impact assessment on dost small enterprise technology … · 2020. 9. 4. · national setup...

Proceedings of the 5th NA International Conference on Industrial Engineering and Operations Management Detroit, Michigan, USA, August 10 - 14, 2020

© IEOM Society International

Impact Assessment on DOST Small Enterprise Technology Upgrading Program (SETUP) – assisted MSMEs using

Analytic Hierarchy (AHP) Model

Michael John S. Rivera Department of Science and Technology Region 3

City of San Fernando, Pampanga, Philippines [email protected]

Nabil A. Hadji Yassin Department of Science and Technology Region 12

Koronadal City, South Cotabato, Philippines [email protected]

Jennifer D. Queddeng Department of Science and Technology-National Capital Region

Taguig City, Philippines [email protected]

Rex Aurelius C. Robielos School of Industrial Engineering and Engineering Management

Mapua University Intramuros, Manila, Philippines [email protected]

Abstract

The Philippines’ readiness to participate with the fourth industrial revolution (Industry 4.0) is highly imminent through incorporating science and technology aspects to the MSMEs’ overall operation. This study aims to assess the impact of SETUP implementation at the regional level, particularly in regions NCR, III, and XII based on the criteria from national SETUP guidelines. In this context, the Analytic Hierarchy Process (AHP) Model was used in determining the weights of the performance indicators under the defined SETUP criteria. The weights of the six (6) performance indicators under the three main criteria were computed through AHP to determine the overall impact of SETUP to MSME beneficiaries- highest and lowest impact. Analysis of the pairwise comparison matrix reveals that technology, process, and innovation assimilation (criteria 1) has the highest computed weight with 59.30% while entrepreneurial acumen and management leadership (criteria 3) follows the market and financial outcomes (criteria 2) with 12.60% and 27.10% respectively. For the impact assessment, Region XII has the highest computed scores for criteria 1 and criteria 2, while the highest IA score was observed in NCR for criteria 3. Further, the highest impact scores were observed on the single-proprietorship businesses engaged in agriculture/marine/aquaculture, and food processing. Keywords DOST SETUP, AHP Model, Impact Assessment 1. Introduction In developing countries such as the Philippines, micro, small and medium enterprises (MSMEs) play an essential role in the industrial growth, trade, and employment generation of the country's economy. They are considered one of the most critical development agents in society (Hampel-Milagrosa, 2014). It constitutes more than 99 percent of the total business enterprises in the country that accounts for 32 percent of the country's gross domestic product (GDP) and employs 62.8 percent of the country's workforce (Philippine Statistics Authority, 2018). In support of the Micro, Small, and Medium Enterprise Development Plan (MSMEDP) 2017-2022 geared to make MSMEs more globally

