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An Application of the Negative Malmquist Model for Vietnamese Garment and Textiles Industry

An Application of the Negative Malmquist Model for Vietnamese Garment and Textiles Industry The study purpose is to measure the performance of the Vietnamese garment and textiles industry by means of the Negative Malmquist model using the data envelopment analysis (DEA) method. The empirical results pre- sented the efficient, inefficient cases, and average efficiency for all garment and textile companies in Vietnam during from 2016 to 2020. The main findings determined that five companies, including HTG, TET, MSH, M10, and BDG possessed efficiency scores in whole terms. An overall picture of the garment and textiles industry in Vietnam is used to evaluate the operational process. The research recommends a feasible alternative method to deal with inefficient cases. Key words: negative malmquist model, data envelopment analysis, garment and textile company, efficiency INTRODUCTION On the contrary, economic development had fostered the Significant improvements in regional economy and social development of the garment and textiles industry before development are fundamental strengths necessary to boost the COVID-19 pandemic. Access to the World Trade Organi- the growth rate of the garment and textiles industry. This is zation helped the Chinese garment industry to develop rap- as true worldwide as it is in Vietnam. The Vietnamese econ- idly [4]. From a competitive context, social influences, and omy has grown rapidly since 1987, after adopting an open- an overall understanding of corporate social responsibility door policy and integrating global market into local affairs. have been major impact factors for the Vietnamese garment Thus, many industries have benefit-ted to develop and ex- and textiles industry [5], and it has achieved considerable pand the manufacturing sector with various product offer- worth since joining the World Trade Organization in 2007. ings; whereas, Vietnam’s garment and textiles industry To effectively assess the performance of the Vietnamese grew continuously, with an average rate of 17 percent, from garment and textiles industry, the study used the negative 2015 to 2019; additionally, it also contributed to the gross Malmquist model in DEA to evaluate garment and textiles domestic product of 16 percent in 2019. However, the im- companies located in Vietnam. pact of the COVID-19 pandemic from 2020 until present has The negative Malmquist model is proposed to calculate the decreased sharply, the total exports of 2020 were been efficiency of the Vietnamese garment and textiles compa- down 3.8 percent compared to the year of 2019 [1]. Total nies because this model can deal with the presence of nega- exports depend on international markets such as the Euro- tive data. Additionally, it can present the unlimited efficien- cy score with effective terms of decision-making units pean Union, North America, China, etc. because they pos- (DMU) in which determines separate efficiency in every sess a large import scale and stable markets to simultane- term of each DMU. In this study, the collected data of 10 ously boost domestic employment and export trade growth garment and textiles companies in Vietnam from 2016 to [2]. From the year of 2019, the COVID-19 pandemic has 2020 contained both negative values and positive values [6]; impacted the garment and textiles industry in Vietnam di- thus, we selected the negative Malmquist model to solve rectly and subsequently reduced the amount of total ex- the negative values and escalate the efficiency score. ports. Besides, the eco-nomic crisis was responsible for the sharp decline in the export quantity of the garment and textile industry [3]. T.K.L. NGUYEN et al. – An Application of the Negative Malmquist Model… Charnes-Cooper-Rhodes (CCR) model, Slacks-Based Meas- The empirical results revealed the operational process, ure (SBM) model, and epsilon-based measure (EBM) model which described the growth progress be-fore the COVID-19 are used to measure the performance for DMU by the ratio pandemic, then decreased in the year 2020 due in most between inputs and outputs [13, 14, 15]; however, these part on account of the COVID-19 pandemic. Additionally, models still exist the input and output limitations when they the study discussed a feasible solution to solve the ineffi- require the positive input and output values for each DMU cient terms and growth directions for the future. The empir- [16]. ical analysis process described full particularly acknowl- The Malmquist model is a combined index to measure the edgement of garment and textiles companies in Vietnam. productivity change of a DMU over time. It has been ap- The paper is arranged, as follows: plied in various economic aspects, including manufacturing Section 1 – general of the garment and textiles industry in [17], energy [18], transportation [19], and education [20]. Vietnam and research purpose; These papers investigated productivity performance with Section 2 – literature review constituting past studies of the positive data; further, others studies have covered the garment and textiles industry, coupled with the negative productivity index with the presence of negative data. Malmquist model; Portela et al., [21] indicated the productivity change of bank Section 3 – mathematical equations offered by the negative branches with the presence of negative data. Tohidi et al., Malmquist model and source of the raw data; [22] gave an illustration of the Malmquist model in the Section 4 – empirical results; presence of negative data. The extendedness of the Section 5 – primary findings and related values; Malmquist model can deal with the negative data when a Section 6 – main