9th GLOBELICS International Conference                      15-17 November 2011, Buenos Aires, ArgentinaAdoption of Intern...
AbstractThis paper attempts to provide new evidence on adoption and impact of internationalstandards by investigating firm...
1. Introduction      Management systems within firms have been getting complex as they face more requestsfrom various stak...
international standards are pre-requisite for firms in East Asia to participate in internationalvalue chains, although the...
2. The Relationships between International Standards and Process Improvements    Firms in Southeast Asia have been facing ...
and drawbacks; impacts on organizational and financial performance; and ISO 9001 and totalquality management (TQM).    Emp...
in developed countries as well as developing countries require their partners to fulfill stricterstandards. As observed by...
3.2. Characteristics of the Establishments    Tables 1 and 2 summarize characteristics of the responded establishments. Th...
nationality and size of the respondent firms. Table 4 observes this finding from a differentpoint of view by providing the...
Table 1: Summary Statistics I                   Variable               Obs        Mean    Std. Dev.   Min   MaxDependent v...
Table 2: Summary Statistics II                Variable                  Obs        Mean     Std. Dev.   Min   MaxIndepende...
Table 3: Adoption of International Standards                                         MNC/JV          Local                ...
Figure 1: Adoption of International Standards and Outcomes                                 Not Adopted                    ...
4. Adoption of International Standards and Performance4.1. Empirical Strategy    The descriptive statistics in the former ...
The equation (1) is estimated by using sub-samples to observe robustness of thecoefficients on Standards estimated using t...
Table 5: Relationship between the Adoption of International Standards and Performance (Whole Sample)                     (...
Table 6: Effects of the Adoption of International Standards on Performance                 (1)         (2)        (3)     ...
(Continued)                     (1)          (2)         (3)         (4)         (5)          (6)         (7)         (8) ...
If the influences of sub-sampling are paid attentions to, the coefficient on Standards isthe most robust significant in th...
from main customer to adopt international standards modeled as the equation (2). Thecoefficient on Request is positively s...
Table 7: Relationship between Customer’s Request for Adopting International Standards and Performance (Whole Sample)      ...
Table 8: Relationship between Customer-requested Adoption of International Standards and Performance                    (1...
Table 9: Relationship between Voluntary Adoption of International Standards and Performance                    (1)        ...
Table 10: Comparison between Customer-requested and Voluntary Adoption of International Standards and Performance         ...
Distinct differences between adopted firms with and without customers’ requirement areobserved when the dependent variable...
management’s backgrounds, and academic background of engineers. Age of firm (i) may alsobe correlated with the capability ...
The similar implication to logistics capability can be derived from engineer exchange.The establishments that dispatch eng...
Table 11: Factors Influential to the Adopted of International Standards                                   (1)       (2)   ...
(Continue)                                       (1)        (2)          (3)        (4)          (5)      (6)             ...
7. Concluding Remarks    This paper attempts to provide new evidence on the adoption and impact of internationalstandards ...
Adoption of International Standards and its Impact on Firm-level Performance in  Southeast Asia:  Effect of Self-Motivatio...
Adoption of International Standards and its Impact on Firm-level Performance in  Southeast Asia:  Effect of Self-Motivatio...
Adoption of International Standards and its Impact on Firm-level Performance in  Southeast Asia:  Effect of Self-Motivatio...
Adoption of International Standards and its Impact on Firm-level Performance in  Southeast Asia:  Effect of Self-Motivatio...
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Adoption of International Standards and its Impact on Firm-level Performance in Southeast Asia: Effect of Self-Motivation and Supply Chain Requirement

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Adoption of International Standards and its Impact on Firm-level Performance in Southeast Asia: Effect of Self-Motivation and Supply Chain Requirement

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Adoption of International Standards and its Impact on Firm-level Performance in Southeast Asia: Effect of Self-Motivation and Supply Chain Requirement

  1. 1. 9th GLOBELICS International Conference 15-17 November 2011, Buenos Aires, ArgentinaAdoption of International Standards and its Impact on Firm-level Performance in Southeast Asia: Effect of Self-Motivation and Supply Chain Requirement TOMOHIRO MACHIKITA Inter-disciplinary Studies Center, Institute of Developing Economies 3-2-2 Wakaba, Mihama-ku, Chiba-shi, Chiba, 261-8545, Japan machi@ide.go.jp YASUSHI UEKI Bangkok Research Center, Institute of Developing Economies 16F, 161 Rajadamri Road, Pathumwan, Bangkok 10330, Thailand yasushi_ueki@ide-jetro.org Tel: +66-2-253-6441(ext. 204) Fax: +66-2-254-1447 1
  2. 2. AbstractThis paper attempts to provide new evidence on adoption and impact of internationalstandards by investigating firm-level dataset constructed by the questionnaire surveyconducted in Indonesia, the Philippines, Thailand and Vietnam in 2009. This paper focuseson: (1) what outcomes can be expected from the adoption of international standards; (2)whether differences in the outcomes exist between firms voluntarily adopted standards andthose adopted upon requirements from their customers; and (3) what kind of a firm isrequired by its customer to adopt and actually adopted international standards. The empiricalresults show the adoption is significantly correlated with outcome indicators and profit.Although there are not considerable differences in outcomes between firms voluntarilyadopted and those adopted upon customer’s requirement, voluntarily-adopted firms tend todecrease inventories and increase profits. Firms voluntarily adopted are likely to ship cargosdaily and practice JIT with their customers and provide training programs to their employees.On the other hand, firms adopted standards facing customers’ request have better engineeringknowledge. This implies that organizational mechanisms fostering intrinsic motivations andcapabilities of employees may enable firms to adopt complex management practices like JITin addition to international standards under silent supply chain pressure and enhanceprofitability.Keywords: ISO; supply chain, process improvement; Southeast Asia.JEL classification: L25, M11, O31, O33 2
  3. 3. 1. Introduction Management systems within firms have been getting complex as they face more requestsfrom various stakeholders. Their corporate customers and final consumers require higher-quality, stable and safe products. Employees demand safer and healthier work environments.The society requires firms not only to pursue more profits and efficiencies but also to takemore responsibilities for confirming to social norms as corporate citizen. Such changes inpublic’s attitudes toward private firms compel governments strengthen social regulations todiscourage antisocial corporate behaviors. All of these pressurize firms, especially multinational companies (MNCs), to introducestandardized quality, environment or other management systems. They are also forced to, forexample, use environmentally-friendly parts, materials and other inputs and produce greenproducts, considering the whole product life cycle. Effects of these managerial requirementsfor a firm reach not only in-house departments but also the whole supply chain of the firm.This is because the whole production process of a product cannot be complete within the firm.Therefore, the firm requires its suppliers to adopt standard management systems. In reality, in their procurement policy or purchasing guidelines, MNCs explicitly orimplicitly set the adoption of international standards as a condition to become their suppliers.For example, suppliers of Toshiba are “expected to establish a quality assurance system inaccordance with the ISO 9000 family of standards,” and “encouraged to adopt ISO 14001-based environmental management systems