salangane nest product SC. The raw material consists of birds’ nests originating from natural islands managed by the company to assure product quality and quantity. The raw products combine with other imported auxiliary materials, which include ingredients and packaging materials sourced from global markets. The company sources other auxiliary materials (sanding sugar, rock sugar), other packaging materials, and fuel from domestic suppliers. All these raw materials enter the company’s manufacturing process, and distributors at Ho Chi Ming City, Kan Koa, Da Nang, and Hanoi branches handle the finished, branded products. The distributor agents here alsomarket the final product through wholesalers and retailers to customers. Observe the location of the main distributors in the country in Figure A1.

3.2. Analyzing the Salangane Nest Product SC with the SCOR Model

3.2.1. Plan

The branch office determines customers’ weekly/monthly/quarterly/yearly demands and forwards the orders by fax, email, or phone to the sales department. Figure 5 demonstrates the planning and execution of an order by the sales manager. The planning process of an order begins with an inventory check by the stockkeeper. A comparison of the number of orders received is made after receiving and checking the inventory status. The sales department makes weekly/monthly plans, submits them to the manager, and prepares production inputs. The planning of the delivery involves a series of decisions by the accounting department, factory manager, sales department, and marketing department until the product is loaded and unloaded and is in the domain of the consumer. The criterion for planning is to ensure timely delivery of goods to markets. The accounting department checks the payment and debt terms on the contract that each market, distributor, and agent signs. If the documentation is correct and meets regulations, the sales department responds to the orders or delivers the goods.
So far, at Khanh Hoa Sanest Soft Drink Joint Stock Company, order processing has been manual and there has been an absence of information technology application to connect the market and administrative steps. At the company level, paper files are still used, which consumes more time and human resources and makes it difficult to access data. Depending on requirements, the market personnel can ask the factory to deliver goods directly to warehouses belonging to showrooms or distributors and agents. Although the company has invested in a local area network (LAN), it is still not integrated.

3.2.2. Source

The materials sourced for product manufacturing include raw materials, packaging, and fuel. The main raw materials are birds’ nests from natural islands. Domestic raw materials include granulated and rock sugar purchased directly from factories. Imported materials include isomalt, sodium alginate, xanthan gum, calcium lactate, fucoidan, ginseng, collagen, and incense. These materials are manufactured in Europe and the US according to the factory’s own specifications. The delivery time for imported materials is 4–5 months from the date of order, and the inventory is sufficient for production from 5 to 6 months. Due to the characteristics of these materials, it is difficult to replace them because they affect the production process, recipe, and taste.
Glass jars are imported from Thailand and aluminum lids from Singapore. The packaging requires exact specifications and standards that meet the requirements of domestic and import markets. Delivery time for these types of packaging is 4–5 months, so the factory has a large inventory and orders for the whole year. Paper packaging, shrink film, tape, glue, and laser anti-counterfeit stamps are included in short-term production plans (weeks/months), with a low inventory and delivery on time. The fuel (DO oil and nitrogen gas) is stored in large tanks. When there is a demand, the company sends an order within three days to the supplier, for fuel to be delivered quickly to the factory. Materials for manufacturing are sourced from Europe, and therefore replacement materials and spare parts must be imported within an expanded delivery period.
The number of suppliers for the company was relatively stable over the period of 2017–2021, fluctuating from 40 to 50. However, purchasing still has limitations such as untimely delivery, incorrect quality and quantity of materials, and order cancellation. Because packaging materials are imported, the delivery time is long. The factory has many automatic production processes, and the packaging and production materials must be precise in every detail. When the production has a problem and the import time is too long, the goods are often not delivered on time. In addition, when the product is not of the right quality and quantity, mainly in paper packaging, the chances of rejection are higher. When market demand increases suddenly, there are temporary shortages. Most of the suppliers have been with the company for a long time, so the parties understand the product requirements.

3.2.3. Make

Based on customer weekly/monthly/quarterly demand information received from the branch offices, and inventory levels, the factory executes a production plan. The production process starts with the assembling of the various ingredients (e.g., sugar food additives and spice), then cooking and mixing. Each product has different recipes for processing, followed by filling, capping the product, sterilizing, packing, and shipping. Figure 6 shows the process of making the product.
The quality control department monitors closely all the stages. The time from receiving the product to packaging is 24 h for bird’s nest jar products. However, for safety and quality, before transporting to the market, products are kept in cold storage for 7–10 days to check for microbiological contamination and other technical quality criteria. This is also a high-end product, so after manufacturing, packaging, and sterilizing through automatic testing equipment, the factory checks each product manually to ensure absolute safety before the product leaves the plant.
The product codes in Table 2 indicate different types of EBN products in glass jars: sweetened, unsweetened, ginseng, etc. During the production process, failed products after filling and capping (black dots in the product, faulty cap assembly, insufficient pressure, incorrect weight) are rejected. These products are checked, recycled, or have the water removed from the product. Some production stages cannot be replaced by machines (manual packaging), and thus human error (wrong operation, wrong operating procedure) may damage packaging. After the rejection of the faulty products, inspection and classification are necessary to see if they can be recycled or discarded. For recycled products, the packaging is removed and replaced, which adds to production costs. During the period from 2017 to 2021, the number of rejects and rejection costs remained constant (Table 3).