results, limitations, and possibility for fu- DMU exists with negative values, therefore the negative ture research. Malmquist model was employed to measure the efficiency of the Vietnamese garment and textiles industry. LITERATURE REVIEW The term “textile” is a primary period of the design, pro- MATERIALS AND METHODS duction, and distribution of yarn, cloth, and clothing, the Data Collection raw materials include natural and synthetic. The term “gar- The Vietnamese garment and textiles industry includes 3 ment” is sequential processes including laying, marking, subsectors, including an up-stream sector (fiber produc- cutting, stitching, checking, finishing, pressing, and packag- tion), a mid-stream sector (fabric production and dyeing), ing to convert raw materials into finished goods [7]. The and a down-stream sector (garment manufacturing). The garment and textile industry is formulated and developed main components of the garment and textile industry are around the world to supply the human’s demand of fashion. cotton, synthetic fibers, wool yarn, synthetic and natural To have a general information of the garment and textile filaments, and silk. To evaluate the garment and textile industry, many researchers surveyed and analyzed this in- companies in Vietnam, the past operating progress of se- dustry under different sides. lected companies has been evaluated. To this end, the In the previous studies of the garment and textile industry, study chose 10 Vietnamese garment and textiles companies several authors used various approaches. Joshi and Singh located in Vietstock (2021) [6] (see Table 1). measured the Indian garment industry via the Malmquist Analysing the effect of operating progress requires having Productivity Index without the presence of negative data complete and exact information related to financial re-ports [8]. Lenzo et al., applied the Social Life Cycle Assessment to to derive the actual value of input variables and out-put evaluate Italian textile production [9]. Le et al., explored variables. Ten garment and textiles companies, operating perceived impacts on the garment and textiles industry of during the period of 2016-2020, were observed ac-cording Vietnam from China’s Belt and Road Initiative when apply- to their financial report posting in Vietstock (2020) [6]. ing both desk and in-depth interviews with 54 leaders and Based on the principle of the negative Malmquist model in high-ranking officials [10]. Zhao et al., analyzed the primary DEA, the quantity of input variables, as well as the quantity factors that effected the Chinese garment and textiles in of output variables, indicated they could not overcome the order to define the target market of the garment and tex- total DMU’s. Hence, three input factors were chosen, in- tiles export trade through Analytical Hierarchy Process [11]. cluding current assets (CA), non-current assets (NA), and Wang et al., integrated three models, including supply chain owner's equity (OE); and, two output factors, including rev- operations reference, analytical network process, and fuzzy enue (RE), and net profit after tax (NP), were also selected. analytical hierarchy process in the multi-criteria decision- making model (MCDM) for garment and textile supplier selection [12]. In this study, we utilized the negative Malmquist model in the DEA method with the presence of negative data to evaluate the performance of 10 Vietnam- ese garment and textiles companies. DEA has been developed and applied in performance as- sessment for more than 40 years, up to now it has various models with different characteristics. 76 Management Systems in Production Engineering 2022, Volume 30, Issue 1 Table 1 t+1 t+1 t+1 DF (x , y ) List of 10 garment and textiles companies in Vietnam 0 0 0 CUI = (1) t t t No. Garment and textile companies Abbreviation DF (x , y ) 0 0 0 Ha Noi Textile and Garment Joint Stock 1 HSM Second, calculating the Frontier-Shift effect (FSI): Corporation 1/2 Hoa Tho Textile & Garment Joint Stock t t t t t++ 11 t 2 HTG  DF (x , y ) DF (x , y ) 0 0 0 0 0 0 Corporation FSI= (2)  t+1 t t t+1 t+1 t+1 DF (x , y ) DF (x , y )  0 0 0 0 0 0 Thanh Cong Textile Garment Invest- 3 TCM ment Trading Joint Stock Company Third, conducting the Malmquist Productivity Index (MPI): Northern Textiles & Garments Joint 4 TET 1/2 Stock Company t t+1 t+1 t+1 t+1 t+1  DF (x , y ) DF (x , y ) 0 0 0 0 0 0 MPI= (3) Nam Dinh Textile Garment Joint Stock  t t t t+1 t t 5 NDT DF (x , y ) DF (x , y )  0 0 0 0 0 0 Corporation Song Hong Garment Joint Stock If the score of the MPI is lower than the number “one”, the 6 MSH Company company is considered not to have attained the efficiency Vietnam National Textile & Garment score. On the contrary, if the score of the MPI is equal to or 7 VTG Group higher than the number “one”, the company obtains an effi- Garmant 10 Corporation – Joint Stock ciency score. In this study, the MPI is integrated into the 8 M10 Company super-efficiency mode so that it exhibits the differential effi- Pro-trade Garment Joint Stock ciency scores in efficient cases versus non-efficient cases. 9 BDG Company Nha Trang Textile Garment Joint Stock EMPIRICAL RESULTS 10 NTT Company Data analysis Source: Vietstock (2021) [6] Based on a given list of 10 Vietnamese garment and textiles companies in Table 2, input and output variables have been Input factors: selected and then summarized, as shown in Table 3. The CA: The value of current assets that are sold, consumed, maximum value of CA, NA, OE, RE, and NP during the period used, and exhausted in one year’s time through standard of 2016-2020 attained as 10547264; 11431177; 7996099; business operations. 