and to promote third-party certification”according to Toshiba Group Procurement Policy.1 Taiwanese Foxconn requires suppliers ofprinted circuit boards (PCBs) to be certified under ISO 14001. Foxconn Technology Group(2010) reports that 74% of the PCB suppliers have obtained ISO 14001 certificate and thefirm aims that 100% PCBs suppliers be certified ISO 14001 standards by 2010. Foxconn alsoasks suppliers to conduct green house gas (GHG) inventory and reduction according to theinternational standard ISO 14064. Reflecting MNCs’ strategies and the agglomeration of export-oriented manufacturingindustries, firms in East Asia are main adopters of the international standards developed bythe International Organization for Standardization (ISO). Far East accounts for 37.4% of theISO 9001, 50.3% of the ISO 14001, and 47.9% of the ISO/TS 16949 certificates that havebeen issued in the world up to 2009 (ISO 2010). It can be said that the adoption of1 Toshiba (http://www.toshiba.co.jp/procure/en/policy/index.htm), accessed on May 22, 2011. In Toyota Green Purchasing Guideline,suppliers are requested to: acquire ISO 14001 certification or maintain the certification if suppliers have already obtained certification; andfill out the ISO 14001 Certification Survey Form every year. More detailed information are available at Toyota’s website(http://www.toyota-global.com/sustainability/environmental_responsibility/basic_stance_on_the_environment/pdf/p4_5.pdf), accessed onMay 22, 2011. 3
  4. 4. international standards are pre-requisite for firms in East Asia to participate in internationalvalue chains, although the ISO standards are voluntary notionally. On the other hand, the costs for adopting and maintaining ISO international standards areheavy burdens for firms in developing countries, especially small and medium sizedenterprises (SMEs). There are also complaints from firms, especially local SMEs, who cannotrecognize benefits from ISO standards, even though they have made a substantial investmentin acquiring international standards according to customers’ requests. This paper attempts to contribute to the literature by providing new evidence from firmsin Southeast Asia. Our focuses are placed on the following three issues: (1) what outcomescan be expected from the adoption of international standards; (2) whether differences in theoutcomes exist between firms voluntarily adopted standards and those adopted uponrequirements from their customers and (3) what kind of a firm is required by its customer toadopt international standards and actually adopted them. Probit estimations are mainlyapplied to examine these issues. Firm-level dataset was constructed by the questionnairesurvey conducted in Indonesia, the Philippines, Thailand and Vietnam in 2009. The result of binary and ordered probit estimations for whole sample show positivelysignificant relationships between the adoption of international standards and (1) the outcomessuch as improvements in process control, decrease in inputs, and development of markets,and (2) profits. Although there are not considerable differences in outcomes between firmsvoluntarily adopted and those adopted upon customer’s requirement, voluntarily-adoptedfirms tend to decrease inventories and increase profits. Firms adopted standards withoutcustomers’ request ship cargos daily, practice JIT with their customers and have MNC-experienced top management. Firms adopted standards facing customers’ request have higherpercentage of engineers who finished technical college and higher educations. This paper is structured as follows. The second section briefly reviews literatures to raisethe issues relevant to Southeast Asia. The third section explains the data using tables andfigures to observe the current situation in Southeast Asia, using descriptive statistics.Econometric methods are applied from the forth section. The forth section examines therelationship between the adoption of international standards and firm-level performances.The fifth section investigates the difference between firms adopted upon customers’ requestand those adopted voluntarily. The sixth section focuses on firm-level characteristics thataffect the adoption of international standards. The seventh section summarizes empiricalfindings and discusses implications. 4
  5. 5. 2. The Relationships between International Standards and Process Improvements Firms in Southeast Asia have been facing harder competition in the more liberalizedmarket and regional economic integration. Even firms in the region whose competitivenessused to depend on cheap labors cannot be economically sustainable without pursuingcontinuous improvements and innovations. Firms are also demanded by diversifiedstakeholders to take more social responsibilities. To response to these changes in business environments and requirements, firms need toachieve process and product improvements. Internal efforts at the firm level are indispensableto achieve these. Collaborations with external entities are getting more importance becausethe processes for producing a product are not completed within a firm. Literature oninnovation emphasize that external sources of information are crucial for firms in SoutheastAsia where indigenous firms do not have sufficient capabilities to conduct in-house researchand development (R&D) (Machikita, Ueki 2011a). Therefore, mechanisms to facilitate communication within a firm and between firms willaffect performances of intra and inter-firm collaborations. Face-to-face communication is oneof the means to smooth exchanges information, especially tacit knowledge. Empiricalevidences suggest face-to-face communications are significantly important for firms inSoutheast Asia to transfer technologies and knowledge through supply chains (Machikita,Ueki 2011b). Organizational forms that motivate employees intrinsically may also influence creationand transfer of tacit knowledge that sustain competitive advantages. It is necessary to balancebetween intrinsic and extrinsic motivations to generate and sustain distinctive competence(Osterloh, Frey 2000; Osterloh, Frost, Frey 2002). Codification and standardization are another effective approach to facilitate treatment,accumulation and dispersion of knowledge, learning and creation of new knowledge. Fromthis point of view, international standards such as ISO 9000 and 14000 series are a commonlanguage (Franceschini, Galetto, Maisano, Mastrogiacomo 2010). The costly tacit-knowledgecodification and documentation processes embedded in international standards can provideopportunities for communication and assessment of existing business processes. Such wholesystem of international standards may result in stabilizing processing and innovations(Bénézech, Lambert, Lanoux, Lerch, Loos-Baroin 2001). There are extensive literatures concerning international standards. The literature reviewby Sampaio, Saraiva, and Rodrigues (2009) identifies eight major research questions on ISO9000 including: certification market evolution; certification motivations and benefits, barriers 5
  6. 6. and drawbacks; impacts on organizational and financial performance; and ISO 9001 and totalquality management (TQM). Empirical studies in the related literature have shown mixed results of the effect ofinternational standards on business performances. (Sharma 2005). Quazi, Hong, and Meng(2002) confirm no significant effect of the ISO 9000 certification on quality managementpractices and quality results of firms in Singapore. Employing panel data reported by OECDnations, Clougherty and Grajek (2008) find ISO diffusion have no effect in developed nations,but enhance inward FDI and exports in developing nations. These findings suggest thatattributes of companies that are closely related to firms’ capabilities may affect the impact ofinternational standards on business performances. Motivations for firms to adopt international standards are also one of the main issues inthe literature as a factor that may affect benefits of international standards (Heras-Saizarbitoria, Landín, Molina-Azorín 2011). Sun and Cheng (2002) investigate Norwegianmanufacturing companies. They find that customers’ demand and pressure encourage SMEsto practice quality management, while large firms implement it due to mainly internalbenefits. They also insist that SMEs’ performance improvement is marginally correlated withISO 9000 certification, however no significant correlation can be identified for the largecompany. As surveyed by Heras-Saizarbitoria, Arana, and San Miguel (2010), not onlyinternal benefits but also external factors including customer pressures motivate firms toadopt international standards. Actually ISO 9000 has been diffused along supply chains(Neumayer, Perkins 2005; Corbett 2006). Arimura, Darnall, and Katayama (2011) foundgovernment programs that encourage voluntary adoption of environmental managementsystems may promote Japanese facilities to require their suppliers to undertake specificenvironmental practices. These related literatures provide important implications to consider the diffusion andbenefits of international standards in Southeast Asia. In the manufacturing sector in SoutheastAsia where MNCs and large firms take leadership in the governance of value chains,customers’ request may be a considerably powerful motive for firms to adopt internationalstandards. In practical, some MNCs have purchasing policies that stipulate potential suppliersto adopt specific international standards. Even if international standards are voluntary, theyare substantially obligatory in some cases. Although tons of ISO certifications are issued in East Asia, the topics related tointernational standards, has not been investigated sufficiently. The necessity of empiricalstudies, above all for Southeast Asia, is growing because governments and private companies 6