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competitive, the Department of Science and Technology (DOST) continues to push technology-driven solutions and assistance to the MSMEs particularly in the countryside. Technological development is an essential factor increasing the growth rate of the economy at the macro level and profits and market shares of the firms at the micro-level (ÇalÕúkan, 2015). DOST- Small Enterprise Technology Upgrading Program (SETUP) is a nationwide strategy to encourage and assist MSMEs to improve their operations, boost productivity, and improve competitiveness through the adoption of relevant technological innovation. Through this assistance, MSMEs can access interest-free technological fund support and other substantial services to maximize their capabilities and potential, including access to appropriate technologies, human resource capability training, value-addition, access to additional and potential markets, product standardization, and product development, among others. ("Small Enterprise Technology Upgrading Program (SETUP)," n.d.) This holistic approach to improve MSMEs through SETUP focuses on socio-economic sustainability in the countryside. As DOST sees the potential growth of small enterprises in the grassroots, it is also evident that many of the MSMEs lack access to technological and mechanical requirements to upgrade their business. Empirical evidence shows that most small enterprises never develop beyond a specific size, and only a small minority manages to upgrade to the next level of productivity, income, and employment (Berner / Gomez / Knorringa 2008). A study conducted at CALABARZON implies the successful implementation of SETUP in encouraging and assisting MSMEs to adopt technological innovations to improve overall operation and productivity; however, internal and external factors affect the ability of MSMEs to achieve their target level of improvement (Asma, 2015). Based on the DOST Regional Operations Report, the total number of projects funded under the DOST SETUP from 2002 to 2017 was 4.11 billion, which supported 5, 132 projects nationwide. 40 percent of this constitutes the food processing sector, followed by metals and engineering sector with 14 percent. This research study aims to measure the effectiveness of SETUP interventions through impact assessment to the overall improvements of the firm-beneficiaries based on the identified criteria of DOST SETUP. It also aims to provide baseline data analysis of SETUP implementation to the three regions included in this study. 2. Methodology This study utilized a dataset obtained from the list of funded SETUP projects in DOST NCR, Region III (Central Luzon), and Region XII (SOCCSKSARGEN) for the period 2011 to 2015. The dataset includes the profile of SETUP beneficiaries, and quantitative data on beforeand-after interventions that were collected using the SETUP Form 008 (Pre-Implementation Project Information Sheet), SETUP Form 009 (Project Information Sheet for Ongoing Projects) and Completion Report. The AHP is one of the multiple decision-making methods that model decision-making processes mathematically, and is used to solve complex problems (Saaty, 1980). Although the AHP has been used since 1980, decision-making processes were already known with comparative judgment and similar scaling techniques. AHP is also based on relative analyses. The AHP aims at solving the hierarchical model by including in the model the criteria that are effective in the decision-making process by adding second or higher-order layers to the scaling techniques. It also aims to combine qualitative and quantitative factors and arrive at a single judgment (Alsamaray, 2017). AHP was used in determining the weight or level of significance per performance indicator to analyze the effectiveness of SETUP to the assisted MSMEs.

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Figure 1. AHP Framework for DOST SETUP

As shown in Figure 1, the goal is to assess the impact of SETUP to MSME beneficiaries. Based on the DOST Guidelines on the selection of Best SETUP Adapter, there are three (3) main criteria considered to measure the overall impact of the program. Aligned with the definitions of the three main criteria, performance indicators that are currently monitored and reported by the DOST Regional Offices were identified: (1) Technology, Process, and Innovation Assimilation, (2) Market and Financial Outcomes, and (3) Entrepreneurial Acumen and Management Leadership. The weights of the six (6) performance indicators under the three main criteria were computed through AHP to determine the overall impact of SETUP to MSME beneficiaries- highest and lowest impact. The AHP uses pairwise comparisons of subject-matter experts to assess the importance of criteria in a decision (Saaty, 1990). Pairwise comparison survey was designed to seek judgments from subject-matter experts composed of top management, technical personnel implementing SETUP, program manager for SETUP monitoring and evaluation, and planning officer. Further, AHP indicators such as principal EigenValue (PEV) and consistency ratio (CR) were computed. Saaty suggests that the value of RCI for matrices of order 2 is zero and increases with the matrix order. The computed CR should be less than 10% to consider AHP results as consistent and reliable.

Table 1. AHP Scale

Importance Scale Definition of Importance Scale

1 Equally Important Preferred 2 Equally to Moderately Important Preferred 3 Moderately Important Preferred 4 Moderately to Strongly Important Preferred 5 Strongly Important Preferred 6 Strongly to Very Strongly Important Preferred 7 Very Strongly Important Preferred 8 Very Strongly to Extremely Important Preferred 9 Extremely Important Preferred

Further, as part of the pairwise comparison matrix, the calculation was established through solving for Eigenvalue and Eigenvector. Formula can be seen below:

Eigenvalue: (1)

Eigenvector: λ max I) X = 0 (2) In addition, assessing the consistency of the comparison matrix was established using the formula below. Saaty

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suggests that the value of RCI for matrices of order 2 is zero and increases with the matrix order. The computed CR should be less than 10% to consider AHP results as consistent and reliable. Consistency Ratio: CR = CI / RI (3) Table 2 below shows the sample questionnaire used for pairwise comparison of three criteria based on the national SETUP guideline and the identified Key Performance Indicators (KPIs) under each category.