19101466; and 716338, respectively. The minimum value of NA: The value of current assets that are invested on a long- CA, NA, OE, RE, and NP during the period from 2016 to 2020 term basis. was 17459; 40355; 68452; 22683; and – 32216, respectively. OE: All of the money a securities company must pay-off in These values indicated that all input and output values were the event of liquidation. suitable for inclusion into the negative Malmquist model in the DEA method. Output factors: RE: All of the money that the garment and textile company Table 2 receive from its business activities in which there has been Summary of the collected data no deduction of operating charges and taxes. Varia- Year CA NA OE RE NP NP: The entire profitability of a garment and textiles com- bles pany after deduction of interest and taxes. Max 9232273 10562150 7594471 15461521 579322 From the actual data posted to Vietstock (2021) [6], the Min 17459 57242 68452 40100 3620 output variable of NP appeared to contain negative values. Average 2016 1595229 1653801 1093226 3295741 118428 Thus, the negative Malmquist model in DEA with the func- SD 2578018 3004474 2180937 4188192 161296 tion of dealing with the presence of negative data was con- Max 9474983 11431177 7821312 17446544 685174 sidered to be particularly well-equipped to calculate gar- Min 37720 54202 88099 36410 3 ment and textile companies’ efficiency. Average 2017 1721265 1748913 1158681 3636986 140334 SD 2631868 3257579 2238410 4757840 192315 Negative Malmquist Model Max 10547264 11347597 7996099 19101466 702616 DEA is a useful statistical method utilized in operations re- Min 55745 49218 97963 38858 -32216 search and economics for the estimation of a production Average 2018 1941302 1729456 1236720 3998175 166536 frontier to assess the efficiency of DMU’s. It uses a non- SD 2924725 3231628 2279705 5217173 213106 parametric method of benchmarking to measure the effi- Max 9341107 10492424 7939649 18986006 716338 ciency of operational research. According to the common Min 30699 69475 94070 24855 -30385 principle of DEA, the efficiency of a DMU may be defined as 2019 Average 1723255 1620488 1274096 4078121 162867 the given ratio between outputs and inputs, where the SD 2600143 2984311 2262577 5164293 229542 Malmquist model presents the performance change in a Max 7433840 10227028 7855136 13972471 569448 Min 66178 40355 100159 22683 -25470 Decision-Making Unit (DMU) between two consecutive Average 1532530 1558297 1305076 3246324 128814 terms (Tone, 2004) [23]. In this study, the Malmquist model SD 2050667 2913509 2241676 3795720 174731 was used with the presence of negative data for measuring Source: Vietstock (2021) [6]. the efficiency of Vietnamese garment and textiles compa- nies from 2016 to 2020. First, estimating the Catch-Up effect (CUI): T. K. L. NGUYEN et al. – An Application of the Negative Malmquist Model… scores of the Vietnamese garment and textiles companies Table 3 from 2016 to 2020 was conducted (see Table 4). Pearson’s correlation coefficient Variables Year CA NA OE RE NP Table 4 CA 1.0000 0.9937 0.9960 0.9926 0.9805 Efficiency of 10 Vietnamese garment and textiles companies NA 0.9937 1.0000 0.9975 0.9808 0.9637 DMUs 2016 2017 2018 2019 2020 Average OE 2016 0.9960 0.9975 1.0000 0.9814 0.9719 HSM 0.4222 0.4819 0.4144 0.4550 0.3277 0.4202 HTG 1.0657 1.5185 2.0970 1.9527 1.0750 1.5418 RE 0.9926 0.9808 0.9814 1.0000 0.9765 TCM 0.6234 0.9178 1.1473 1.1119 1.3590 1.0319 NP 0.9805 0.9637 0.9719 0.9765 1.0000 TET 8.8384 7.2995 6.2561 6.6120 5.2791 6.8570 CA 1.0000 0.9904 0.9961 0.9923 0.9823 NDT 0.3943 0.3740 0.4006 0.4904 0.5163 0.4351 NA 0.9904 1.0000 0.9951 0.9779 0.9578 MSH 2.4663 2.2255 8.0508 16.2945 2.7867 6.3648 VGT 1.0000 1.0508 1.0395 1.0395 0.9093 1.0078 OE 2017 0.9961 0.9951 1.0000 0.9828 0.9744 M10 1.4858 1.2862 1.0444 1.2247 1.5275 1.3137 RE 0.9923 0.9779 0.9828 1.0000 0.9695 BDG 2.0869 2.1763 2.3327 2.4530 2.5412 2.3180 NP 0.9823 0.9578 0.9744 0.9695 1.0000 NTT 0.5354 0.4824 0.5004 0.7971 0.7987 0.6228 CA 1.0000 0.9913 0.9971 0.9915 0.9073 Average 1.8918 1.7813 2.3283 3.2431 1.7121 2.1913 Max 8.8384 7.2995 8.0508 16.2945 5.2791 6.8570 NA 0.9913 1.0000 0.9941 0.9777 0.8534 Min 0.3943 0.3740 0.4006 0.4550 0.3277 0.4202 OE 2018 0.9971 0.9941 1.0000 0.9832 0.8982 SD 2.5411 2.0481 2.6594 4.9305 1.4891 2.3996 RE 0.9915 0.9777 0.9832 1.0000 0.9061 NP 0.9073 0.8534 0.8982 0.9061 1.0000 Observing Table 4, there were five companies, including CA 1.0000 0.9838 0.9963 0.9926 0.8933 HTG, TET, MSH, M10, and BDG with scores under the num- NA 0.9838 1.0000 0.9887 0.9729 0.8099 ber one and that always achieved efficiency in whole terms; although their scores experienced large-scale annual fluctu- OE 2019 0.9963 0.9887 1.0000 0.9834 0.8818 ations. The efficiency scores of MSH reduced somewhat RE 0.9926 0.9729 0.9834 1.0000 0.8902 from 2.4663 in 2016 to 2.2255 in 2017, then they increased NP 0.8933 0.8099 0.8818 0.8902 1.0000 sharply for the next two years, with scores as 8.0508 (2018) CA 1.0000 0.9720 0.9935 0.9916 0.9442 and 16.2945 (2019), and continuously dropped in the year NA 0.9720 1.0000 0.9849 0.9560 0.8631 2020. TET maintained a downward trend year-to-year ex- OE 2020 0.9935 0.9849 1.0000 0.9740 0.9345 cept for rising slightly from 6.2561 (2018) to 6.612 (2019). The performance of M10 declined for three consecutive RE 0.9916 0.9560 0.9740 1.0000 0.9268 years, and then increased the following two consecutive NP 0.9442 0.8631 0.9345 0.9268 1.0000 years; on the contrary, HTG enjoyed an upward trend within three consecutive years and then suffered a downturn for According to the principle of the DEA method, the collected the next two consecutive years. Minor score fluctuations data must be checked using Pearson’s correlation coeffi- occurred from 2.0869 to 2.5412, so that BDG was the only cient to ensure the appropriate relationship be-tween input company to obtain efficiency with an upward trend for the and inputs; output and output; and, input