  7. 7. in developed countries as well as developing countries require their partners to fulfill stricterstandards. As observed by Machikita and Ueki (2010) that examined the relationship betweenthe adoption of ISO standards and the geographical structure of production networks, suchnew business environments may have considerable influences on the structure of East Asianproduction networks that are a basic infrastructure for export-driven economic developmentin the region. The worst affected entities by such changes in business environments would beindigenous firms and SMEs in developing countries that do not have sufficient capacities tosatisfy one standard after another. Therefore, the investigation in the following sections takesinto careful consideration differences in firm-level characteristics such as nationality, size,sector, and so force.3. The Data3.1. The sample The dataset used in this paper was developed from the Survey on Fostering Productionand Science & Technology Linkages to Stimulate Innovation in ASEAN (hereafter ERIAEstablishment Survey 2009). The original questionnaire was designed by the authors andtheir collaborators to capture firm-level production networks and collaborative efforts forinnovation. The establishments participated in the survey were asked details on not only theirown characteristics including their sources of information used for process and productinnovation activities but also attributes of their main customer and supplier and cooperativeactivities with them. These unique characteristics differentiate our dataset from existing largesample survey on the adoption of the ISO standards reported by the ISO and governments insome countries that are not necessarily enable to associate ISO standards with firm-levelbusiness performances. The data was collected by mail and interviews conducted during November 2009 –January 2010 in five industrial districts in four countries in Southeast Asia: JABODETABEK(Jakarta, Bogor, Depok, Tangerang and Bekasi) in Indonesia; CALABARZON (Cavite,Laguna, Batangas, Rizal, and Quezon) in the Philippines; Bangkok and surrounding area inThailand; and Hanoi and Ho Chi Minh City area in Vietnam. A total of 864 establishmentsagreed to participate in the survey including: 183 establishments in Indonesia; 203establishments in the Philippines; 178 establishments in Thailand; and 300 establishments inVietnam. The establishments responded to the survey primarily involve in manufacturing. 7
  8. 8. 3.2. Characteristics of the Establishments Tables 1 and 2 summarize characteristics of the responded establishments. The averageage of the responded establishments (variable Age) is 16.8 years old. Some 63.9% of them arecategorized as SMEs that employ 199 or less workers (SME). About 67.5% of them are 100%locally-owned (Local). The high proportion of local firms differentiates the dataset fromother firm surveys that often focus on MNCs. Reflecting the industrial structure in developing countries, the sample includes firmswhose main activities are: Food including beverages and tobacco (11.1%); Textile includingapparel and leather (10.6%); Electronics including computers and parts (11.8%); and Othermachines including machinery industries other than electronics (21.1%). Chemicals includingplastic and rubber products (12.8%) are also an important sector, although fewerestablishments produce other basic materials such as non-metallic mineral products (Non-metal: 1.5%) and iron and steel (Iron: 4.7%).3.3. Adoption of International Standards Table 1 also shows that 43.3% of the respondents (Request) are required by their maincustomers to adopt international standards (ISO9000, ISO14000, etc.) and 50.3% of them(Standards) have adopted any of them. Table 3 describes the influence of firm characteristics to the requirement from thecustomer and the adoption of international standards. There are statistically significantdifferences between MNCs/joint ventures (JVs) and local firms and between large firms andSMEs. Higher proportion of MNCs/JVs: (1) was requested by their customers to adoptinternational standards; (2) has adopted international standards; (3) adopted upon customer’srequest; and (4) adopted without customer’s request. For example, among the MNCs/JVs, 60.5% of them were required to adopt internationalstandards and 70.5% of them have adopted any of them. These percentages for local firms are35.0% and 40.7% respectively, which are significantly smaller than the percentage forMNCs/JVs. Among the firms adopted international standards, (1) 81.8% of MNCs/JVs wererequested adoption by their partners while 57.4% of local firms received such request, and (2)53.2% of MNCs/JVs have adopted without customer’s requirement although 31.7% of localfirms have done without it. Table 3 also presents that firms tend to be motivated by their customers’ requirement toadopt international standards rather than their own voluntary initiatives, irrespective of 8
  9. 9. nationality and size of the respondent firms. Table 4 observes this finding from a differentpoint of view by providing the evidence that the proportion of the firms to whom theircustomers required the adoption of international standards is 58.9% for the firms adoptedstandards and 27.5% for those not adopted. Table 4 reflects the possible relationship between the adoption of international standardsand business performance and whether the difference in motives may affect the impact of theadoption on business performances. To measure performances, firms were asked annualchange in profit (Profit) that is measured on a five-point Likert scale ranging from 1(substantial decrease) to 5 (substantial increase). They were also asked 11 questions abouttheir achievements in 2007-2009, which correspond to 11 dummy variables for outcome(Defect, Inventory, Material, Labor, Quality, Flexibility, Lead-time, Domestic market,Foreign market, Pollution, Regulation) listed in Table 1 and Appendix Table A1 as dependentvariables. These 11 dummy variables for outcome are aggregated into the variable Outcomesthat can ranges from 0 to 11. Table 4 shows that the establishments certified international standards have had betteroutcomes and increased profits with higher possibility than non-certified ones. These findingsare obvious from Figures 1 and 2. Table 4 also suggests that there are not significantdifferences in the performances between establishments adopted internationals standards withand without customer’s requests. But there are exceptions. The establishments obtainedcertifications without requirements from customers have decreased inventories of productsand increased profits. On the other hand, those responded to customers’ requirements haveachieved better performances in decreasing defective products, reducing labor inputs,reducing environmental impacts caused by factory operations and meeting regulatoryrequirements on products. 9
  10. 10. Table 1: Summary Statistics I Variable Obs Mean Std. Dev. Min MaxDependent variable Defect 864 0.727 0.446 0 1 Inventory 864 0.580 0.494 0 1 Material 864 0.506 0.500 0 1 Labor 864 0.334 0.472 0 1 Quality 864 0.838 0.369 0 1 Flexibility 864 0.752 0.432 0 1 Lead-time 864 0.503 0.500 0 1 Domestic market 864 0.606 0.489 0 1 Foreign market 864 0.350 0.477 0 1 Pollution 864 0.612 0.488 0 1 Regulation 864 0.825 0.380 0 1 Outcomes 864 6.634 2.814 0 11 Profit 849 3.356 1.004 1 5Independent variable Standards 864 0.503 0.500 0 1 Request 864 0.433 0.496 0 1Control variable SME 864 0.639 0.481 0 1 Local 864 0.675 0.469 0 1 Food 864 0.111 0.314 0 1 Textile 864 0.106 0.309 0 1 Chemicals 864 0.128 0.335 0 1 Non-metal 864 0.015 0.122 0 1 Iron 864 0.047 0.213 0 1 Electronics 864 0.118 0.323 0 1 Other machines 864 0.211 0.408 0 1 Indonesia 864 0.212 0.409 0 1 Philippines 864 0.235 0.424 0 1 Thailand 864 0.206 0.405 0 1 Vietnam 864 0.347 0.476 0 1Source: ERIA Establishment Survey 2009. 10