3.2.4. Deliver

For over 17 years, Salanganes Nest Company products have occupied the leading position in the country, with over 900 distributors and agents nationwide. The company’s distribution system has four major branches. The spatial distribution consists of: (1) the Ho Chi Minh City branch (19 provinces) manages the markets from Dong Nai province onward, the eastern and southwest provinces. (2) The Da Nang branch (17 provinces) manages the market from Da Nang City to Binh Thuan province, including the Central Highlands region (excluding Khanh Hoa province). (3) The Hanoi City branch (26 provinces) manages the markets from Thanh Hoa province onwards; and (4) The Khanh Hoa branch includes Nha Trang City and districts.
For each branch, the company has a delivery network including a system of distributors and agents in every province to supply retail stores. (1) Each distributor or agent has representatives to manage and monitor deliveries. (2) HoReCa channels include nationwide supermarket systems, restaurants, hotels, amusement parks, and coffee shops. (3) Showrooms introduce products with unique features from Khanh Hoa Salanganes Nest that are uniform across the country. (4) At affiliate stores, the storeowner bears the cost of the business premises; the company invests in signboards and displays and supplies products. The stores that reach sales targets receive special rewards according to a monthly bonus policy. In addition, the company delivers through sampling and promotion events, connects to agencies, schools, associations, unions, tours, etc., and invites them to visit the production line free of charge.
The Ho Chi Minh City branch markets distribute the highest proportion of products. Next are the provincial-level markets under the Da Nang, Khanh Hoa, and Hanoi branches. With the goal of popularizing Khanh Hoa EBN drinks to consumers and promoting public health, the company has researched technical, production, and processing techniques, combining tradition with modern technology to save money, decrease costs, increase competitiveness in the market, and offer the best prices to many customers. In 2018 and 2019, revenue from bird’s nest jar products was highest (over VND 2 trillion = USD 90.09 million) but decreased by 50% in 2020 (1 trillion VND). During 2020–2021, revenue decreased sharply because of the influence of the COVID-19 pandemic on business. Revenue from the Hanoi branch and exports is still very low and not commensurate with the market potential (Figure 7). Therefore, the company should continue to invest in expansion and development in the coming years.
Depending on the actual location, number of orders, and delivery time, the factory uses company vehicles or outsources delivery to increase efficiency and timely response to customer demands. The market of the Hanoi branch is far from the factory, so the factory hires a logistics company to transport the goods to the Hanoi branch warehouse and then the branch delivers them to another market. The orders along National Route 1 are delivered early to save costs. The distance from the factory to the markets of the Da Nang branch is 70–400 km, and each order has a volume of 2–10 tons, so the factory delivers directly or combines outsourcing with factory vehicles to respond to distributors, agents, and showrooms in a timely manner. Small orders from 1.8 to 4.4 tons use factory vehicles, and large orders are outsourced. In Da Nang, there is a warehouse for the branch to deliver small orders to provinces such as Nghe An, Ha Tinh, and Quang Nam. In Khanh Hoa, the factory and sales areas are close to one another, so they mainly use factory vehicles every day. Markets for the Ho Chi Minh City branch have large orders and consumption quantities, so transportation is mainly outsourced. If the market has orders with excessive weight, the factory rents a vehicle to deliver the load directly to the purchase area to reduce costs.
With the criterion disallowing the shortage of goods, when market demand is high, the company’s order completion time must be quick. The company produces according to the inventory model, so the delivery time for distributors and agents depends on the geographical location. The Da Nang branch and Ho Chi Minh City branch have delivery times of 48 h, the provinces of the Hanoi branch 84 h, and Khanh Hoa province 5 h after receiving payment from the customer. The company estimates a reasonable amount of inventory to supply customers with unexpected purchasing needs immediately. The company also reserves inventory at the factory to supply on-demand orders. The time from warehouse pickup to payment receipt from the customer is about 15 days. The value of inventory is high due to the characteristics of imported packaging and the materials reserved to ensure continuous production to satisfy market demand. This situation is common at the end of each quarter or year when the demand increases dramatically.

3.2.5. Returns

The amount of goods returned is small; returns are due to torn or broken packaging or microbial contamination. The company has a process for evaluating and handling returned goods as follows: branches receive information from the market or customer feedback to the customer service center; then customer care staff immediately makes a direct appointment with the customer, makes an on-site appearance to explain, or brings back analysis, then gives feedback to customers. If it is due to a manufacturing error, they can check the diary and traceability then conclude and respond to the customer.

3.3. Measuring the Performance of the Salangane Nest Product SC

The SCOR method facilitated the evaluation of this salangane nest product SC. We first examined customer-facing performance, in which the company employees had direct interaction with customers. Customer-facing performance is composed of reliability, responsiveness, and flexibility. Reliability received a score of 100% because of a perfect fill rate and delivery performance, made possible through modern equipment, machines, materials inventory, and adequate plant capacity (Table 3). The information in Table A1 shows that there were 10 cancellations in the period studied, all during 2020, at the height of the COVID-19 pandemic. The firm was relatively responsive to customers’ requests in terms of order fulfillment, and the lead times for manufacture were only 11 days. Production time was 24 h plus an additional 7 days for refrigeration and observation. The firm was flexible in terms of order fulfillment delivery times, which ranged from 13 to 16 days. The plant could supply the quantity demanded at a given time because of excess plant capacity.
Internal-facing performance relates to financial components: costs and assets. The SCM costs of goods sold were 75.27% of total costs, while the production cost was 41.99% of total costs. This indicates that the firm was profitable. The assets showed a cash–cash cycle of 43.81 days and inventory days’ supply of 43.82 days. However, this was much shorter than it took to source raw material inputs from international suppliers. Even though total assets increased by 16.6% from 2019 to 2021, profits declined by 32.9% for the same period while return on assets fell by 42.4% (Table A1). It appears that COVID-19 had a major effect on the company’s internal-facing performance, but the effects on customer-facing performance were small. The plant survived the ravages of COVID-19 and is still operational, which indicates that the business is sustainable.