Table 2. Sample AHP Questionnaire

CRITERIA 1. TECHNOLOGY, PROCESS AND INNOVATION ASSIMILATION

Definition Degree and extent of technology adoption in the products and process chain and business processes of the enterprise. Further, it is the extent of assimilation of technology intervention in the whole supply chain comprising materials, people, equipment materials, measurement, information, and energy that results in the expansion of assets, services, and production capabilities.

Question Based on the definition of criteria 1, compare the degree of importance of Indicator (A) with Indicator (B). Please select from 1 (equally important preferred) to 9 (extremely important preferable). Please select one score per row.

Indicator (A) Importance Score please shade the box or encircle the number that corresponds to your answer. Indicator (B)

Production Productivity

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Improvement in Asset Size

The derived weights of performance indicators resulting from AHP were used in the computation of total impact scores per SETUP project. Data collected from each region were tabulated and used to calculate the impact score based on the weights derived from three criteria for SETUP. Then, the impact scores were assessed based on impact rate calculated per criteria. Below is the formula used to calculate for the impact score per SETUP-assisted firms:

IA= (TPI Impact Score x 59.30%) + (MFO Impact Score x 27.10%) + (EML x 13.60%) (4) Where, TPI= (KPI 1 weighted score x 70.30%) + (KPI 2 weighted score*29.30%) (5) MFO= (KPI 3 weighted score*66.40%) + (KPI 4 weighted score*33.60%) (6) EML= (KPI 5 weighted score*65.80%) + (KPI 6 weighted score*34.20%) (7)

3. Results and Discussion 3.1. Descriptive Statistics For the preliminary part of the analysis, a demographic summary was established using the given data set gathered from three regions. Table 3 shows the number of SETUP projects per industry sector with the total approved project costs. From 2011 to 2015, 54% of the SETUP MSME beneficiaries in NCR, Region III, and Region XII belonged to the food processing sector. This is followed by the metals and engineering sector, with 19%. Correspondingly, food processing and metals and engineering utilized the biggest portion of the budget. With the total approved project cost of P285.3 million, 47% of it was allocated to the food processing sector and 26% for the metals and engineering sector. It is evident, however, based on Table 2 that among the 104 SETUP projects assisted in Region 3, GDH or gift, decors, and housewares sector was the main priority sector funded, with 13 approved projects during the period covered.

Table 3. SETUP Projects According to Industry Sector and Region (NCR, Region III, Region XII), 2011-2015

Sectors Approved Projects for 2011-2015 in NCR, Region III, and Region XII Total Approved

Project Costs

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NCR Region III Region XII Total No. of Projects Agriculture/Marine/

Aquaculture 2 11 7 20 22,681,985.00

Food Processing 51 56 46 153 134,336,369.02 Furniture 5 11 4 20 23,658,495.21

GDH 10 13 0 23 16,706,468.00 Halal 0 0 1 1 1,200,000.00 ICT 2 0 0 2 846,238.00

Metals and Engineering 30 11 12 53 74,299,252.38 Pharmaceuticals

Health and Wellness 5 0 2 7 7,408,974.00

Others 1 2 0 3 4,191,209.60 Total 106 104 72 282 285,328,991.21

Based on Table 4 below, 70% of the complete SETUP projects were owned by individual entrepreneurs, in which 60% of these single proprietors are engaged in food processing. Of the total corporation-owned businesses (28%), 43% are into food processing, while 25% are involved in metals and engineering. Out of the 282 SETUP projects in the three regions, only four or 1% of these were owned by cooperatives from Region XII and engaged in agriculture/marine/aquaculture, food processing, metals and engineering, and health and wellness. Tables 5 to 7 show the breakdown per region. In NCR, MSME beneficiaries are equally operated through single proprietorship and corporation arrangements, whereas in Region III and Region XII, the majority of the assisted MSMEs are single proprietorships, 76%, and 89%, respectively.