  11. 11. Table 2: Summary Statistics II Variable Obs Mean Std. Dev. Min MaxIndependent variable Foreign-owned customer 864 0.203 0.402 0 1 JV customer 864 0.161 0.368 0 1 Capital tie with customer 864 0.406 0.491 0 1 SME customer 864 0.473 0.500 0 1 Ship a few times in a day 864 0.113 0.317 0 1 Ship once in a day 864 0.141 0.348 0 1 Ship a few times in a week 864 0.328 0.470 0 1 Ship once in a week 864 0.176 0.381 0 1 Ship once in a month 864 0.093 0.290 0 1 JIT with customer 864 0.553 0.497 0 1 Dispatch engineer to customer 864 0.541 0.499 0 1 Customer dispatches engineer 864 0.432 0.496 0 1 Customer dispatches trainer 864 0.319 0.467 0 1 Customer dispatches trainee 864 0.242 0.428 0 1 R&D 864 0.501 0.500 0 1 OJT 864 0.590 0.492 0 1 OFF-JT 864 0.465 0.499 0 1 Top has master/Ph.D. 864 0.284 0.451 0 1 Top is engineer 864 0.578 0.494 0 1 Top is MNC-experienced 864 0.459 0.499 0 1 0-20% of engineers 864 0.219 0.414 0 1 20-40% of engineers 864 0.066 0.248 0 1 40-60% of engineers 864 0.063 0.242 0 1 60-80% of engineers 864 0.168 0.374 0 1 80-100% of engineers 864 0.332 0.471 0 1 Age 833 16.796 13.922 0 181Source: ERIA Establishment Survey 2009. 11
  12. 12. Table 3: Adoption of International Standards MNC/JV Local Large SME Percent (1) Percent (2) diff Percent (1) Percent (2) diffCustomer required the adoption 60.5% 35.0% (***) 54.2% 37.1% (***)Adoption of international standards 70.5% 40.7% (***) 67.9% 40.4% (***)Observations 281 583 312 552Adoption of international standards Upon customers request 81.8% 57.4% (***) 79.3% 59.5% (***) No. of Observations 170 204 169 205 Voluntarily 53.2% 31.7% (***) 54.5% 29.1% (***) No. of Observations 111 379 143 347Notes: diff=Percent(1)-Percent(2), H0: diff=0. (***) indicates H0 (Ha: diff>0) are significant at 1% level.Source: ERIA Establishment Survey 2009.Table 4: Adoption of International Standards and Performances Adopted Not Adopted Adopted Not requested Requested Percent (1) Percent (2) diff Percent (1) Percent (2) diff Customer required the adoption 27.5% 58.9% ***(1) Decrease defective goods 67.6% 77.7% *** 72.6% 81.3% **(2) Decrease inventories 50.8% 65.1% *** 69.8% 61.7% (**)(3) Decrease raw materials 41.0% 60.0% *** 59.2% 60.5%(4) Reduce labor input 30.8% 36.1% ** 31.8% 39.1% *(5) Improve quality of goods 81.8% 85.7% * 83.2% 87.5%(6) Improve flexibility of production 68.8% 81.6% *** 79.3% 83.2%(7) Reduce lead-time 42.0% 58.6% *** 62.0% 56.3%(8) Enter/Increase domestic market 52.9% 68.3% *** 70.4% 66.8%(9) Enter/Increase foreign market 23.5% 46.2% *** 49.2% 44.1%(10) Reduce environmental impacts 50.6% 71.7% *** 67.0% 75.0% **(11) Meet regulatory requirements 0.7% 0.9% *** 87.7% 92.2% *(12) Number of outcomes 5.8 7.4 *** 7.3 7.5 Observations 429 435 179 256 Increase profit 3.2 3.5 *** 3.7 3.3 (***) Observations 419 430 179 256Notes: diff=Percent(1)-Percent(2), H0: diff=0. ***, **,* indicate H0 (Ha: diff<0) are significant at 1%, 5%,10% level respectively. (***), (**) indicate H0 (Ha: diff>0) are significant at 1% and 5% level respectively.Source: ERIA Establishment Survey 2009. 12
  13. 13. Figure 1: Adoption of International Standards and Outcomes Not Adopted Adopted 20 15 Percent 10 5 0 0 2 4 6 8 10 0 2 4 6 8 10 Number of Outcomes Adoption of International StandardsNote: The variable Outcomes is an aggregate total of 11 dummy variables foroutcome, thus ranges from 0 to 11.Source: ERIA Establishment Survey 2009.Figure 2: Adoption of International Standards and Change in Profit Not Adopted Adopted 50 45 40 35 30 Percent 25 20 15 10 5 0 1 2 3 4 5 1 2 3 4 5 Annual Change in Profit 1(Substantial decrease) - 3(almost same) - 5(Substantial increase) Adoption of International StandardsNote: The annual change in Profit is measured on a five-point Likert scale rangingfrom 1 (substantial decrease) to 5 (substantial increase).Source: ERIA Establishment Survey 2009. 13
  14. 14. 4. Adoption of International Standards and Performance4.1. Empirical Strategy The descriptive statistics in the former section implies the relationship between theadoptions of international standards and business performances. Because rigorous statisticalmethods should be applied to examine it, the following model is developed: yi = α + β∗Standardsi + γ∗xi + ui. (1) The dependent variable y is one of the following performance indicators: a dummyvariable for outcome (Defect, Inventory, Material, Labor, Quality, Flexibility, Lead-time,Domestic market, Foreign market, Pollution, Regulation); Outcomes that can ranges from 0to 11; and a five-point Likert-type variable Profit. The independent variables are Standards and control variables x, both of which arebinary. The variable Standardsi is coded 1 if firm (i) has adopted international standards and 0otherwise. A set of the binary variables xi are control variables for size (SME), nationality(Local), main business activity (Food, Textile, Chemicals, Non-metal, Iron, Electronics,Other machines), and location where firm (i) is located (Indonesia, Philippines, Vietnam).Details of the dependent, independent and control variables are listed in Appendix Table A1. We applied binary probit estimations when the dependent variable is binary and orderedprobit estimations when the dependent variable is Outcomes or Profit. As there are 13performance indicators, 13 estimations are implemented using the whole sample as a baseline.Then the same estimations are carried out using restricted samples to check robustness of theestimated coefficients on Standards and influence of firm characteristics to the relationshipbetween Standards and performance.4.2. Results Table 5 shows the result of baseline estimations using the whole sample. The adoption ofinternational standards has positively significant relationships with all performance indicatorsexcept the improvement in quality of goods and services in the column (5). Among thecontrol variables, SMEs are less likely to develop markets, improve quality and pollutioncontrols control and increase profits than large firms. Significant differences betweenMNCs/JVs and local firms are not identified in all performance indicators except thedevelopment of or new entry into foreign market and compliance with regulatoryrequirements on products. 14
  15. 15. The equation (1) is estimated by using sub-samples to observe robustness of thecoefficients on Standards estimated using the whole sample, or whether there are significantdifferences according to characteristics of the establishments. Table 6 reports only theestimated coefficients on Standards and robust standard errors. The far-left column indicatescriteria for restricting the sample, which is chosen from the control variables in the equation(1). The figures in the first row for “Whole” are the same as the coefficients on and robuststandard errors for Standards in Table 5. Table 6 makes it obvious that there are differences among firm groups in thesignificances of the estimated coefficients. If the sample is restricted to one of the sector, thenumber of significant coefficients on Standards decreases considerably. For example, thecoefficient for Food sector is positively significant only when the dependent variable isInventory and Pollution and negatively significant in the regression of Quality. There are differences between local firms and MNCs/JVs. Local firm adoptedinternational standards tend to have decreased labor inputs and increased profit, whileMNCs/JVs have decreased defective products and inventories and improved flexibilities. Notso many differences were observed between SMEs and large firms. Higher proportion of theSMEs conforming to international standards have developed or entered into foreign marketsalthough large firms have increased profit. Dissimilarities are also observed among local firms and among MNCs/JVs. Local SMEsadopted international standards have realized better achievements than local large firms.Except Defect and Flexibility, the significant coefficients for the sample restricted to localSMEs are same as the results based on the whole sample. In contrast, the coefficient onStandards is significant in only four of the 13 regressions for large local firms. MultinationalSMEs have more significant coefficients than large MNCs. But the foreign-owned SMEswith certifications have not increased profit even although large certified MNCs have realizedit. The differences between local and foreign-owned SMEs exist in: decreases in inventory,materials and labor input and increase in profit that local SMEs have attained; and decreasein defective products and improvement in quality and flexibility of production or serviceprovision that have achieved by foreign-owned SMEs. It can be considered local large firms can not recognize benefits from obtainingcertifications of international standards. Compared with local large firms, local SMEsadopted international standards tend to develop domestic and foreign markets and increaseprofit. Relative to large local or foreign-owned firms, local or foreign-owned SMEs have hadsucceeded in developing or entering foreign market. 15