3.3.1. Measure Performance through Nonfinancial and Financial Metrics

Performance measures and metrics are essential for effective performance evaluation of SCM. The challenge for managers in evaluating SCM is to acquire suitable performance measures and metrics to make the right decisions to improve organizational competitiveness [46]. Now, the question is, are traditional performance measures adequate, or can firms use customer surveys to obtain direct feedback from product users? Some of the traditional measures of internal-facing performance are easily identifiable but do not assist with customer-facing performance. Measuring intangible and nonfinancial performance poses the greater challenge in business performance evaluation, and may be better conducted with a customer survey, backed up by firm data. Valuable information of various kinds is obtained when customer surveys and internal-facing information are integrated to identify areas of potential improvement [47].

3.3.2. Measure Performance Based on Customer Surveys

The company holds a customer appreciation conference each year to honor agents in the country. Agents play an important role because they have knowledge and information about the products. They serve as a bridge connecting the company with consumers. With the support of a manager, the authors obtained feedback from 200 agents. About 86.0 percent of them indicated that the product quality was good or very good, and 60.5 percent claimed that there were positive benefits from consuming the product (Figure 8 and Figure 9).
The high product quality ratings may be due to the birds’ nests coming from a natural island. The company has disseminated scientific research information on EBN products to enhance customers’ perceptions of product safety. Second, with the goal of increasing the popularity of EBN products, prices can be increased, since consumers indicated that the product price was average, which means that it is relatively affordable. Third, packaging designs and promotions are normal, since only 43.0 percent indicated that the product was attractive, and 56.0 percent said that the packaging was normal, indicating that some improvement is necessary to adjust to specific market demand. Fourth, there is no superiority in brand awareness. Whereas promotion was considered normal (64.0 percent), brand awareness was considered good (44.0 percent) or very good (49.0 percent) (Figure 9).

4. Discussion and Conclusions

The SCOR model involves planning, and the method includes analyzing information and forecasting market trends for goods and services [48]. Khanh Hoa Sanest Soft Drink Joint Stock Company applies the planning process through weekly and monthly operational and long-term annual decision making, which facilitates its ability to meet long-term and seasonal demands. It employs a procurement system using large inventories to ensure that the supply meets demand. The just-in-case inventory system is more appropriate than the just-in-time one, even though it is costly, given the risks of having insufficient materials at the required time. Modern and lean forms of purchasing can be explored by adopting new technologies that will facilitate the delivery of inputs and reduce just-in-case purchasing. The size of safety inventory stocks required to obtain a certain customer service level depends on the degree of demand uncertainty and the corresponding forecast errors. Demand misspecification significantly affects the whole SC, but its costs can be reduced by minimizing forecast errors [36,49]. Improving forecasts can directly influence inventory savings and service level improvements [50]. The company’s product manufacturing, in terms of time, allows it to deliver its finished product to reach planned or actual demand, minimize risks, and increase sustainability [51].
Our analysis of the salangane nest product SC with the SCOR model showed that the company’s performance was perfect in the areas of customer-facing reliability, responsibility, agility, and flexibility. Reliability and responsibility come at a cost, but the question is, are consumers willing to pay for zero expected failures, given the anticipated price increases for such effort, over any product use over a duration of time? The scores were perfect in this area, and even with the incidence of COVID-19, no standards are necessary for comparison. The customer survey showed that a large proportion of respondents were satisfied with the company’s performance. One limitation was the absence of a question relating to willingness to pay a higher price for the product, although 77.0 percent said that the price was average, while 20.5 said it was too high.
While customer-facing performance seemed to be almost perfect, there was room for improvement of internal-facing performance, and the indicators were seriously affected by COVID-19. The company’s financial indicators, such as return on assets, working capital turnover, and inventory turnover, decreased sharply during the period of 2020–2021 due to the influence of the pandemic; total profits fell while total assets increased.
The SCOR model is an extremely effective tool for translating strategy into SC performance goals. By following the SCOR project mapping, one identifies strengths and disconnects in the SC planning process that can be resolved to improve the company’s performance [52]. For Khanh Hoa Sanest Soft Drink Joint Stock Company, the customer-facing aspects appear to be good, with few areas needing improvement, but internal-facing aspects show some weaknesses. The ability to apply information technology to communicate within and between parts of the SC is still limited [53]. Product movement and forecasting are manual and sporadic, and inventory and sales have not been connected to markets. The company mainly uses Excel spreadsheets, with no additional software, to update market demand status. Information from markets is delayed and feedback processing is slow. In addition, there is no inventory management software available in stores. The return on assets for the drinks company is less than desired, but overall, business performance remains good, and adjustments being made will increase sustainability [54]. Today, with big data analytic techniques, the SCOR model allows for solid performance evaluation even with basic software or no software at all and enables managers to detect areas requiring immediate attention [55].
A limitation of this study is that comparisons were not made with other companies producing similar products; the difficulties of obtaining data from other firms limited the scope of the study to just one company. However, with the present contact, the hope is that longitudinal data can be collected, and AHP and machine learning techniques can be used to improve the analysis [56]. A broadened scope involves the collection of longitudinal and cross-sectional data for future analyses and comparisons using the SCOR model.