and output exist entire term. TCM and VGT experienced both efficiency and before their application into the DEA method. The relation- inefficiency; whereas TCM increased continually except for ship between two variables is always isotonic with the value reducing efficiency in the year 2019. VGT had two inefficient exhibited from -1 to +1, it has a perfect linear relationship years and three efficient years; so, VGT had only one up- as near to ±1, a strong correlation as near to ±0.5 and ±0.8, ward-trending term from 1 (2016) to 1.0508 (2017), then a medium correlation as near to ±0.3 and ±0.49, and a low declined consecutively; but it still obtained efficiency in four correlation occurs when lower than ±0.29 [24]. All variables consecutive years from 2016 to 2019. Finally, the three re- with unqualified Pear-son’s correlation are to be removed maining companies, including HSM, NDT, and NTT did not prior to summarization. In this research, the Pearson’s cor- achieve efficiency in whole terms despite their scores show- relations of the 10 Vietnamese garment and textiles com- ing an upward trend. panies maintained variables with values from 0.8099 to 1, In addition, the negative Malmquist model presented the so they are said to have a good linear relationship. There- average score for all garment and textiles companies based fore, all collected data were appreciable in order to apply to on their scores year-to-year. TET had the highest average the negative Malmquist model in the DEA method. efficiency score when it achieved the average score of 6.8570; in contrast, HSM had the lowest average efficiency Measurement of performance score when its score was 0.4202. Besides, this model also In recent years, the garment and textiles industry of Vi- determined the average, maximum and mini-mum scores etnam has developed markedly. The negative Malmquist occurring in each year. The average score for the year 2019 model not only deals with negative data but also provides held the highest valuation, but the influence of the COVID- separate scores for each DMU in each of the years ob- 19 pandemic impacted the average score for the year 2020 served. In this research, a determination of the efficiency to have the lowest valuation. 78 Management Systems in Production Engineering 2022, Volume 30, Issue 1 Additionally, the year of 2019 held the highest efficiency development activities, technology transfers, and product score and the year 2020 had the lowest efficiency score for innovation. both maximum scores and minimum scores present. CONCLUSIONS DICUSSIONS The Vietnamese garment and textiles industry presents a Vietnam is one of the nations in the world where the ex- marked variation in its operational performance from 2016 to 2020, as conducted by the negative Malmquist model. port value of the garment and textiles industry always The empirical results of this modelling exhibited a separate achieves a large valuation. Statistics (2021) have indicated efficiency score every year and an average efficiency score that the total export value in the garment and textiles in- for the period of 2016-2020; moreover, the study revealed dustry in Vietnam increased consecutively from 24.7 billion the considerable impact of the COVID-19 pandemic for the USD to 39 billion USD during 2014 to 2019; however, the garment and textiles industry in Vietnam. COVID-19 pandemic impacted directly on the market-place The study exhibited the process of business operations and and caused a recession while reducing the total export val- improved efficiency score for the Vietnamese garment and ue 35.2 billion USD in 2020 (See Figure 1). Therefore, the textiles industry. Analytic results determined efficient and garment and textiles industry in Vietnam experienced inefficient cases for 10 companies. Such measurement is growth before the COVID-19 outbreak influenced Vietnam, fundamental to the support of enterprises by identifying the region, and globally. The total export values for the year their capable operations to extend improved operational 2020 declined sharply so that the effective operation of the performance in the near future. The main findings contrib- garment and textiles companies in Vietnam dropped sharp- ute to maintaining and developing a sustainable efficient ly with the average efficiency score from 3.2431 in 2019 to garment and textiles industry in Vietnam. This industry con- 1.7121 in 2020. tributes considerably to the GDP, and it will provide an ef- fective operational orientation in the future. Although the study uniquely concerned the performance of the garment and textiles companies in Vietnam, there are still limitations existing. Future research is necessary to compare the Vietnamese garment and textiles industry with other nations in order to have a larger overview of the glob- al garment and textiles industry and to make a comparison for the growing region. Further study has the possibility to give more inputs and outputs such as costs of manufactur- ing, employee, and so on to insure a deeper observation. REFERENCES Fig. 1 Total export value of Vietnamese textiles and garments [1] T. Nguyen. Seizing Investment Opportunities in Vietnam’s from 2014 to 2020 (billion USD) Garment and Textile Industry. Vietnam Briefing. 2020. Source: Statistics (2021) [25]. Available online: https://www.vietnam-brief- ing.com/news/seizing-investment-opportunities-vi- The above analysis results, as shown in Table 4, present 50 etnams-textile-garment-industry.html/ [April 5, 2021]. scores; whereas, there were 32 efficient cases and 18 ineffi- [2] J.N. Zhao, J. Li, and L.T. Li. “An Analysis on the Target cient cases. 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Thi Kim Lien Nguyen Thanh Dong University Scientific Research-International Cooperation Hai Duong 171967, Vietnam e-mail: lienntk@thanhdong.edu.vn Xuan-Huynh Nguyen (Corresponding author) Hanoi School of Business & Management Vietnam National University Hanoi 100000, Vietnam e-mail: huynhnx@hsb.edu.vn Hong V. Pham Vietnam Institution of Science Technology and Innovation Hanoi, 100000, Vietnam e-mail: phamvanhong1973@gmail.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Management Systems in Production Engineering de Gruyter