  16. 16. Table 5: Relationship between the Adoption of International Standards and Performance (Whole Sample) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) Binary Ordered Ordered domestic foreign defect inventory material labor quality flexibility lead-time pollution regulation outcomes profit market marketStandards 0.105*** 0.094** 0.178*** 0.071* 0.013 0.109*** 0.184*** 0.135*** 0.165*** 0.225*** 0.144*** 0.534*** 0.156* (0.034) (0.037) (0.037) (0.036) (0.028) (0.032) (0.038) (0.037) (0.035) (0.036) (0.027) (0.079) (0.081)SME -0.027 -0.025 -0.061 0.040 -0.085*** -0.019 -0.021 -0.067* -0.121*** -0.074* -0.030 -0.193** -0.209** (0.034) (0.038) (0.039) (0.036) (0.026) (0.033) (0.040) (0.038) (0.037) (0.038) (0.027) (0.077) (0.083)Local -0.038 -0.052 0.028 -0.042 -0.030 -0.040 0.057 -0.018 -0.132*** -0.002 -0.051* -0.117 -0.017 (0.038) (0.041) (0.043) (0.040) (0.030) (0.035) (0.044) (0.042) (0.041) (0.043) (0.029) (0.085) (0.091)Food 0.017 -0.070 -0.055 -0.035 0.020 0.020 -0.086 -0.017 -0.127** -0.067 0.057 -0.149 0.079 (0.054) (0.063) (0.064) (0.058) (0.043) (0.053) (0.065) (0.065) (0.056) (0.065) (0.040) (0.120) (0.130)Textile -0.007 -0.033 0.031 0.031 -0.017 -0.063 -0.137** -0.111* -0.006 -0.094 -0.095* -0.190 -0.423*** (0.057) (0.064) (0.065) (0.063) (0.048) (0.058) (0.065) (0.067) (0.062) (0.065) (0.054) (0.136) (0.136)Chemicals 0.003 0.039 0.082 0.027 -0.004 0.010 0.008 -0.065 -0.045 0.010 -0.032 0.041 -0.244* (0.054) (0.059) (0.059) (0.060) (0.043) (0.049) (0.062) (0.061) (0.055) (0.061) (0.047) (0.131) (0.132)Non-metal -0.162 0.030 0.152 0.138 -0.068 -0.197 -0.041 0.120 0.049 -0.014 -0.079 -0.026 0.482 (0.143) (0.142) (0.144) (0.164) (0.116) (0.137) (0.146) (0.121) (0.131) (0.149) (0.120) (0.290) (0.389)Iron 0.051 0.021 0.106 0.156* -0.017 0.000 -0.165* -0.219** -0.227*** -0.035 -0.085 -0.190 0.212 (0.074) (0.088) (0.086) (0.090) (0.062) (0.071) (0.085) (0.086) (0.055) (0.088) (0.076) (0.160) (0.209)Electronics -0.089 0.044 -0.007 0.001 0.008 0.082* -0.045 -0.014 -0.028 -0.159** -0.019 -0.077 -0.173 (0.062) (0.063) (0.064) (0.060) (0.046) (0.049) (0.066) (0.066) (0.059) (0.065) (0.051) (0.129) (0.132)Other machines 0.016 0.083* 0.085 0.047 0.038 0.080** 0.128** 0.006 -0.050 0.032 -0.001 0.156 -0.173 (0.045) (0.050) (0.052) (0.051) (0.034) (0.039) (0.054) (0.053) (0.048) (0.053) (0.038) (0.106) (0.111)Indonesia 0.214*** 0.012 -0.072 0.063 0.087*** 0.203*** 0.449*** 0.329*** 0.033 0.211*** 0.116*** 0.688*** 0.214** (0.032) (0.054) (0.055) (0.053) (0.030) (0.031) (0.041) (0.038) (0.055) (0.044) (0.027) (0.111) (0.105)Philippines 0.239*** 0.111** 0.136** 0.256*** 0.076** 0.146*** 0.328*** 0.149*** 0.052 0.293*** 0.085*** 0.797*** -0.605*** (0.031) (0.051) (0.053) (0.053) (0.031) (0.035) (0.049) (0.048) (0.055) (0.041) (0.030) (0.127) (0.118)Vietnam 0.219*** 0.216*** -0.027 -0.114** 0.060* 0.113*** 0.309*** 0.356*** 0.110** 0.045 0.050 0.506*** 0.999*** (0.035) (0.046) (0.050) (0.046) (0.031) (0.037) (0.049) (0.040) (0.051) (0.048) (0.032) (0.101) (0.103)Observations 864 864 864 864 864 864 864 864 864 864 864 864 849Pseudo R2 0.069 0.055 0.051 0.076 0.032 0.064 0.105 0.099 0.088 0.093 0.082 0.036 0.111Notes: Marginal effect for binary probit estimation. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. 16
  17. 17. Table 6: Effects of the Adoption of International Standards on Performance (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) Binary Ordered Ordered domestic foreign defect inventory material labor quality flexibility lead-time pollution regulation outcomes profit market market<Sample>Whole 0.105*** 0.094** 0.178*** 0.071* 0.013 0.109*** 0.184*** 0.135*** 0.165*** 0.225*** 0.144*** 0.534*** 0.156* (0.034) (0.037) (0.037) (0.036) (0.028) (0.032) (0.038) (0.037) (0.035) (0.036) (0.027) (0.079) (0.081)Local 0.015 0.059 0.178*** 0.072* -0.042 0.064 0.146*** 0.102** 0.166*** 0.202*** 0.095*** 0.421*** 0.211** (0.040) (0.045) (0.045) (0.043) (0.035) (0.040) (0.046) (0.044) (0.041) (0.043) (0.033) (0.094) (0.094)MNC/JV 0.320*** 0.142** 0.178** 0.047 0.156*** 0.207*** 0.245*** 0.248*** 0.120* 0.272*** 0.266*** 0.747*** 0.008 (0.068) (0.068) (0.072) (0.072) (0.053) (0.060) (0.069) (0.074) (0.070) (0.073) (0.058) (0.153) (0.168)SME 0.085** 0.098** 0.179*** 0.072 0.007 0.083** 0.161*** 0.129*** 0.180*** 0.219*** 0.168*** 0.527*** 0.082 (0.042) (0.047) (0.047) (0.046) (0.038) (0.041) (0.048) (0.047) (0.042) (0.045) (0.033) (0.102) (0.103)Large 0.142** 0.112* 0.164** 0.078 0.029 0.143** 0.272*** 0.150** 0.076 0.242*** 0.111** 0.568*** 0.249* (0.061) (0.065) (0.067) (0.063) (0.038) (0.058) (0.064) (0.066) (0.067) (0.065) (0.047) (0.139) (0.144)Local SME 0.028 0.094* 0.208*** 0.095* -0.037 0.042 0.138** 0.120** 0.183*** 0.219*** 0.128*** 0.480*** 0.213* (0.049) (0.054) (0.053) (0.052) (0.044) (0.049) (0.055) (0.053) (0.049) (0.052) (0.038) (0.115) (0.113)Local large -0.029 0.137 0.160* 0.018 -0.015 0.107 0.250*** 0.078 0.054 0.191** 0.032 0.371* 0.197 (0.080) (0.094) (0.091) (0.071) (0.062) (0.078) (0.089) (0.083) (0.091) (0.089) (0.061) (0.193) (0.184)SME MNC/JV 0.299*** 0.149 0.112 0.019 0.221** 0.257*** 0.248** 0.259** 0.181* 0.200** 0.333*** 0.718*** -0.384 (0.098) (0.099) (0.102) (0.097) (0.086) (0.085) (0.098) (0.114) (0.101) (0.101) (0.083) (0.217) (0.245)Large MNC/JV 0.359*** 0.065 0.168 0.080 0.128 0.132 0.254** 0.187* 0.029 0.374*** 0.226** 0.672*** 0.433* (0.102) (0.102) (0.112) (0.105) (0.078) (0.091) (0.101) (0.110) (0.106) (0.116) (0.088) (0.226) (0.244)Indonesia 0.172** 0.015 0.113 0.012 0.018 0.004 0.173** 0.132* 0.223*** 0.329*** 0.191*** 0.552*** 0.183 (0.077) (0.088) (0.087) (0.082) (0.064) (0.078) (0.085) (0.078) (0.081) (0.076) (0.052) (0.192) (0.194)Philippines 0.170*** 0.112 0.092 0.078 0.077 0.163*** 0.149* 0.186** 0.157* 0.104* 0.149*** 0.536*** -0.184 (0.058) (0.079) (0.079) (0.082) (0.049) (0.061) (0.082) (0.082) (0.083) (0.061) (0.049) (0.186) (0.180)Thailand 0.174** 0.044 0.210** 0.108 0.049 0.117 0.232*** 0.151* 0.181** 0.330*** 0.307*** 0.678*** -0.099 (0.087) (0.095) (0.086) (0.079) (0.075) (0.085) (0.066) (0.084) (0.081) (0.081) (0.072) (0.181) (0.206)Vietnam -0.011 0.160*** 0.234*** 0.064 -0.032 0.129** 0.176*** 0.120** 0.133** 0.188*** 0.053 0.540*** 0.509*** (0.050) (0.055) (0.059) (0.045) (0.042) (0.051) (0.060) (0.052) (0.057) (0.060) (0.046) (0.127) (0.132) 17
  18. 18. (Continued) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) Binary Ordered Ordered domestic foreign defect inventory material labor quality flexibility lead-time pollution regulation outcomes profit market marketFood 0.084 0.233* 0.122 0.128 -0.198** -0.047 0.183 0.039 0.184 0.211* 0.049 0.400 0.075 (0.101) (0.125) (0.133) (0.121) (0.101) (0.113) (0.130) (0.131) (0.115) (0.113) (0.049) (0.292) (0.256)Textile 0.201** 0.241* 0.195 0.123 -0.068 0.097 0.165 0.053 0.321*** 0.297*** 0.255*** 0.673*** 0.665** (0.088) (0.126) (0.122) (0.126) (0.066) (0.116) (0.124) (0.129) (0.119) (0.110) (0.081) (0.241) (0.275)Chemicals 0.065 0.032 0.281*** -0.086 0.074 0.192** -0.002 0.177* 0.077 0.123 0.176** 0.389* 0.045 (0.087) (0.101) (0.096) (0.095) (0.076) (0.090) (0.109) (0.101) (0.097) (0.098) (0.079) (0.210) (0.217)Electronics 0.117 0.122 0.286** 0.079 0.068 0.141* 0.350*** 0.049 0.128 0.226* 0.193** 0.650*** -0.094 (0.109) (0.107) (0.115) (0.099) (0.080) (0.083) (0.101) (0.110) (0.110) (0.128) (0.088) (0.252) (0.264)Other machines 0.106 0.109 0.104 0.055 -0.002 0.061 0.126 0.132 0.147* 0.195** 0.094 0.454*** 0.440** (0.072) (0.077) (0.083) (0.083) (0.048) (0.070) (0.083) (0.081) (0.079) (0.079) (0.061) (0.169) (0.190)Notes: Only estimated coefficients are reported. Marginal effect for binary probit estimation. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. 18