5. Recommendations

To maintain a competitive advantage in the long term and adapt to the 4.0 technology revolution, we recommend that the factory apply information technology in SCM [57]:
(1) Enterprise resource planning (ERP) systems aim to integrate business processes of the enterprise, collect data from key functions, and store data (Figure 10). Figure 10 shows a simulation of modernized business processes. There are several benefits of using ERP: (i) ERP integrates data from each department into a common database with high accuracy and quickly generates complex analytics and diverse reports. Employees can access data simultaneously in the ERP system easily. Therefore, they save costs and time and reduce paperwork. (ii) ERP enables companies to monitor inventory accurately and determine optimal inventory, thereby reducing working capital demand and increasing production efficiency, checking the accuracy of accounts, streamlining human resource processes, and calculating employee salaries. (iii) Areas of inefficiency are identified to be eliminated in the production process, increasing the company’s production productivity. (iv) ERP defines business processes, helping to assign work to the company’s day-to-day operations.
(2) The factory can apply Electronic Data Interchange (EDI) technology to exchange data (Figure 11). By using EDI, the factory will save on the cost of paper document processing, save time, and increase accuracy and efficiency. An EDI system ensures safety, and the factory can check the route of product at each stage. Automating data in the SC helps to reduce errors at all stages of the process (ordering, drafting contracts, invoicing). Therefore, the factory can speed up transactions with partners and customers and ensure business efficiency.
(3) An application to share point of sale (POS) data (Figure 12) is also useful and can serve as a feedback mechanism to the manufacturer. This process can be employed to develop an inventory management model, because inventory management is important for the factory. Therefore, the factory should accurately forecast customer demand to plan purchases and limit inventory accumulation. For distribution (agents, stores, distributors), the system application supports sales management and payment processing. A POS system is used at the checkout counters of retail stores; it is a combination of hardware (barcode scanner POS, receipt printer, payment card reader, cash drawer, and cash register) and POS software to perform and control all transactions. Retail stores applying POS systems and sharing customer data through POS servers with market branches help branches manage customer information and forecast demand accurately. When retail stores install POS, the entire business process is updated, and transactions with customers can be controlled to the maximum. Retail stores can share pertinent sales information with the branch office, which enables the factory to assess changes in customer behaviors and demand and enhance forecasting accuracy. Therefore, the factory manages productivity and inventory levels. All data on consumer demand and inventory from all retail stores are forwarded by the POS factory central transfer to the ERP system for overall control of enterprise resources (Figure 12).

Author Contributions

Conceptualization, Methodology and formal analysis T.A.T.N.; Data processing, T.L.N.; Data analysis, Q.T.T.N.; Writing—original draft, K.A.T.N.; Writing—review & editing, C.M.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

The authors would like to thank the NORHED II Project (ECOGIV Project number 63113) for their support in the preparation of this paper and the Khanh Hoa Salanganes Nest Company for allowing us to use their data and conduct the survey at their customer appreciation conference.

Conflicts of Interest

Author Thuy Lan Nguyen was employed by the Khanh Hoa Salanganes Nest Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Appendix A

Figure A1. Map of Vietnam showing major product distribution centers.
Figure A1. Map of Vietnam showing major product distribution centers.
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Table A1. Supply chain performance metrics.
Table A1. Supply chain performance metrics.
ItemsUnit20172018201920202021Comment
1. Order fulfillment rate
Total number of deliveries in the yearTimes43654626482535443347The order fulfilment rate was good. The number of orders increased during 2017–2019 and began to decline from 2020.
Number of right deliveriesTimes43654626482535443347
Number of failed deliveries (domestic and international)Times00000
2. The number of supplier contracts
Number of contractsContract4646504040The number of contracts, the number of deliveries not on time, wrong quality and wrong quantity decreased from 2017 to 2021, and the number of cancellations of contracts increased in 2020.
Supplier delivery not on timeTimes168163160120108
Supplier delivery of wrong qualityTimes1261221208072
Supplier delivery of wrong quantityTimes4241404036
Cancellation of contractTimes000100
3. Return on assets
Profit after tax (1)VND198,029,041,364209,591,554,787214,367,845,959174,279,285,612143,876,584,008ROA decreased over the years because profit after tax decreased; however, total assets increased.
Total assets (2)VND1,089,621,958,7541,184,371,694,2981,275,682,738,1131,429,704,217,8401,486,892,386,553
Return on total assets ROA (3) = (1)/(2)%18.1717.7016.8012.199.68
4. Working capital turnover
Net revenue (1)VND3,919,077,019,2584,198,692,522,7833,729,688,212,1823,069,641,025,0552,511,224,273,092Working capital turnover decreased over the years due to decreasing revenue.
Short-term assets (2)VND537,837,398,841557,608,124,829616,956,775,336752,571,689,325782,997,530,758
Short-term debt (3)VND159,084,805,979168,931,540,872196,086,589,649300,422,682,180289,853,958,754
Working capital (4) = (2)–(3)VND378,752,592,862388,676,583,957420,870,185,687452,149,007,145493,143,572,004
Average working capital (5) = (4)/12VND31,562,716,07232,389,715,33035,072,515,47437,679,083,92941,095,297,667
Working capital turnover (6) = (1)/(5)Ratio124.17129.63106.3481.4761.11
5. Inventory turnover
Cost of goods sold (1)VND2,952,113,655,0873,113,841,166,7522,785,722,618,3422,338,892,926,7791,910,875,521,178Inventory turnover decreased due to a decrease in the cost of goods sold.
Average Inventory (2)VND160,006,626,155178,589,030,157220,680,189,840233,406,382,189198,983,356,707
Inventory turnover (3) = (1)/(2)Ratio18.4517.4412.6210.029.60
Stock cover day = 365/(3)Days19.7820.9328.9136.4238.01