Table 4. SETUP Projects According to Industry Sector and Ownership, 2011-2015

Sectors

Type of Ownership Total Approved

Project Costs Single Proprietorship Corporation Cooperative

Total No. of Projects

Agriculture/Marine/ Aquaculture/ 16 3 1 20 22,681,985.00


GHD 16 7 0 23 16,706,468.00 Halal 0 1 0 1 1,200,000.00 ICT 2 0 0 2 846,238.00



Others 1 2 0 3 4,191,209.60 Total 198 80 4 282 285,328,991.21

Table 5. SETUP Projects of National Capital Region According to Industry Sector and Ownership, 2011-2015

Sectors Type of Ownership

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Single Proprietorship Corporation Cooperative


Total Approved Project Costs



GHD 6 4 0 10 9,113,793.00 Halal 0 0 0 0 - ICT 2 0 0 2 846,238.00

Metals and Engineering 14 16 0 30 40,123,367.00

Pharmaceuticals Health and Wellness 3 2 0 5 5,208,974.00

Others 0 1 0 1 1,800,000.00 Total 55 51 0 106 115,729,861.59

Table 6. SETUP Projects of Region III (Central Luzon) According to Industry Sector and Ownership, 2011-2015

SECTORS






GHD 10 3 0 13 7,592,675.00 Halal 0 0 0 0 - ICT 0 0 0 0 -


Health and Wellness 0 0 0 0 -

Others 1 1 0 2 2,391,209.60 Total 79 25 0 104 85,656,325.62

Table 7. SETUP Projects of Region XII (SOCCSKSARGEN) According to Industry Sector and Ownership, 2011-

2015

Sectors






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GHD 0 0 0 0 - Halal 0 1 0 1 1,200,000.00 ICT 0 0 0 0 -



Others 0 0 0 0 - Total 64 4 4 72 83,942,804.00

As shown in Table 8 to 11, microscale beneficiaries that are engaged in food processing are predominant in the three regions. In NCR, interventions and funding support were provided to micro (40%), small (44%), and medium (16%) firms. In Central Luzon, more than half (58%) of the assisted firms are micro in scale, followed by small scale firms (38%), and only a few (4%) medium-scale firms were assisted. In SOCCSKSARGEN, program support was solely provided to micro (71%) and small (29%) firms.

Table 8. SETUP Projects According to Industry Sector and Asset Size, 2011-2015

Sectors Type of Asset Size

Total Approved Project Costs Micro Small Medium Total No. of Projects



GHD 14 8 1 23 16,706,468.00 Halal 0 1 0 1 1,200,000.00 ICT 1 1 0 2 846,238.00

Metals and Engineering 20 26 7 53 74,299,252.38 Pharmaceuticals Health and

Wellness 4 2 1 7 7,408,974.00

Others 1 2 0 3 4,191,209.60 Total 152 109 21 282 285,328,991.21

Table 9. SETUP Projects of National Capital Region According to Industry Sector and Asset Size, 2011-2015




Food Processing 20 23 8 51 50,058,453.59

Furniture 2 2 1 5 6,198,036.00 GHD 6 3 1 10 9,113,793.00 Halal 0 0 0 0 0.00 ICT 1 1 0 2 846,238.00

Metals and Engineering 8 16 6 30 40,123,367.00

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Pharmaceuticals Health and Wellness 2 2 1 5 5,208,974.00

Others 1 0 0 1 1,800,000.00 Total 41 48 17 106 115,729,861.59

Table 10. SETUP Projects of Region III (Central Luzon) According to Industry Sector and Asset Size, 2011-2015





GHD 8 5 0 13 7,592,675.00 Halal 0 0 0 0 0.00 ICT 0 0 0 0 0.00


Wellness 0 0 0 0 0.00

Others 0 2 0 2 2,391,209.60 Total 60 40 4 104 85,656,325.62

Table 11. SETUP Projects of Region XII (SOCCSKSARGEN) According to Industry Sector and Asset Size, 2011-