  19. 19. If the influences of sub-sampling are paid attentions to, the coefficient on Standards isthe most robust significant in the regressions of Pollution and Outcomes. For each dependentvariable, 18 estimations were attempted. Only the estimation using the sample of Chemicalsdoes not have a significant marginal effect of Standards on Pollution. When the dependentvariable is Outcomes and the sample is restricted to the Food related sector, the estimatedcoefficient Standards is not significant. Other relatively robust coefficients were obtainedfrom the regressions of Lead-time, Regulation, Domestic market, and Foreign market. Fromthese analyses, firms adopted international standards may have better management systems tomeet environmental and other regulatory requirements. They also show better results inmarket developments.5. Comparison Between Customer-requested and Voluntary Adoption5.1. Empirical Strategy Table 4 attempted to show how difference in motives to adopt international standardsmay affect performances. To examine this question by regression analyses, firstly weinvestigate which one or both may really matter for firms who achieved better performance:requests from customers to adopt international standards that put pressure on firms to makeimprovements or actual adoption of them. For this purpose implemented are estimations ofthe following model that is based on the equation (1): yi = α + β∗Requesti + γ∗xi + ui. (2). The variables in equation (2) are the same as those in equation (1) except replacingindependent variable Standards with Request. Then the equation (1) is estimated again by using the data only for the firms adoptedinternational standards. To investigate the impact of requirements from customers onperformances of the firms adopted international standards, the certified firms are categorizedinto two groups: firms (1) requested and (2) not requested. As already discussed in theprevious section, firm characteristics may or may not affect results of the estimation. Thesame methodology as Table 6 is applied to the two groups to get a better understanding on theimpacts.5.2. Results Table 7 provides results of the regression of performance indicators on the requirement 19
  20. 20. from main customer to adopt international standards modeled as the equation (2). Thecoefficient on Request is positively significant only in the three regressions of Defect at the1% significant level, Pollution at the 5% level and Regulation at the 10% level. Compared tothe significant coefficients on Standards in Table 5, the number of the significant coefficienton Request is small. From these findings it can be considered that adoption of internationalstandards will have substantial impacts on management system and performance. Tables 8, 9 and 10 show estimation results of the equation (1) with the sample restrictedto the firms that have adopted international standards. To investigate the influence ofdifference in motives to performances, the sample is divided into the firms who adoptedinternational standards having a requirement from their main customers to adopt them andthose who adopted them without such requirement from their main customers. Table 8 presents the estimation result for the firms adopted international standards uponthe requirement from the customers. The coefficients on Standards are significant at the 1%and 5% levels except in the regressions of Inventory, Labor, Quality, and Profit. Thecoefficients on control variables for size, nationality and industries are not as constantlysignificant as Standards. Table 9 presents the estimation result for the firms adopted international standardswithout the requirement from the customers. The coefficients on Standards are significant inall of the regressions except of Defect, and Quality. Although the coefficients on Electronicsare negative, the coefficients on other control variables for size, nationality and industries arenot persistently significant. To see the robustness of the coefficients on Standards shown in Tables 8 and 9 orwhether there are significant differences in the significant coefficients according tocharacteristics of the firms and presence/absence of customers’ requirement, the equation (1)is estimated restricting the sample in the same way as conducted in Table 6. Because of theconstraint of the number of the observations, the sample was restricted to local firms,MNCs/JVs, SMEs and large firms. The upper portion of Table 10 contains only the estimatedcoefficients on Standards and robust standard errors for the adopted firms required by theircustomers, while the lower portion of Table 10 tabulates figures for the adopted firms withoutrequirement from their customers. The coefficient on Standards in the regression of Material, Pollution, and Outcomes issignificant irrespective of presence or absence of the requirement from customers. Thecoefficient is also relatively robust in the regression of Lead-time and Regulation. 20
  21. 21. Table 7: Relationship between Customer’s Request for Adopting International Standards and Performance (Whole Sample) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) Binary probit Ordered probit domestic foreign defect inventory material labor quality flexibility lead-time pollution regulation outcomes profit market marketRequest 0.090*** -0.045 0.003 0.010 0.030 0.025 -0.015 0.021 -0.010 0.089** 0.045* 0.076 0.001 (0.032) (0.037) (0.037) (0.035) (0.027) (0.032) (0.038) (0.037) (0.036) (0.036) (0.027) (0.075) (0.078)SME -0.040 -0.051 -0.096** 0.026 -0.085*** -0.039 -0.060 -0.093** -0.153*** -0.110*** -0.057** -0.290*** -0.240*** (0.033) (0.037) (0.038) (0.036) (0.025) (0.032) (0.039) (0.037) (0.037) (0.036) (0.027) (0.075) (0.083)Local -0.041 -0.079* -0.010 -0.055 -0.027 -0.056 0.015 -0.043 -0.168*** -0.033 -0.067** -0.215** -0.051 (0.037) (0.041) (0.042) (0.040) (0.029) (0.034) (0.044) (0.041) (0.041) (0.041) (0.029) (0.086) (0.088)Food 0.007 -0.081 -0.072 -0.043 0.019 0.011 -0.103 -0.031 -0.139*** -0.085 0.048 -0.196* 0.060 (0.056) (0.063) (0.063) (0.057) (0.043) (0.053) (0.063) (0.065) (0.054) (0.064) (0.042) (0.119) (0.129)Textile -0.018 -0.063 -0.011 0.015 -0.015 -0.086 -0.176*** -0.139** -0.045 -0.129** -0.126** -0.292** -0.460*** (0.058) (0.065) (0.065) (0.062) (0.047) (0.059) (0.062) (0.066) (0.060) (0.065) (0.058) (0.137) (0.137)Chemicals 0.003 0.049 0.094 0.029 -0.005 0.015 0.023 -0.057 -0.031 0.020 -0.025 0.072 -0.234* (0.054) (0.058) (0.059) (0.060) (0.043) (0.049) (0.061) (0.061) (0.055) (0.060) (0.047) (0.131) (0.132)Non-metal -0.134 0.028 0.162 0.141 -0.061 -0.181 -0.033 0.131 0.059 0.008 -0.066 0.019 0.488 (0.140) (0.141) (0.137) (0.162) (0.114) (0.142) (0.149) (0.120) (0.133) (0.147) (0.121) (0.303) (0.389)Iron 0.050 0.030 0.111 0.156* -0.021 0.002 -0.153* -0.213** -0.221*** -0.036 -0.081 -0.178 0.215 (0.073) (0.087) (0.085) (0.090) (0.063) (0.071) (0.085) (0.086) (0.058) (0.088) (0.074) (0.155) (0.209)Electronics -0.085 0.058 0.013 0.007 0.007 0.089* -0.021 0.000 -0.006 -0.138** -0.006 -0.026 -0.158 (0.062) (0.063) (0.064) (0.060) (0.046) (0.048) (0.066) (0.065) (0.061) (0.064) (0.050) (0.131) (0.131)Other machines 0.018 0.097** 0.101** 0.053 0.035 0.087** 0.145*** 0.017 -0.031 0.043 0.010 0.195* -0.159 (0.046) (0.050) (0.052) (0.051) (0.034) (0.039) (0.053) (0.053) (0.048) (0.051) (0.037) (0.105) (0.111)Indonesia 0.221*** 0.009 -0.068 0.064 0.089*** 0.205*** 0.440*** 0.330*** 0.034 0.215*** 0.122*** 0.683*** 0.216** (0.032) (0.054) (0.055) (0.053) (0.029) (0.031) (0.042) (0.038) (0.055) (0.044) (0.028) (0.111) (0.105)Philippines 0.241*** 0.100** 0.124** 0.253*** 0.079*** 0.143*** 0.310*** 0.142*** 0.039 0.286*** 0.086*** 0.753*** -0.613*** (0.032) (0.051) (0.053) (0.054) (0.031) (0.036) (0.050) (0.048) (0.054) (0.041) (0.032) (0.126) (0.117)Vietnam 0.240*** 0.212*** -0.015 -0.107** 0.066** 0.123*** 0.309*** 0.363*** 0.115** 0.075 0.071** 0.539*** 1.005*** (0.035) (0.047) (0.051) (0.047) (0.032) (0.037) (0.049) (0.040) (0.051) (0.048) (0.032) (0.102) (0.104)Observations 864 864 864 864 864 864 864 864 864 864 864 864 849Pseudo R2 0.067 0.051 0.032 0.073 0.033 0.053 0.086 0.088 0.069 0.066 0.050 0.025 0.109Notes: Marginal effect for binary probit estimation. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. 21