References

  1. Arzu, G.; Erkan, T. Supply Chain Performance Measurement: A Literature Review. Int. J. Prod. Res. 2010, 48, 5137–5155. [Google Scholar] [CrossRef]
  2. Puigjaner, L.; Lainez, J.M. Capturing Dynamics in Integrated Supply Chain Management. Comput. Chem. Eng. 2008, 32, 2582–2605. [Google Scholar] [CrossRef]
  3. Sobirov, B. The Concept of the Tourist Economic Zone: Case of Uzbekistan. World Sci. News 2018, 98, 34–45. [Google Scholar]
  4. Gunasekaran, A.; Williams, H.J.; McGaughey, R.E. Performance Measurement and Costing System in New Enterprise. Technovation 2005, 25, 523–533. [Google Scholar] [CrossRef]
  5. Babenko, V.; Chebanova, N.; Ryzhikova, N.; Rudenko, S.; Birchenko, N. Research into the Process of Multi-Level Management of Enterprise Production Activities with Taking Risks into Consideration. East.-Eur. J. Enterp. Technol. 2018, 1, 4–12. [Google Scholar] [CrossRef]
  6. Meixell, M.J.; Gargeya, V.B. Global Supply Chain Design: A Literature Review and Critique. Transp. Res. E Logist. Transp. 2005, 41, 531–550. [Google Scholar] [CrossRef]
  7. Xu, J.; She, S.; Liu, W. Role of Digitalization in Environment, Social and Governance, and Sustainability: Review-Based Study for Implications. Front. Psychol. 2022, 13, 961057. [Google Scholar] [CrossRef]
  8. Agami, N.; Saleh, M.; Rasmy, M. Supply Chain Performance Measurement Approaches: Review and Classification. J. Organ. Manag. Stud. 2012, 2012, 1. [Google Scholar] [CrossRef]
  9. Lima-Junior, F.R.; Carpinetti, L.C.R. Quantitative Models for Supply Chain Performance Evaluation: A Literature Review. Comput. Ind. Eng. 2017, 113, 333–346. [Google Scholar] [CrossRef]
  10. Huang, S.H.; Sheoran, S.K.; Wang, G. A Review and Analysis of Supply Chain Operations Reference (SCOR) Model. Supply Chain Manag. 2004, 9, 23–29. [Google Scholar] [CrossRef]
  11. Lockamy, A.; McCormack, K. Linking SCOR Planning Practices to Supply Chain Performance: An Exploratory Study. Int. J. Oper. Prod. Manag. 2004, 24, 1192–1218. [Google Scholar] [CrossRef]
  12. SCC. Supply Chain Operations Reference Model Revision 11.0. 2012. Available online: https://docs.huihoo.com/scm/supply-chain-operations-reference-model-r11.0.pdf (accessed on 30 June 2022).
  13. Jacobs, F.R.; Chase, R.B.; Lummus, R.R. Operations and Supply Chain Management; McGraw-Hill/Irwin: New York, NY, USA, 2014. [Google Scholar]
  14. Khan, S.A.R.; Piprani, A.Z.; Yu, Z. Supply Chain Analytics and Post-Pandemic Performance: Mediating Role of Triple—A Supply Chain Strategies. Int. J. Emerg. Mark. 2023, 18, 1330–1354. [Google Scholar] [CrossRef]
  15. Khan, S.A.R.; Yu, Z. A Systematic Literature Review: Blockchain Technology and Organizational Theories in the Perspective of Supply Chain Management. J. Phys. Conf. Ser. 2021, 1910, 012011. [Google Scholar] [CrossRef]
  16. Pang, N.T.P.; Imon, G.N.; Johoniki, E.; Kassim, M.A.M.; Omar, A.; Rahim, S.S.S.A.; Hayati, F.; Jeffree, M.S.; Ng, J.R. Fear of COVID-19 and COVID-19 Stress and Association with Sociodemographic and Psychological Process Factors in Cases under Surveillance in a Frontline Worker Population in Borneo. Int. J. Environ. Res. Public Health 2021, 18, 7210. [Google Scholar] [CrossRef] [PubMed]
  17. Chantler, P.; Wells, D.; Schuchmann, K. Family Apodidae (Swifts). In Handbook of the Birds of the World; Lynx: Barcelona, Spain, 1999; Volume 5, pp. 388–457. [Google Scholar]
  18. Marcone, M.F. Characterization of the Edible Bird’s Nest the ‘Caviar of the East’. Food Res. Int. 2005, 38, 1125–1134. [Google Scholar] [CrossRef]
  19. Adebayo, O.M.; Panandam, J.M.; Sugnaseelan, S.; Tan, S.G. Mitochondrial DNA Variability of Edible Bird Nest Swiftlet (Aerodramus fuciphagus) Colonies in Malaysia. Int. J. Sci. Res. Publ. 2020, 10, 49–57. [Google Scholar] [CrossRef]
  20. Norhayati, M.; Azman, O.; Wan Nazaimoon, W. Preliminary Study of the Nutritional Content of Malaysian Edible Bird’s Nest. Malays. J. Nutr. 2010, 16, 389–396. [Google Scholar]
  21. Guo, C.T.; Takahashi, T.; Bukawa, W.; Takahashi, N.; Yagi, H.; Kato, K.; Suzuki, Y. Edible Bird’s Nest Extract Inhibits Influenza Virus Infection. Antivir. Res. 2006, 70, 140–146. [Google Scholar] [CrossRef]
  22. Rahman, M.; Ghazali, P.L.; Lian, C.J.; Basari, N.; Mamat, M.; Foziah, H.; Afthanorhan, A. Suitable ranching practices in successful edible bird nest swiftlet houses in Terengganu. Int. J. Recent Technol. Eng. 2019, 7, 60–64. [Google Scholar]
  23. Aowphol, A.; Voris, H.K.; Feldheim, K.A.; Harnyuttanakorn, P.; Thirakhupt, K. Genetic Homogeneity Among Colonies of the White-Nest Swiftlet (Aerodramus fuciphagus) in Thailand. Zool. Sci. 2008, 25, 372–380. [Google Scholar] [CrossRef]
  24. Nag, B.; Han, C.; Yao, D.Q. Mapping Supply Chain Strategy: An Industry Analysis. J. Manuf. Technol. Manag. 2014, 25, 351–370. [Google Scholar] [CrossRef]