An Application of the Negative Malmquist Model for Vietnamese Garment and Textiles Industry

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de Gruyter
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Abstract

The study purpose is to measure the performance of the Vietnamese garment and textiles industry by means of the Negative Malmquist model using the data envelopment analysis (DEA) method. The empirical results pre- sented the efficient, inefficient cases, and average efficiency for all garment and textile companies in Vietnam during from 2016 to 2020. The main findings determined that five companies, including HTG, TET, MSH, M10, and BDG possessed efficiency scores in whole terms. An overall picture of the garment and textiles industry in Vietnam is used to evaluate the operational process. The research recommends a feasible alternative method to deal with inefficient cases. Key words: negative malmquist model, data envelopment analysis, garment and textile company, efficiency INTRODUCTION On the contrary, economic development had fostered the Significant improvements in regional economy and social development of the garment and textiles industry before development are fundamental strengths necessary to boost the COVID-19 pandemic. Access to the World Trade Organi- the growth rate of the garment and textiles industry. This is zation helped the Chinese garment industry to develop rap- as true worldwide as it is in Vietnam. The Vietnamese econ- idly [4]. From a competitive context, social influences, and omy has grown rapidly since 1987, after adopting an open- an overall understanding of corporate social responsibility door policy and integrating global market into local affairs. have been major impact factors for the Vietnamese garment Thus, many industries have benefit-ted to develop and ex- and textiles industry [5], and it has achieved considerable pand the manufacturing sector with various product offer- worth since joining the World Trade Organization in 2007. ings; whereas, Vietnam’s garment and textiles industry To effectively assess the performance of the Vietnamese grew continuously, with an average rate of 17 percent, from garment and textiles industry, the study used the negative 2015 to 2019; additionally, it also contributed to the gross Malmquist model in DEA to evaluate garment and textiles domestic product of 16 percent in 2019. However, the im- companies located in Vietnam. pact of the COVID-19 pandemic from 2020 until present has The negative Malmquist model is proposed to calculate the decreased sharply, the total exports of 2020 were been efficiency of the Vietnamese garment and textiles compa- down 3.8 percent compared to the year of 2019 [1]. Total nies because this model can deal with the presence of nega- exports depend on international markets such as the Euro- tive data. Additionally, it can present the unlimited efficien- cy score with effective terms of decision-making units pean Union, North America, China, etc. because they pos- (DMU) in which determines separate efficiency in every sess a large import scale and stable markets to simultane- term of each DMU. In this study, the collected data of 10 ously boost domestic employment and export trade growth garment and textiles companies in Vietnam from 2016 to [2]. From the year of 2019, the COVID-19 pandemic has 2020 contained both negative values and positive values [6]; impacted the garment and textiles industry in Vietnam di- thus, we selected the negative Malmquist model to solve rectly and subsequently reduced the amount of total ex- the negative values and escalate the efficiency score. ports. Besides, the eco-nomic crisis was responsible for the sharp decline in the export quantity of the garment and textile industry [3]. T.K.L. NGUYEN et al. – An Application of the Negative Malmquist Model… Charnes-Cooper-Rhodes (CCR) model, Slacks-Based Meas- The empirical results revealed the operational process, ure (SBM) model, and epsilon-based measure (EBM) model which described the growth progress be-fore the COVID-19 are used to measure the performance for DMU by the ratio pandemic, then decreased in the year 2020 due in most between inputs and outputs [13, 14, 15]; however, these part on account of the COVID-19 pandemic. Additionally, models still exist the input and output limitations when they the study discussed a feasible solution to solve the ineffi- require the positive input and output values for each DMU cient terms and growth directions for the future. The empir- [16]. ical analysis process described full particularly acknowl- The Malmquist model is a combined index to measure the edgement of garment and textiles companies in Vietnam. productivity change of a DMU over time. It has been ap- The paper is arranged, as follows: plied in various economic aspects, including manufacturing Section 1 – general of the garment and textiles industry in [17], energy [18], transportation [19], and education [20]. Vietnam and research purpose; These papers investigated productivity performance with Section 2 – literature review constituting past studies of the positive data; further, others studies have covered the garment and textiles industry, coupled with the negative productivity index with the presence of negative data. Malmquist model; Portela et al., [21] indicated the productivity change of bank Section 3 – mathematical