  22. 22. Table 8: Relationship between Customer-requested Adoption of International Standards and Performance (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) Binary Ordered Ordered domestic foreign defect inventory material labor quality flexibility lead-time pollution regulation outcomes profit market marketStandards 0.114** 0.094 0.214*** 0.062 -0.012 0.142*** 0.219*** 0.192*** 0.171*** 0.195*** 0.147*** 0.603*** 0.072 (0.055) (0.062) (0.059) (0.060) (0.038) (0.053) (0.060) (0.061) (0.055) (0.060) (0.046) (0.126) (0.130)SME -0.039 0.004 -0.064 0.051 -0.108*** -0.043 0.018 -0.035 -0.088 -0.100* -0.012 -0.198* -0.096 (0.047) (0.057) (0.057) (0.054) (0.035) (0.044) (0.060) (0.056) (0.054) (0.053) (0.033) (0.112) (0.120)Local -0.064 -0.180*** -0.000 -0.074 -0.063* -0.057 0.030 -0.028 -0.097 -0.021 -0.075** -0.226* -0.184 (0.051) (0.060) (0.064) (0.059) (0.037) (0.048) (0.066) (0.061) (0.061) (0.061) (0.037) (0.126) (0.126)Food -0.062 -0.021 -0.201* -0.194** -0.051 0.015 -0.080 -0.075 -0.162* -0.285*** -0.032 -0.433** 0.210 (0.089) (0.109) (0.109) (0.084) (0.077) (0.079) (0.115) (0.113) (0.092) (0.105) (0.072) (0.187) (0.206)Textile 0.001 0.093 -0.029 0.046 0.040 0.029 -0.247** 0.023 0.231* -0.153 -0.153 -0.023 -0.043 (0.099) (0.114) (0.119) (0.123) (0.061) (0.087) (0.109) (0.138) (0.127) (0.131) (0.105) (0.234) (0.267)Chemicals 0.022 0.053 0.024 -0.136* 0.013 -0.036 -0.077 -0.165* -0.144* -0.146 -0.083 -0.245 -0.145 (0.070) (0.086) (0.089) (0.077) (0.051) (0.070) (0.093) (0.089) (0.074) (0.094) (0.068) (0.184) (0.174)Non-metal 0.105 0.360 -0.145 0.218 0.116 -0.196 0.715 1.115 (0.286) (0.281) (0.268) (0.232) (0.327) (0.288) (0.610) (1.298)Iron 0.027 0.162 0.118 0.316** -0.089 -0.084 -0.170 -0.150 -0.282*** -0.175 -0.135 -0.181 0.154 (0.104) (0.116) (0.127) (0.125) (0.096) (0.111) (0.129) (0.127) (0.075) (0.134) (0.115) (0.293) (0.297)Electronics -0.030 0.194** -0.012 0.091 0.041 0.116** 0.076 0.086 -0.026 -0.143 -0.018 0.181 0.082 (0.078) (0.080) (0.092) (0.091) (0.051) (0.056) (0.090) (0.086) (0.085) (0.093) (0.059) (0.182) (0.194)Other machines 0.091* 0.195*** 0.085 0.032 0.014 0.123** 0.144* 0.011 -0.046 0.018 0.047 0.293* -0.016 (0.055) (0.069) (0.077) (0.076) (0.045) (0.049) (0.080) (0.078) (0.071) (0.077) (0.041) (0.155) (0.164)Indonesia 0.194*** -0.027 -0.124 0.192** 0.081** 0.138*** 0.473*** 0.334*** 0.103 0.234*** 0.097*** 0.739*** 0.235 (0.039) (0.082) (0.080) (0.082) (0.032) (0.044) (0.058) (0.055) (0.081) (0.052) (0.028) (0.163) (0.150)Philippines 0.211*** 0.053 0.145* 0.304*** 0.090*** 0.146*** 0.340*** 0.084 0.116 0.280*** 0.082** 0.823*** -0.807*** (0.041) (0.076) (0.076) (0.075) (0.035) (0.047) (0.070) (0.072) (0.077) (0.053) (0.034) (0.176) (0.171)Vietnam 0.236*** 0.131* 0.011 -0.030 0.056 0.084* 0.180** 0.340*** 0.075 0.092 0.054 0.498*** 0.857*** (0.041) (0.072) (0.076) (0.073) (0.036) (0.048) (0.077) (0.056) (0.075) (0.063) (0.033) (0.155) (0.151)Observations 371 374 371 374 371 374 374 371 374 374 371 374 368Pseudo R2 0.123 0.0846 0.0810 0.119 0.0932 0.111 0.148 0.123 0.0975 0.130 0.152 0.0618 0.0996Notes: The sample is restricted to firms adopted upon cutomers’ request. Marginal effect for binary probit estimation. Robust standard errors in parentheses. *** p<0.01, **p<0.05, * p<0.1. 22
  23. 23. Table 9: Relationship between Voluntary Adoption of International Standards and Performance (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) Binary Ordered Ordered domestic foreign defect inventory material labor quality flexibility lead-time pollution regulation outcomes profit market marketStandards 0.069 0.125** 0.178*** 0.090* 0.004 0.088** 0.188*** 0.107** 0.168*** 0.239*** 0.126*** 0.519*** 0.227** (0.047) (0.050) (0.051) (0.050) (0.039) (0.044) (0.053) (0.051) (0.050) (0.050) (0.035) (0.107) (0.109)SME -0.014 -0.070 -0.069 0.038 -0.065* 0.003 -0.036 -0.096* -0.142*** -0.049 -0.051 -0.197* -0.323*** (0.050) (0.052) (0.055) (0.050) (0.037) (0.048) (0.056) (0.053) (0.053) (0.055) (0.040) (0.110) (0.113)Local 0.024 0.075 0.058 -0.010 0.030 -0.007 0.102 0.010 -0.176*** 0.049 -0.004 0.025 0.149 (0.056) (0.059) (0.059) (0.056) (0.046) (0.051) (0.062) (0.058) (0.057) (0.061) (0.045) (0.126) (0.132)Food 0.076 -0.086 0.031 0.049 0.074 0.046 -0.077 0.013 -0.115* 0.057 0.138*** 0.023 -0.022 (0.069) (0.081) (0.080) (0.075) (0.050) (0.067) (0.082) (0.081) (0.069) (0.080) (0.043) (0.157) (0.170)Textile -0.012 -0.102 0.049 0.039 -0.022 -0.100 -0.111 -0.165** -0.088 -0.040 -0.072 -0.238 -0.611*** (0.071) (0.078) (0.078) (0.074) (0.060) (0.072) (0.079) (0.078) (0.069) (0.077) (0.065) (0.167) (0.167)Chemicals -0.020 0.042 0.141* 0.180** -0.021 0.048 0.061 0.019 0.045 0.139* 0.004 0.277 -0.329* (0.079) (0.082) (0.079) (0.085) (0.064) (0.067) (0.086) (0.084) (0.079) (0.078) (0.063) (0.185) (0.197)Non-metal -0.273* -0.026 0.091 0.093 -0.083 -0.205 -0.098 0.032 0.037 0.070 -0.096 -0.205 0.243 (0.163) (0.173) (0.178) (0.188) (0.141) (0.166) (0.172) (0.154) (0.138) (0.168) (0.145) (0.329) (0.381)Iron 0.068 -0.074 0.107 0.037 0.050 0.082 -0.159 -0.262** -0.179** 0.079 -0.034 -0.180 0.314 (0.104) (0.122) (0.117) (0.119) (0.075) (0.089) (0.112) (0.116) (0.080) (0.114) (0.097) (0.172) (0.288)Electronics -0.168* -0.160* -0.017 -0.164** -0.056 0.017 -0.209** -0.109 -0.017 -0.222** -0.042 -0.404** -0.397** (0.096) (0.096) (0.092) (0.067) (0.078) (0.084) (0.091) (0.098) (0.085) (0.092) (0.082) (0.179) (0.167)Other machines -0.066 -0.007 0.094 0.064 0.051 0.032 0.107 0.012 -0.055 0.027 -0.056 0.045 -0.283* (0.070) (0.074) (0.073) (0.070) (0.048) (0.061) (0.075) (0.074) (0.065) (0.073) (0.061) (0.147) (0.152)Indonesia 0.221*** 0.030 -0.050 -0.034 0.086* 0.239*** 0.433*** 0.337*** -0.037 0.186*** 0.111** 0.644*** 0.250* (0.050) (0.076) (0.077) (0.068) (0.046) (0.044) (0.060) (0.055) (0.075) (0.069) (0.045) (0.159) (0.147)Philippines 0.251*** 0.118 0.111 0.169** 0.049 0.130** 0.301*** 0.189*** -0.025 0.275*** 0.061 0.703*** -0.436*** (0.049) (0.073) (0.078) (0.077) (0.050) (0.053) (0.073) (0.067) (0.076) (0.065) (0.051) (0.185) (0.163)Vietnam 0.239*** 0.281*** -0.059 -0.204*** 0.076 0.147*** 0.382*** 0.375*** 0.069 0.012 0.051 0.510*** 1.133*** (0.055) (0.065) (0.072) (0.060) (0.048) (0.055) (0.069) (0.059) (0.071) (0.071) (0.050) (0.141) (0.146)Observations 490 490 490 490 490 490 490 490 490 490 490 490 481Pseudo R2 0.0609 0.0774 0.0392 0.0921 0.0262 0.0568 0.109 0.0992 0.112 0.0829 0.0648 0.0292 0.131Notes: The sample is restricted to firms adopted voluntarily. Marginal effect for binary probit estimation. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, *p<0.1. 23
  24. 24. Table 10: Comparison between Customer-requested and Voluntary Adoption of International Standards and Performance (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) Binary Ordered Ordered domestic foreign defect inventory material labor quality flexibility lead-time pollution regulation outcomes profit market market<Requested>Whole 0.114** 0.094 0.214*** 0.062 -0.012 0.142*** 0.219*** 0.192*** 0.171*** 0.195*** 0.147*** 0.603*** 0.072 (0.055) (0.062) (0.059) (0.060) (0.038) (0.053) (0.060) (0.061) (0.055) (0.060) (0.046) (0.126) (0.130)Local 0.093 0.124 0.252*** 0.112* -0.039 0.138** 0.126 0.140* 0.190*** 0.169** 0.101* 0.557*** 0.219 (0.069) (0.078) (0.074) (0.067) (0.057) (0.070) (0.078) (0.078) (0.063) (0.076) (0.057) (0.159) (0.158)MNC/JV 0.192* 0.048 0.189* -0.081 0.043 0.140 0.377*** 0.399*** 0.153 0.220** 0.242*** 0.702*** -0.215 (0.101) (0.098) (0.102) (0.117) (0.062) (0.088) (0.092) (0.116) (0.104) (0.101) (0.087) (0.217) (0.247)SME 0.096 0.075 0.198** 0.069 -0.009 0.144** 0.199** 0.243*** 0.129* 0.189** 0.191*** 0.601*** -0.117 (0.071) (0.081) (0.077) (0.075) (0.059) (0.070) (0.080) (0.079) (0.069) (0.079) (0.061) (0.160) (0.171)Large 0.121 0.091 0.210** 0.039 0.006 0.132 0.309*** 0.138 0.172 0.196** 0.107 0.637*** 0.343 (0.095) (0.101) (0.103) (0.101) (0.039) (0.083) (0.094) (0.103) (0.105) (0.099) (0.066) (0.226) (0.226)<Voluntary>Whole 0.069 0.125** 0.178*** 0.090* 0.004 0.088** 0.188*** 0.107** 0.168*** 0.239*** 0.126*** 0.519*** 0.227** (0.047) (0.050) (0.051) (0.050) (0.039) (0.044) (0.053) (0.051) (0.050) (0.050) (0.035) (0.107) (0.109)Local -0.065 0.081 0.162*** 0.067 -0.059 0.032 0.208*** 0.099* 0.178*** 0.228*** 0.082** 0.401*** 0.273** (0.056) (0.059) (0.059) (0.058) (0.047) (0.052) (0.060) (0.059) (0.056) (0.057) (0.042) (0.123) (0.127)MNC/JV 0.491*** 0.202* 0.244** 0.102 0.252*** 0.239*** 0.111 0.049 0.058 0.322*** 0.307*** 0.750*** 0.125 (0.101) (0.110) (0.115) (0.107) (0.088) (0.092) (0.115) (0.117) (0.115) (0.118) (0.085) (0.240) (0.234)SME 0.052 0.164*** 0.181*** 0.086 0.016 0.078 0.165** 0.082 0.233*** 0.250*** 0.166*** 0.573*** 0.293** (0.060) (0.062) (0.065) (0.064) (0.052) (0.056) (0.066) (0.065) (0.061) (0.061) (0.042) (0.142) (0.141)Large 0.143* 0.133 0.164* 0.120 0.003 0.089 0.248*** 0.124 -0.001 0.283*** 0.083 0.458*** 0.125 (0.086) (0.095) (0.092) (0.082) (0.058) (0.085) (0.092) (0.088) (0.092) (0.094) (0.073) (0.171) (0.187)Notes: Only estimated coefficients are reported. Marginal effect for binary probit estimation. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. 24