2015





GHD 0 0 0 0 0.00 Halal 0 1 0 1 1,200,000.00 ICT 0 0 0 0 0.00


Wellness 2 0 0 2 2,200,000.00

Others 0 0 0 0 0.00 Total 51 21 0 72 83,942,804.00

3.2.Analytic Hierarchy Process (AHP) Results Tables 12 to 14 show the computed weight per performance indicator. The computed consistency ratio for all performance indicators in the three regions is below 10%, thus consistent and reliable. Table 12 shows the pairwise comparison results for Technology, Process, and Innovation Assimilation. In the three regions, the computed weight for production productivity is higher or more preferred than improvement in asset size. The aggregated AHP results from the three regions revealed that production productivity (70.8%) is a more significant measure compared with

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improvement in asset size (29.2%) in assessing the impact of technology and innovation assimilation to MSME beneficiaries.

Table 12. Computed Weights for Technology, Process and Innovation Assimilation

Criteria NCR REGION III REGION XII Consolidated 3 Regions Production Productivity 71.70% 69.50% 51.40% 70.80%

Improvement in Asset Size 28.30% 30.50% 48.60% 29.20% PEV (λ) 2.0 2.0 2.0 2.0

CR 0.00% 0.00% 0.00% 0.00% Table 13 shows the pairwise comparison results for Market and Financial Outcomes. The results in the three regions revealed that gross sales are a more meaningful measure in assessing the impact of SETUP to MSME beneficiaries compared with market penetration. Gross sales resulting from an increase in production volume sold in at least sustained markets is the main objective. An increase in sales is correlated with product differentiation, and additional product lines offered to the market and improvement in product quality that meets the customers' preferences and demands.

Table 13. Computed Weights for Market and Financial Outcomes

Criteria NCR REGION III REGION XII Consolidated 3 Regions Gross Sales 53.40% 63.90% 84.60% 66.40%

Additional Market Penetrated 46.60% 36.10% 15.40% 33.60% PEV 2.0 2.0 2.0 2.0 CR 0.00% 0.00% 0.00% 0.00%

Table 14 shows the pairwise comparison results for Entrepreneurial Acumen and Management Leadership. In the three regions, financial discipline or the ability of the MSME beneficiaries to pay the refund every month is a more meaningful indicator to exemplify entrepreneurial acumen and management leadership. Financial discipline implies excellent performance in sales and business operations. MSME beneficiaries can sustain the production and remain competitive in the market despite various market players offering the same products and services, and economic shocks. Employment generation is less important or secondary objective as it is the resulting impact of the expansion in business operations and market chain.

Table 14. Computed Weights for Entrepreneurial Acumen and Management Leadership

Criteria NCR REGION III REGION XII Consolidated 3 Regions

Financial Discipline 70.50% 60.10% 65.90% 65.80% Employment Generate 29.50% 39.90% 34.10% 34.20%

PEV 2.0 2.0 2.0 2.0 CR 0.00% 0.00% 0.00% 0.00%

Table 15 shows the derived weights for the three main criteria in assessing the overall impact of SETUP. Technology, Process, and Innovation Assimilation is the most critical factor to focus on implementing the SETUP. The provision of intervention, particularly the technological and innovation component to boost productivity competitiveness of MSMEs, is the comparative advantage of the DOST's SETUP compared with other productivity-related programs of other government agencies. Market and Financial Outcomes, and Entrepreneurial Acumen and Management Leadership criteria are less critical since these are the resulting outcomes of technology assimilation. Other government agencies supporting the development of MSMEs in the country have a higher focus on the two criteria with less consolidated weights.

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Table 15. Computed Weights for the Three Main Criteria in Lieu of the Goal

Criteria NCR REGION III REGION XII Consolidated 3 Regions

Technology, Process and Innovation Assimilation 49.30% 72.7% 54.0% 59.3%

Market and Financial Outcomes 31.10% 20.0% 29.7% 27.1% Entrepreneurial Acumen and

Management Leadership 19.60% 7.3% 16.3% 13.6%

PEV 3.054 3.009 3.009 3.020 CR 5.6% 1.0% 1.0% 2.1%

3.3. Impact Assessment Following the results of AHP, Figure 2 shows the overall weights used in the computation of impact scores per SETUP project.