  25. Chopra, S.; Meindl, P. Supply Chain Management Strategy: Planning and Operation; Pearson Prentice Hall: New York, NY, USA, 2007. [Google Scholar]
  26. Lambert, D.M.; Cooper, M.C. Issues in Supply Chain Management. Ind. Mark. Manag. 2000, 29, 65–83. [Google Scholar] [CrossRef]
  27. Levi, S.D.; Kaminsky, P.; Levi, E.S. Designing and Managing the Supply Chain: Concepts Strategies and Case Studies; McGraw-Hill Education: New York, NY, USA, 2008. [Google Scholar]
  28. Kusrini, E.; Rifai, M.A.B.; Miranda, S. Performance Measurement Using Supply Chain Operation Reference (SCOR) Model: A Case Study in a Small-Medium Enterprise (SME) in Indonesia. IOP Conf. Ser. Mater. Sci. Eng. 2019, 697, 012014. [Google Scholar] [CrossRef]
  29. Shukla, R.K.; Garg, D.D.; Agarwal, D.A. Understanding of Supply Chain: A Literature Review. Int. J. Eng. Sci. Technol. 2011, 3, 2059–2072. [Google Scholar]
  30. Oubrahim, I.; Sefiani, N. Supply Chain Performance Measurement Systems: Benefits and Drawbacks. Int. J. Latest Eng. Manag. Res. 2022, 7, 24–28. [Google Scholar] [CrossRef]
  31. Ambe, I.M. Key Indicators for Optimizing Supply Chain Performance: The Case of Light Vehicle Manufacturers in South Africa. J. Appl. Bus. Res. 2014, 30, 277–290. [Google Scholar] [CrossRef]
  32. Hwang, G.; Han, S.; Jun, S.; Park, J. Operational Performance Metrics in Manufacturing Process: Based on SCOR Model and RFID Technology. Int. J. Innov. Technol. Manag. 2014, 5, 50–55. [Google Scholar] [CrossRef]
  33. Sutopo, W.; Maryanie, D.I.; Yuniaristanto. Evaluation of Valuable Chain in Palm Oil Industry Based on SCOR Model: A Case Study. Int. J. Logist. Syst. Manag. 2015, 21, 229–244. [Google Scholar] [CrossRef]
  34. Ikasari, N.; Sutopo, W.; Zakaria, R. Performance Measurement in Supply Chain Using SCOR Model in the Lithium Battery Factory. IOP Conf. Ser. Mater. Sci. Eng. 2020, 943, 012049. [Google Scholar]
  35. Jagan Mohan Reddy, K.; Neelakanteswara Rao, A.; Krishnanand, L. A Review on Supply Chain Performance Measurement Systems. Procedia Manuf. 2019, 30, 40–47. [Google Scholar] [CrossRef]
  36. SCC. Supply Chain Operations Reference Model Overview Version 7.0. 2005. Available online: https://www.scpiteam.com/SCOR%207.0%20Overview.pdf (accessed on 12 July 2022).
  37. Nasab, S. Strategic Orientation in Evaluation of Supply Chain Activities. Manag. Sci. Lett. 2012, 2, 1785–1794. [Google Scholar]
  38. Otto, A.; Kotzab, H. Does Supply Chain Management Really Pay? Six Perspectives to Measure the Performance of Managing a Supply Chain. Eur. J. Oper. Res. 2003, 144, 306–320. [Google Scholar] [CrossRef]
  39. Gunasekaran, A.; Patel, C.; McGaughey, R.E. A Framework for Supply Chain Performance Measurement. Int. J. Prod. Econ. 2004, 87, 333–347. [Google Scholar] [CrossRef]
  40. Khan, M.; Bashar, I.; Minhaj, G.M.; Wasi, A.I.; Hossain, N.U.I. Resilient and Sustainable Supplier Selection: An Integration of SCOR 4.0 and Machine Learning Approach. Sustain. Resilient Infrastruct. 2023, 8, 453–469. [Google Scholar] [CrossRef]
  41. Es-Satty, A.; Lemghari, R.; Okar, C. Supply Chain Digitalization Overview SCOR Model Implication. In Proceedings of the 13th International Colloquium of Logistics and Supply Chain Management, Fez, Morocco, 2–4 December 2020. [Google Scholar] [CrossRef]
  42. Ayyildiz, E.; Taskin Gumus, A. Interval-Valued Pythagorean Fuzzy AHP Method-Based Supply Chain Performance Evaluation by a New Extension of SCOR Model: SCOR 4.0. Complex Intell. Syst. 2021, 7, 559–576. [Google Scholar] [CrossRef]
  43. Erkan, T.E.; Bac, U. Supply Chain Performance Measurement: A Case Study About Applicability of SCOR Model in a Manufacturing Industry Firm. Int. J. Bus. Manag. Stud. 2011, 3, 381–390. [Google Scholar]
  44. Manay, L.O.R.; Pradas, I.G.; Perez, I.M. Measuring the Supply Chain Performance of the Floricultural Sector Using the SCOR Model and a Multicriteria Decision-Making Method. Horticulturae 2022, 8, 168. [Google Scholar] [CrossRef]
  45. Huang, S.H.; Sheoran, S.K.; Keskar, H. Computer-Assisted Supply Chain Configuration Based on Supply Chain Operations Reference (SCOR) Model. Comput. Ind. Eng. 2005, 48, 377–394. [Google Scholar] [CrossRef]
  46. Saleheen, F.; Habib, M.M.; Hanafi, Z. Supply Chain Performance Measurement Model: A Literature Review. Int. J. Supply Chain Manag. 2018, 7, 70–78. [Google Scholar]
  47. Freitas, A.A.; Carvalho, A.C.P.F. A Tutorial on Hierarchical Classification with Applications in Bioinformatics. In Research and Trends in Data Mining Technologies and Applications; Taniar, D., Ed.; IGI Publishing: Hershey, PA, USA, 2007; pp. 176–209. [Google Scholar]
  48. Costa, E.P.; Lorena, A.C.; Carvalho, A.C.; Freitas, A.A. A Review of Performance Evaluation Measures for Hierarchical Classifiers. In Evaluation Methods for Machine Learning II: Papers from the AAAI-2007 Workshop; AAAI Press: Washington, DC, USA, 2007. [Google Scholar]