equations offered by the negative branches with the presence of negative data. Tohidi et al., Malmquist model and source of the raw data; [22] gave an illustration of the Malmquist model in the Section 4 – empirical results; presence of negative data. The extendedness of the Section 5 – primary findings and related values; Malmquist model can deal with the negative data when a Section 6 – main results, limitations, and possibility for fu- DMU exists with negative values, therefore the negative ture research. Malmquist model was employed to measure the efficiency of the Vietnamese garment and textiles industry. LITERATURE REVIEW The term “textile” is a primary period of the design, pro- MATERIALS AND METHODS duction, and distribution of yarn, cloth, and clothing, the Data Collection raw materials include natural and synthetic. The term “gar- The Vietnamese garment and textiles industry includes 3 ment” is sequential processes including laying, marking, subsectors, including an up-stream sector (fiber produc- cutting, stitching, checking, finishing, pressing, and packag- tion), a mid-stream sector (fabric production and dyeing), ing to convert raw materials into finished goods [7]. The and a down-stream sector (garment manufacturing). The garment and textile industry is formulated and developed main components of the garment and textile industry are around the world to supply the human’s demand of fashion. cotton, synthetic fibers, wool yarn, synthetic and natural To have a general information of the garment and textile filaments, and silk. To evaluate the garment and textile industry, many researchers surveyed and analyzed this in- companies in Vietnam, the past operating progress of se- dustry under different sides. lected companies has been evaluated. To this end, the In the previous studies of the garment and textile industry, study chose 10 Vietnamese garment and textiles companies several authors used various approaches. Joshi and Singh located in Vietstock (2021) [6] (see Table 1). measured the Indian garment industry via the Malmquist Analysing the effect of operating progress requires having Productivity Index without the presence of negative data complete and exact information related to financial re-ports [8]. Lenzo et al., applied the Social Life Cycle Assessment to to derive the actual value of input variables and out-put evaluate Italian textile production [9]. Le et al., explored variables. Ten garment and textiles companies, operating perceived impacts on the garment and textiles industry of during the period of 2016-2020, were observed ac-cording Vietnam from China’s Belt and Road Initiative when apply- to their financial report posting in Vietstock (2020) [6]. ing both desk and in-depth interviews with 54 leaders and Based on the principle of the negative Malmquist model in high-ranking officials [10]. Zhao et al., analyzed the primary DEA, the quantity of input variables, as well as the quantity factors that effected the Chinese garment and textiles in of output variables, indicated they could not overcome the order to define the target market of the garment and tex- total DMU’s. Hence, three input factors were chosen, in- tiles export trade through Analytical Hierarchy Process [11]. cluding current assets (CA), non-current assets (NA), and Wang et al., integrated three models, including supply chain owner's equity (OE); and, two output factors, including rev- operations reference, analytical network process, and fuzzy enue (RE), and net profit after tax (NP), were also selected. analytical hierarchy process in the multi-criteria decision- making model (MCDM) for garment and textile supplier selection [12]. In this study, we utilized the negative Malmquist model in the DEA method with the presence of negative data to evaluate the performance of 10 Vietnam- ese garment and textiles companies. DEA has been developed and applied in performance as- sessment for more than 40 years, up to now it has various models with different characteristics. 76 Management Systems in Production Engineering 2022, Volume 30, Issue 1 Table 1 t+1 t+1 t+1 DF (x , y ) List of 10 garment and textiles companies in Vietnam 0 0 0 CUI = (1) t t t No. Garment and textile companies Abbreviation DF (x , y ) 0 0 0 Ha Noi Textile and Garment Joint Stock 1 HSM Second, calculating the Frontier-Shift effect (FSI): Corporation 1/2 Hoa Tho Textile & Garment Joint Stock t t t t t++ 11 t 2 HTG  DF (x , y ) DF (x , y ) 0 0 0 0 0 0 Corporation FSI= (2)  t+1 t t t+1 t+1 t+1 DF (x , y ) DF (x , y )  0 0 0 0 0 0 Thanh Cong Textile Garment Invest- 3 TCM ment Trading Joint Stock Company Third, conducting the Malmquist Productivity Index (MPI): Northern Textiles & Garments Joint 4 TET 1/2 Stock Company t t+1 t+1 t+1 t+1 t+1  DF (x , y ) DF (x , y ) 0 0 0 0 0 0 MPI= (3) Nam Dinh Textile Garment Joint Stock  t t t t+1 t t 5 NDT DF (x , y ) DF (x , y )  0 0 0 0 0 0 Corporation Song Hong Garment Joint Stock If the score of the MPI is lower than the number “one”, the 6 MSH Company company is considered not to have attained the efficiency Vietnam National Textile & Garment score. On the contrary, if the score of the MPI is equal to or 7 VTG Group higher than the number “one”, the company obtains an effi- Garmant 10 Corporation – Joint Stock ciency score. In this study, the MPI is integrated into the 8 M10 Company super-efficiency mode so that it exhibits the differential effi- Pro-trade Garment Joint Stock ciency scores in efficient cases versus non-efficient cases. 9 BDG Company Nha Trang Textile Garment Joint Stock EMPIRICAL RESULTS 10 NTT Company Data analysis Source: Vietstock (2021) [6] Based on a given list of 10 Vietnamese garment and textiles companies in Table 2, input and output variables have been Input factors: selected and then summarized, as shown in Table 3. The CA: The value of current assets that are sold, consumed, maximum value of CA, NA, OE, RE, and NP during the period used, and exhausted in one year’s time through standard of 2016-2020 attained as 10547264; 11431177; 7996099; business operations. 