Figure 2. Impact Assessment Using Derived Weights from AHP

Table 16 to 19 show the impact assessment (IA) scores per criterion and performance indicators that are summarized per sector. For Technology, Process, and Innovation Assimilation, Region XII has the highest overall impact assessment (IA) score among the three regions, while the National Capital Region has the lowest IA score. Significant improvement in production productivity for the agriculture/marine/aquaculture sector was observed with the highest IA score of 46.82, while the ICT sector in NCR has the lowest IA score of 24.78. For Market and Financial Outcomes, SETUP has a significant impact on increasing the volume or sales in Region XII MSME beneficiaries, and sectors agriculture/marine/aquaculture and pharmaceuticals health and wellness. Among the three main criteria, Entrepreneurial Acumen and Management Leadership has the highest computed impact scores from 56.84 (Region XII, Furniture and Pharmaceuticals Health and Wellness) to 98.29 (NCR, ICT). The highest IA score of NCR may be accounted to its maintained 97-98% region-wide annual refund rate, and increased number of direct and indirect employment.

Table 16. Impact Assessment Rate for Technology, Process, and Innovation Assimilation (Criteria 1) per Sector and Region

Sector Impact Assessment (in percentage)

NCR Region III Region XII Consolidated Result

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Agriculture/Marine/ Aquaculture 38.94 39.91 59.93 46.82

Food Processing 32.24 37.06 48.03 38.75 Furniture 12.74 33.47 48.01 31.20

GHD 33.41 28.32 0 30.53 Halal 0 0 60.45* 56.64* ICT 24.78 0 0 24.78

Metals and Engineering 24.12 34.11 45.13 30.95 Pharmaceuticals Health and

Wellness 25.58 0 50.00 32.55

Others 42.48 31.79 0 30.68 Consolidated Impact

Assessment 28.90 35.34 48.88 36.38

*one instance only Table 17. Impact Assessment Rate for Market and Financial Outcomes (Criteria 2) per Sector and Region


NCR Region III Region XII Consolidated Result Agriculture/Marine/

Aquaculture 43.16 46.21 59.64 50.60


GHD 33.26 47.45 0 41.28 Halal 0 0 68.88 68.88* ICT 29.88 0 44.56 29.88


Wellness 53.12 0 44.56 50.67


Assessment 40.73 41.86 49.87 43.48

*one instance only

Table 18. Impact Assessment Rate for Entrepreneurial Acumen and Management Leadership (Criteria 3) per Sector and Region



Aquaculture 91.45 74.93 62.03 72.07


GHD 76.78 69.58 0 72.71 Halal 0 0 60.26 60.26* ICT 98.29 0 0 77.90

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Wellness 86.32 0 56.84 77.90

Others 65.80* 81.19 0 76.06 Consolidated Impact

Assessment 85.02 72.81 59.23 73.93

*one instance only

Table 19. Overall Impact Assessment Rate of SETUP Projects per Sector and Region

Sector

Impact Assessment (in percentage)


Aquaculture 47.22 46.38 60.13 51.28


GHD 39.27 43.35 0 39.18 Halal 0 0 60.45* 60.45* ICT 36.16 0 0 36.16


Wellness 41.30 0 49.96 43.63


Assessment 39.74 42.20 50.55 43.41

*one instance only Table 20 to 23 show the IA scores per type of ownership that are summarized per sector. Across all sectors, cooperative has the highest IA score, but the data is from Region XII only. These assisted cooperatives are engaged in fabrication, machining, herbal products, production of shrimps, and other food products. The single-proprietorship businesses engaged in agriculture/marine/aquaculture has the highest computed IA score. Corporate GHD businesses have the lowest IA score. The NCR has the highest impact scores on the single proprietorship engaged in agriculture/marine/aquaculture, food processing, and pharmaceuticals health and wellness. Lowest IA score of 19.21 is observed in corporate furniture businesses. In Region III, individually owned businesses engaged in agriculture/marine/aquaculture (47.19), food processing (44.84), furniture (43.14); businesses formed through corporations with business lines related to metals and engineering (43.21) have the highest computed IA scores. In Region XII, the corporation, particularly food processing businesses has the highest IA score. While for the individually owned businesses, the agriculture/marine/aquaculture sector has the highest IA score. For cooperatives, the food sector has a significant IA score though it has only one instance in the data set.