  49. Kamble, S.S.; Gunasekaran, A.; Ghadge, A.; Raut, R. A Performance Measurement System for Industry 4.0 Enabled Smart Manufacturing System in SMMEs: A Review and Empirical Investigation. Int. J. Prod. Econ. 2020, 229, 107853. [Google Scholar] [CrossRef]
  50. Gunasekaran, A.; Kobu, B. Performance Measures and Metrics in Logistics and Supply Chain Management: A Review of Recent Literature (1995–2004) for Research and Applications. Int. J. Prod. Res. 2007, 45, 2819–2840. [Google Scholar] [CrossRef]
  51. Yang, C.C.; Yang, K.J.; Yeh, T.M.; Pai, F.Y. Methods for Determining Areas for Improvement Based on the Design of Customer Surveys. Serv. Ind. J. 2009, 29, 143–154. [Google Scholar] [CrossRef]
  52. Delipinar, G.E.; Kocaoglu, B. Using SCOR Model to Gain Competitive Advantage: A Literature Review. Procedia Soc. Behav. Sci. 2016, 229, 398–406. [Google Scholar] [CrossRef]
  53. Trkman, P. The Impact of Business Analytics on Supply Chain Performance. Decis. Support Syst. 2010, 49, 318–327. [Google Scholar] [CrossRef]
  54. Lima-Junior, F.R.; Carpinetti, L.C.R. Predicting Supply Chain Performance Based on SCOR® Metrics and Multilayer Perceptron Neural Networks. Int. J. Prod. Econ. 2019, 212, 19–38. [Google Scholar] [CrossRef]
  55. Chehbi-Gamoura, S.; Derrouiche, R.; Damand, D.; Barth, M. Insights from Big Data Analytics in Supply Chain Management: An All-Inclusive Literature Review Using the SCOR Model. Prod. Plan. Control 2020, 31, 355–382. [Google Scholar] [CrossRef]
  56. Persson, F.; Araldi, M. The Development of a Dynamic Supply Chain Analysis Tool—Integration of SCOR and Discrete Event Simulation. Int. J. Prod. Econ. 2009, 121, 574–583. [Google Scholar] [CrossRef]
  57. Huang, S.H.; Uppal, M.; Shi, J. A product driven approach to manufacturing supply chain selection. Supply Chain. Manag. Int. J. 2002, 7, 189–199. [Google Scholar] [CrossRef]
Figure 1. The research processes.
Figure 1. The research processes.
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Figure 2. SCOR model Level 1. Source: SCC (2005) [12].
Figure 2. SCOR model Level 1. Source: SCC (2005) [12].
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Figure 4. Salangane nest product SC. Source: authors’ simulation, 2022.
Figure 4. Salangane nest product SC. Source: authors’ simulation, 2022.
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Figure 5. Order processing and planning. Source: Khanh Hoa Sanest Soft Drink Joint Stock Company.
Figure 5. Order processing and planning. Source: Khanh Hoa Sanest Soft Drink Joint Stock Company.
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Figure 6. Salangane nest product production process. Source: Khanh Hoa Sanest Soft Drink Joint Stock Company.
Figure 6. Salangane nest product production process. Source: Khanh Hoa Sanest Soft Drink Joint Stock Company.
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Figure 7. Revenue from salangane nest products for each market, 2017–2021. Source: authors’ calculations from company data, 2017–2021.
Figure 7. Revenue from salangane nest products for each market, 2017–2021. Source: authors’ calculations from company data, 2017–2021.
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Figure 8. Customer perceptions of product quality, product benefits, and brand awareness. Source: authors’ survey, 2021.
Figure 8. Customer perceptions of product quality, product benefits, and brand awareness. Source: authors’ survey, 2021.
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Figure 9. Customer perceptions of product packaging design, promotions, and prices. Source: authors’ survey, 2021.
Figure 9. Customer perceptions of product packaging design, promotions, and prices. Source: authors’ survey, 2021.
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Figure 10. Enterprise business system. Source: authors’ simulation, 2022.
Figure 10. Enterprise business system. Source: authors’ simulation, 2022.
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Figure 11. Electronic data interchange. Source: authors’ simulation, 2022.
Figure 11. Electronic data interchange. Source: authors’ simulation, 2022.
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Figure 12. Point of sale data exchange. Source: authors’ simulation, 2022.
Figure 12. Point of sale data exchange. Source: authors’ simulation, 2022.
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Table 1. SCOR Level 1 model metrics and performance measurements.
Table 1. SCOR Level 1 model metrics and performance measurements.
Performance AttributesDefinitionLevel 1 Metric