19101466; and 716338, respectively. The minimum value of NA: The value of current assets that are invested on a long- CA, NA, OE, RE, and NP during the period from 2016 to 2020 term basis. was 17459; 40355; 68452; 22683; and – 32216, respectively. OE: All of the money a securities company must pay-off in These values indicated that all input and output values were the event of liquidation. suitable for inclusion into the negative Malmquist model in the DEA method. Output factors: RE: All of the money that the garment and textile company Table 2 receive from its business activities in which there has been Summary of the collected data no deduction of operating charges and taxes. Varia- Year CA NA OE RE NP NP: The entire profitability of a garment and textiles com- bles pany after deduction of interest and taxes. Max 9232273 10562150 7594471 15461521 579322 From the actual data posted to Vietstock (2021) [6], the Min 17459 57242 68452 40100 3620 output variable of NP appeared to contain negative values. Average 2016 1595229 1653801 1093226 3295741 118428 Thus, the negative Malmquist model in DEA with the func- SD 2578018 3004474 2180937 4188192 161296 tion of dealing with the presence of negative data was con- Max 9474983 11431177 7821312 17446544 685174 sidered to be particularly well-equipped to calculate gar- Min 37720 54202 88099 36410 3 ment and textile companies’ efficiency. Average 2017 1721265 1748913 1158681 3636986 140334 SD 2631868 3257579 2238410 4757840 192315 Negative Malmquist Model Max 10547264 11347597 7996099 19101466 702616 DEA is a useful statistical method utilized in operations re- Min 55745 49218 97963 38858 -32216 search and economics for the estimation of a production Average 2018 1941302 1729456 1236720 3998175 166536 frontier to assess the efficiency of DMU’s. It uses a non- SD 2924725 3231628 2279705 5217173 213106 parametric method of benchmarking to measure the effi- Max 9341107 10492424 7939649 18986006 716338 ciency of operational research. According to the common Min 30699 69475 94070 24855 -30385 principle of DEA, the efficiency of a DMU may be defined as 2019 Average 1723255 1620488 1274096 4078121 162867 the given ratio between outputs and inputs, where the SD 2600143 2984311 2262577 5164293 229542 Malmquist model presents the performance change in a Max 7433840 10227028 7855136 13972471 569448 Min 66178 40355 100159 22683 -25470 Decision-Making Unit (DMU) between two consecutive Average 1532530 1558297 1305076 3246324 128814 terms (Tone, 2004) [23]. In this study, the Malmquist model SD 2050667 2913509 2241676 3795720 174731 was used with the presence of negative data for measuring Source: Vietstock (2021) [6]. the efficiency of Vietnamese garment and textiles compa- nies from 2016 to 2020. First, estimating the Catch-Up effect (CUI): T. K. L. NGUYEN et al. – An Application of the Negative Malmquist Model… scores of the Vietnamese garment and textiles companies Table 3 from 2016 to 2020 was conducted (see Table 4). Pearson’s correlation coefficient Variables Year CA NA OE RE NP Table 4 CA 1.0000 0.9937 0.9960 0.9926 0.9805 Efficiency of 10 Vietnamese garment and textiles companies NA 0.9937 1.0000 0.9975 0.9808 0.9637 DMUs 2016 2017 2018 2019 2020 Average OE 2016 0.9960 0.9975 1.0000 0.9814 0.9719 HSM 0.4222 0.4819 0.4144 0.4550 0.3277 0.4202 HTG 1.0657 1.5185 2.0970 1.9527 1.0750 1.5418 RE 0.9926 0.9808 0.9814 1.0000 0.9765 TCM 0.6234 0.9178 1.1473 1.1119 1.3590 1.0319 NP 0.9805 0.9637 0.9719 0.9765 1.0000 TET 8.8384 7.2995 6.2561 6.6120 5.2791 6.8570 CA 1.0000 0.9904 0.9961 0.9923 0.9823 NDT 0.3943 0.3740 0.4006 0.4904 0.5163 0.4351 NA 0.9904 1.0000 0.9951 0.9779 0.9578 MSH 2.4663 2.2255 8.0508 16.2945 2.7867 6.3648 VGT 1.0000 1.0508 1.0395 1.0395 0.9093 1.0078 OE 2017 0.9961 0.9951 1.0000 0.9828 0.9744 M10 1.4858 1.2862 1.0444 1.2247 1.5275 1.3137 RE 0.9923 0.9779 0.9828 1.0000 0.9695 BDG 2.0869 2.1763 2.3327 2.4530 2.5412 2.3180 NP 0.9823 0.9578 0.9744 0.9695 1.0000 NTT 0.5354 0.4824 0.5004 0.7971 0.7987 0.6228 CA 1.0000 0.9913 0.9971 0.9915 0.9073 Average 1.8918 1.7813 2.3283 3.2431 1.7121 2.1913 Max 8.8384 7.2995 8.0508 16.2945 5.2791 6.8570 NA 0.9913 1.0000 0.9941 0.9777 0.8534 Min 0.3943 0.3740 0.4006 0.4550 0.3277 0.4202 OE 2018 0.9971 0.9941 1.0000 0.9832 0.8982 SD 2.5411 2.0481 2.6594 4.9305 1.4891 2.3996 RE 0.9915 0.9777 0.9832 1.0000 0.9061 NP 0.9073 0.8534 0.8982 0.9061 1.0000 Observing Table 4, there were five companies, including CA 1.0000 0.9838 0.9963 0.9926 0.8933 HTG, TET, MSH, M10, and BDG with scores under the num- NA 0.9838 1.0000 0.9887 0.9729 0.8099 ber one and that always achieved efficiency in whole terms; although their scores experienced large-scale annual fluctu- OE 2019 0.9963 0.9887 1.0000 0.9834 0.8818 ations. The efficiency scores of MSH reduced somewhat RE 0.9926 0.9729 0.9834 1.0000 0.8902 from 2.4663 in 2016 to 2.2255 in 2017, then they increased NP 0.8933 0.8099 0.8818 0.8902 1.0000 sharply for the next two years, with scores as 8.0508 (2018) CA 1.0000 0.9720 0.9935 0.9916 0.9442 and 16.2945 (2019), and continuously dropped in the year NA 0.9720 1.0000 0.9849 0.9560 0.8631 2020. TET maintained a downward trend year-to-year ex- OE 2020 0.9935 0.9849 1.0000 0.9740 0.9345 cept for rising slightly from 6.2561 (2018) to 6.612 (2019). The performance of M10 declined for three consecutive RE 0.9916 0.9560 0.9740 1.0000 0.9268 years, and then increased the following two consecutive NP 0.9442 0.8631 0.9345 0.9268 1.0000 years; on the contrary, HTG enjoyed an upward trend within three consecutive years and then suffered