Table 20. Impact Assessment Results of SETUP Projects per Type of Ownership

Sectors


Single Proprietorship Corporation Cooperative Consolidated Result

Agriculture/Marine/ Aquaculture 51.76 44.83 62.83 51.28 Food Processing 46.59 39.31 65.55 45.10

Furniture 43.56 32.99 0 37.74

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GHD 41.70 33.43 0 39.18 Halal 0 60.45* 0 60.45* ICT 36.16 0 0 36.16

Metals and Engineering 38.71 35.93 26.08* 39.90 Pharmaceuticals Health and Wellness 42.82 34.13 36.74 43.63

Others 33.78* 36.47 0 35.57 Consolidated Impact Assessment 45.77 37.35 47.80** 43.41 *one instance only **four instance only

Table 21. Impact Assessment Results of SETUP Projects per Type of Ownership, NCR, 2011-2015

Sectors



Agriculture/Marine/ Aquaculture 55.72 38.73* 0 47.22 Food Processing 45.07 39.75 0 42.57

Furniture 32.90 19.21 0 24.68 GHD 44.96 30.74 0 39.27 Halal 0 0 0 0 ICT 36.16 0 0 36.16

Metals and Engineering 40.22 34.11 0 36.96 Pharmaceuticals Health and Wellness 46.08 34.13 0 41.30

Others 0 43.14* 0 43.14 Consolidated Impact Assessment 43.50 35.89 0 39.74

*one instance only

Table 22. Impact Assessment Results of SETUP Projects per Type of Ownership, Region III, 2011-2015

Sectors



Agriculture/Marine/ Aquaculture 47.19 38.20* 0 46.38 Food Processing 44.84 35.20 0 43.46

Furniture 43.14 38.15 0 39.51 GHD 39.74 37.02 0 43.35 Halal 0 0 0 0 ICT 0 0 0 0

Metals and Engineering 37.96 43.21 0 39.87 Pharmaceuticals Health and Wellness 0 0 0 0

Others 33.78 29.81 0 31.79 Consolidated Impact Assessment 43.68 37.55 0 42.20

*one instance only

Table 23. Impact Assessment Results of SETUP Projects per Type of Ownership, Region XII, 2011-2015

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Sectors



Agriculture/Marine/ Aquaculture 60.11 57.56* 62.83* 60.13 Food Processing 49.51 50.39 65.55* 49.90

Furniture 49.20 0.00 0.00 49.20 GHD 0.00 0.00 0.00 0 Halal * 60.45* 60.45* 60.45* ICT 0.00 0.00 0.00 0

Metals and Engineering 0 0.00 26.08* 47.29 Pharmaceuticals Health and Wellness 62.17* 0.00 36.74 49.96

Others 0.00 0.00 0.00 0 Consolidated Impact Assessment 50.47 54.69 49.18 50.55

*one instance only 4. Conclusion Technology, process, and innovation assimilation score the highest impact rate. It, therefore, must be given the high focus on, especially on the conduct of different activities, such as but not limited to technology training, consultancy services, and research and development extension, among others. The results show the lowest and highest impact assessment scores (IAS) in terms of sectors, type of ownership, and both. This can be used in the targeting and evaluating prospective beneficiaries on top of existing practices. The highest Impact Assessment Score (IAS) is Region XII among the three Regions, and the lowest IAS is NCR. The following sectors have the highest IAS: metals and engineering (40.61); food processing (40.54) and furniture (40.50) while the ICT sector has the lowest IAS. In terms of the type of ownership, the Cooperative has the highest IAS. The food processing sector is the second-highest IAS, and the last is the Corporation. In the National Capital Region, the single proprietorship has the highest IAS compared to the Corporation in terms of the type of ownership. The agriculture/marine and aquaculture have the highest IAS, while furniture has the lowest IAS score in the business sectors. In Region III, the highest IAS is food processing, and agriculture is the next second highest. The lowest is the other sectors and GHD. Further, single proprietorship has the highest IAS compared to Corporation. The metals and engineering sector with a corporation as a type of ownership got the highest IAS in the region. In Region XII, agriculture has the highest IAS score among the sectors, while the metals and engineering have the lowest IAS. The single proprietorship under agriculture has the highest IAS for a specific sector and type ownership. References Asma, J.D. 2015. Effects of the Small Enterprises Technology Upgrading Program of the Department of Science and