Customer-facingReliabilityThe performance of the supply chain in delivering: the correct product, to the correct place, at the correct time, in the correct condition and packaging, in the correct quantity, with the correct documentation, to the correct customer.Delivery performance
Fill rates
Perfect order fulfillment
ResponsivenessThe velocity at which a supply chain provides products to the customer.Order fulfillment lead time
AgilityThe agility of a supply chain in responding to marketplace changes to gain or maintain competitive advantage.Supply chain response time
Production flexibility
Internal facingCostsThe costs associated with operating the supply chain.Cost of goods sold
Total supply chain
management costs
AssetsThe effectiveness of an organization in managing assets to support demand satisfaction. This includes the management of all assets: fixed and working capital.Cash-to-cash cycle time
Inventory days of supply
Asset turns
Source: SCC, 2005. [36].
Table 2. The packaging cost of defective products 2017–2021.
Table 2. The packaging cost of defective products 2017–2021.
Code20172018201920202021
Defective ProductsPackaging Cost (USD)Defective ProductsPackaging Cost (USD)Defective ProductsPackaging Cost (USD)Defective ProductsPackaging Cost (USD)Defective ProductsPackaging Cost (USD)
00220736.0519734.0018831.8820735.1520334.71
02917630.6816828.9416027.1317629.9117229.54
70035862.3234158.7832555.1235860.7635060.01
77039769.0337865.1136061.0539667.3038866.47
09511630.2611028.5410526.7611629.5011329.14
096112.88112.72102.55112.81112.78
0056110.55589.95559.336110.285910.16
016113836.0213133.9812531.8613835.1213534.69
Total1464277.781394262.021328245.691461270.841432267.49
Source: authors’ calculations from company aggregate data, 2017–2021.
Table 3. Supply chain performance metrics Level 1 during 2017–2021.
Table 3. Supply chain performance metrics Level 1 during 2017–2021.
Customer-facingOverview MetricsSCOR Level 1 MetricsUnitActualComments
Supply chain reliabilityDelivery performance to commit date%100The company can delivery all orders from customers (distributors) because of modern equipment machines, materials inventory, and the large plant’s capacity (see Appendix A)
Fill rates%100
ResponsivenessOrder fulfillment lead timesDays/hours
Manufacturing lead timedays11The time it takes to produce is 24 h. For safety and quality, before being accessed to the market, the products are kept in a refrigerated warehouse for 7–10 days to check microbiology and technical quality criteria.
FlexibilitySupply chain response timeday
Order fulfillment delivery lead times to Da Nang marketdays11 + 2
Order fulfillment delivery lead times to HCM City marketdays11 + 2
Order fulfillment delivery lead times to Hanoi marketdays11 + 3.5
Order fulfillment delivery lead times at Khanh Hoa markethours11 + 5
Production flexibilitydaysNAThe demand suddenly increases at the end of the quarter, end of the year, Lunar New Year, and back of the promotion program. This is the safety inventory demand of distributors or agents, not the consumer’s reality need. Due to the large plant’s capacity of two factories, the company always supplies enough products.
Internal-facingCostTotal SCM management costs%
Cost of goods sold%75.29Appendix A
Production costs%41.99
AssetsInventory days of supplydays28.81Appendix A
Cash-to-cash cycle timedays43.81Including 28.81 days of inventory and 15 accounts receivable days
Net asset turns (working capital)turn100.54Appendix A
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Nguyen, T.A.T.; Nguyen, T.L.; Nguyen, Q.T.T.; Nguyen, K.A.T.; Jolly, C.M. Measuring Supply Chain Performance for Khanh Hoa Sanest Soft Drink Joint Stock Company: An Application of the Supply Chain Operations Reference (SCOR) Model. Sustainability 2023, 15, 16057. https://doi.org/10.3390/su152216057

AMA Style

Nguyen TAT, Nguyen TL, Nguyen QTT, Nguyen KAT, Jolly CM. Measuring Supply Chain Performance for Khanh Hoa Sanest Soft Drink Joint Stock Company: An Application of the Supply Chain Operations Reference (SCOR) Model. Sustainability. 2023; 15(22):16057. https://doi.org/10.3390/su152216057

Chicago/Turabian Style

Nguyen, Tram Anh Thi, Thuy Lan Nguyen, Quynh Trang Thi Nguyen, Kim Anh Thi Nguyen, and Curtis M. Jolly. 2023. "Measuring Supply Chain Performance for Khanh Hoa Sanest Soft Drink Joint Stock Company: An Application of the Supply Chain Operations Reference (SCOR) Model" Sustainability 15, no. 22: 16057. https://doi.org/10.3390/su152216057

APA Style

Nguyen, T. A. T., Nguyen, T. L., Nguyen, Q. T. T., Nguyen, K. A. T., & Jolly, C. M. (2023). Measuring Supply Chain Performance for Khanh Hoa Sanest Soft Drink Joint Stock Company: An Application of the Supply Chain Operations Reference (SCOR) Model. Sustainability, 15(22), 16057. https://doi.org/10.3390/su152216057

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