a downturn for According to the principle of the DEA method, the collected the next two consecutive years. Minor score fluctuations data must be checked using Pearson’s correlation coeffi- occurred from 2.0869 to 2.5412, so that BDG was the only cient to ensure the appropriate relationship be-tween input company to obtain efficiency with an upward trend for the and inputs; output and output; and, input and output exist entire term. TCM and VGT experienced both efficiency and before their application into the DEA method. The relation- inefficiency; whereas TCM increased continually except for ship between two variables is always isotonic with the value reducing efficiency in the year 2019. VGT had two inefficient exhibited from -1 to +1, it has a perfect linear relationship years and three efficient years; so, VGT had only one up- as near to ±1, a strong correlation as near to ±0.5 and ±0.8, ward-trending term from 1 (2016) to 1.0508 (2017), then a medium correlation as near to ±0.3 and ±0.49, and a low declined consecutively; but it still obtained efficiency in four correlation occurs when lower than ±0.29 [24]. All variables consecutive years from 2016 to 2019. Finally, the three re- with unqualified Pear-son’s correlation are to be removed maining companies, including HSM, NDT, and NTT did not prior to summarization. In this research, the Pearson’s cor- achieve efficiency in whole terms despite their scores show- relations of the 10 Vietnamese garment and textiles com- ing an upward trend. panies maintained variables with values from 0.8099 to 1, In addition, the negative Malmquist model presented the so they are said to have a good linear relationship. There- average score for all garment and textiles companies based fore, all collected data were appreciable in order to apply to on their scores year-to-year. TET had the highest average the negative Malmquist model in the DEA method. efficiency score when it achieved the average score of 6.8570; in contrast, HSM had the lowest average efficiency Measurement of performance score when its score was 0.4202. Besides, this model also In recent years, the garment and textiles industry of Vi- determined the average, maximum and mini-mum scores etnam has developed markedly. The negative Malmquist occurring in each year. The average score for the year 2019 model not only deals with negative data but also provides held the highest valuation, but the influence of the COVID- separate scores for each DMU in each of the years ob- 19 pandemic impacted the average score for the year 2020 served. In this research, a determination of the efficiency to have the lowest valuation. 78 Management Systems in Production Engineering 2022, Volume 30, Issue 1 Additionally, the year of 2019 held the highest efficiency development activities, technology transfers, and product score and the year 2020 had the lowest efficiency score for innovation. both maximum scores and minimum scores present. CONCLUSIONS DICUSSIONS The Vietnamese garment and textiles industry presents a Vietnam is one of the nations in the world where the ex- marked variation in its operational performance from 2016 to 2020, as conducted by the negative Malmquist model. port value of the garment and textiles industry always The empirical results of this modelling exhibited a separate achieves a large valuation. Statistics (2021) have indicated efficiency score every year and an average efficiency score that the total export value in the garment and textiles in- for the period of 2016-2020; moreover, the study revealed dustry in Vietnam increased consecutively from 24.7 billion the considerable impact of the COVID-19 pandemic for the USD to 39 billion USD during 2014 to 2019; however, the garment and textiles industry in Vietnam. COVID-19 pandemic impacted directly on the market-place The study exhibited the process of business operations and and caused a recession while reducing the total export val- improved efficiency score for the Vietnamese garment and ue 35.2 billion USD in 2020 (See Figure 1). Therefore, the textiles industry. Analytic results determined efficient and garment and textiles industry in Vietnam experienced inefficient cases for 10 companies. Such measurement is growth before the COVID-19 outbreak influenced Vietnam, fundamental to the support of enterprises by identifying the region, and globally. The total export values for the year their capable operations to extend improved operational 2020 declined sharply so that the effective operation of the performance in the near future. The main findings contrib- garment and textiles companies in Vietnam dropped sharp- ute to maintaining and developing a sustainable efficient ly with the average efficiency score from 3.2431 in 2019 to garment and textiles industry in Vietnam. This industry con- 1.7121 in 2020. tributes considerably to the GDP, and it will provide an ef- fective operational orientation in the future. Although the study uniquely concerned the performance of the garment and textiles companies in Vietnam, there are still limitations existing. 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Thi Kim Lien Nguyen Thanh Dong University Scientific Research-International Cooperation Hai Duong 171967, Vietnam e-mail: lienntk@thanhdong.edu.vn Xuan-Huynh Nguyen (Corresponding author) Hanoi School of Business & Management Vietnam National University Hanoi 100000, Vietnam e-mail: huynhnx@hsb.edu.vn Hong V. Pham Vietnam Institution of Science Technology and Innovation Hanoi, 100000, Vietnam e-mail: phamvanhong1973@gmail.com

Journal

Management Systems in Production Engineering – de Gruyter

Published: Mar 1, 2022

Keywords: negative malmquist model; data envelopment analysis; garment and textile company; efficiency

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