Technology–Philippines on the Productivity of Beneficiary Enterprises in CALABARZON. Journal of Economics, Management & Agricultural Development Vol. 1, No. 1, Institute of Cooperatives and Bio-Enterprise Development, College of Economics and Management, University of the Philippines Los Baños.

ÇalÕúkan, H.K. 2015. World Conference on Technology, Innovation, and Entrepreneurship: Technological Change and Economic Growth. Procedia - Social and Behavioral Sciences 195 (2015) 649 – 654.

Goepel, Klaus D. (2013). Implementing the Analytic Hierarchy Process as a Standard Method for MultiCriteria Decision Making In Corporate Enterprises – A New AHP Excel Template with Multiple Inputs. Proceedings of the International Symposium on the Analytic Hierarchy Process, pp. 1 -10.

Hampel-Milagrosa, A. 2014. Micro and Small Enterprise Upgrading in the Philippines: The Role of the Entrepreneur, Enterprise, Networks and Business Environment. Studies. German Development Institute.

Department of Trade and Industry, 2018. MSME Statistics. Retrieved from https://www1.dti.gov.ph/resources/msme- statistics/

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Department of Science and Technology Central Visayas Region. Retrieved from http://region7.dost.gov.ph/programs/technology-transfer-andcommercialization/setup/

Wedley, W. C. (1993). Consistency prediction for incomplete AHP matrices, Mathematical and Computer Modelling (Vol. 17). https://doi.org/10.1016/0895-7177(93)90183-Y.

Biographies Rex Aurelius C. Robielos is the Dean of the School of Industrial Engineering and Engineering Management at Mapua University. Before joining Mapua, he was Section Manager of Operations Research Group, Analog Devices General Trias. He has a BS in Applied Mathematics from the University of the Philippines Los Baños, and a Diploma and MS in Industrial Engineering from the University of the Philippines Diliman. He is pursuing Ph.D in Industrial Management (candidate) at National Taiwan University of Science and Technology in Taiwan. He is the current Secretary of Human Factors and Ergonomics Society of the Philippines and Director of the Philippine Institute of Industrial Engineers and Operations Research Society of the Philippines. Michael John S. Rivera is a Science Research Specialist II of the Department of Science and Technology Region 3 (DOST Region 3). He has a BS in Information Technology from the Columban College, Olongapo City. He is pursuing Master in Business Analytics at Mapua University, Manila. He is the current the head of Management Information System (MIS) Unit of DOST Region 3. Nabil A. Hadji Yassin is a Science Research Specialist II at the Department of Science and Technology Region 12. He finished his bachelor’s degree in Forestry at Mindanao State University, Main Campus, Marawi City. He is pursuing Master in Business Analytics at Mapua University, Manila. Jennifer D. Queddeng is a Science Research Specialist II at the Department of Science and Technology-National Capital Region (DOST NCR). She received a bachelor’s degree in Agricultural Economics from the University of the Philippines Los Baños. She is pursuing Master in Business Analytics at Mapua University, Manila.

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1. Introduction2. Methodology3. Results and Discussion3.1. Descriptive Statistics

3.2.Analytic Hierarchy Process (AHP) Results3.3. Impact Assessment

4. ConclusionReferencesBiographies

impact assessment on dost small enterprise technology … · 2020. 9. 4. · national setup...

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