  25. 25. Distinct differences between adopted firms with and without customers’ requirement areobserved when the dependent variable is Inventory and Profit. When Standards is regressedon Inventories using the whole sample of adopted firms and the sample limited to adoptedMNCs and SMEs, the coefficient on Standards is significant at the 5%, 10%, and 1% levelrespectively. In contrast the coefficient is not significant for the firms adopted uponcustomers’ request. In the same manner, when Standards is regressed on Profit using thewhole sample of adopted firms and the sample limited to adopted local firms and SMEs, thecoefficient on Standards is significant at the 5% level. But the coefficient is not significant forthe firms adopted upon customers’ request. There results imply that firms voluntarily adoptedinternational standards tend to establish better inventory control and make profits than firmspassively adopted them. On the other hand, the firms accepted customers’ requirement may have betterachievement in the development of domestic market. There are differences in the significanceof estimated coefficients for MNCs/JVs and SMEs. The coefficient on Standards issignificant at the 1% level for MNCs/JVs and SMEs adopted international standards requiredby their customers but not significant for these two groups adopted them without therequirement.6. The Mechanisms for Adopting International Standards6.1. Empirical Strategy The regressions above indicate that the adoption of international standards will havepositive impacts on firm-level performance and whether firms have adopted them with orwithout requirements from their main customers will have different performances. It isimportant to understand characteristics of the firms who are required from their maincustomers to adopt international standards and actually adopted them. To explore this issue,the following model is developed: yi = α + β1∗Customeri + β2∗Capacityi +γ∗xi + ui. (3). The independent variables Customer are characteristics of and relationships with themain customer of firm (i). The variables Customer include customer’s nationality (MNC orJV), capital tie with customer, size of customer, frequency of shipping, JIT with customer,and human exchange. The variables Capacity are factors influential to capabilities anddecisions of firm (i) such as implementation of R&D, training programs for employees, top 25
  26. 26. management’s backgrounds, and academic background of engineers. Age of firm (i) may alsobe correlated with the capability and probability of adopting international standards. Detailson these variables are listed in Table 2 and Appendix Table A2. The control variables x inequation (3) are the same as those in equation (1). The following six binary variables are defied as dependent variable: Required bycustomer that is coded 1 if the firm (i) is required by its main customer to adopt internationalstandards and 0 otherwise; Adopted that is coded 1 if the firm (i) has adopted themirrespective of presence or absence of such requirement; Adopted upon request that takes thevalue 1 if the firm (i) has adopted them, responding to the requirement from its maincustomer; Voluntarily adopted that is equal to 1 if the firm (i) has adopted them even thoughit is not being required to adopt them by its main customer; Turn down request that is coded 1if the firm (i) is required and has not adopted them; and No request & Not adopted that iscoded 1 if the firm (i) is not required and has not adopted them. Binary probit estimations areapplied to these regressions.6.2. Results Table 11 summarizes the results of binary probit estimation. From the columns (1) to (6),capital tie with customer and monthly shipping of products are not relevant to therequirement from the customer and the adoption of international standards. From the columns(1) and (5), the firms that have SME customers are less likely to be required the adoption bysuch SME customers, so that they have fewer opportunities to turn down requirements. From the column (1), firms that have foreign-owned customers are likely to be requestedby their customers. But such firms do not necessarily adopt them as implied by the column(3). On the other hand, the significant coefficient on Foreign-owned customer in the column(4) suggests firms that have foreign-owned customers are more likely to adopt them withoutrequirement. The firms voluntarily adopted tend to have better production and logistic controls thatenable to make daily and weekly shipments as the significant coefficients on Ship a few timesin a day, Ship once in a day, and Ship a few times in a week are shown in the column (4). Thecoefficients on JIT with customer are significant for all of the regressions. As in the column(5), establishments performing JIT with their main customers are associated with a higherprobability of refusing customer’s request and negatively correlated to Adopted upon requestand No request & Not adopted. Thus firms with strong ability enough to develop a JIT systemwill make decisions on their own account, even if they are requested by their customers. 26
  27. 27. The similar implication to logistics capability can be derived from engineer exchange.The establishments that dispatch engineers to their customers tend to be requested but lesslikely to adopt them upon customers’ request. In contrast, those accept engineers from theircustomers are more likely to adopt upon request. Thus if it is assumed that more capablefirms dispatch their engineers, the establishments who dispatch engineers to their customersmay not adopt upon requests from less capable customers or may be able to turn downrequirements from the customers without fears to lose businesses. In the same way, theestablishments whose customers with stronger abilities dispatch engineers may have no otherchoice to adopt upon request. Among other variables relevant to firms’ capability, training programs for employees areinfluential to the establishments voluntarily adopt international standards as the positivecoefficients on OJT and OFF-JT significant at the 5% level in the column (4) are shown. Thevariable OJT is negatively correlated with the group Adopted upon request (column (3)). Topmanagement’s backgrounds and academic background of engineers are also important: Top isMNC-experienced and 20-40% of engineers are positively significant at the 5% and 10%level respectively for the regression of Adopted upon request; and Top is MNC-experienced ispositively significant at the 5% level for the regression of Voluntarily adopted. In sum, the establishments adopted upon a request has not enough capacity to performJIT, learn from customers through engineer exchange with the customers, do not have OJTprograms, and have a top management with engineering background and have higherpercentage of engineers who finished technical college and higher educations. Such betterengineering knowledge allows them to respond to customers’ requirement. Theestablishments voluntarily adopt international standards have foreign-owned customers, abetter production logistics control enable to make daily and weekly shipments and JIT,training programs that stimulate employees’ willingness to make improvements, and topmanagements who understand from working experiences in MNCs the importance ofmanagement systems that conform to international standards. The establishments that canrefuse a requirement from their customers have bargaining abilities against the customers,especially SME customers, which are backed up by technological and managerial edges onthe customers. The establishments without request and adoption have a lack of suchrelationships with customers and capabilities. It can be said, by comparing to the firmsrequested the adoption, that the establishments without request and adoption need to improvelogistics, create training programs, and dispatch engineers to learn from customers. 27
  28. 28. Table 11: Factors Influential to the Adopted of International Standards (1) (2) (3) (4) (5) (6) Required Adopted Turned No request Voluntarily by Adopted upon down & Not adopted customer request request adoptedForeign-owned customer 0.191*** 0.176*** -0.020 0.168*** 0.012 -0.191*** (0.059) (0.058) (0.043) (0.056) (0.037) (0.046)JV customer 0.208*** 0.052 -0.073* 0.122** 0.065 -0.131*** (0.058) (0.059) (0.038) (0.055) (0.043) (0.047)Capital tie with customer -0.064 0.000 0.030 -0.035 -0.025 0.031 (0.045) (0.047) (0.031) (0.037) (0.026) (0.043)SME customer -0.096** 0.017 0.041 -0.044 -0.047* 0.044 (0.043) (0.044) (0.033) (0.036) (0.026) (0.040)Ship a few times in a day 0.179** 0.179** 0.043 0.147* 0.036 -0.190*** (0.075) (0.072) (0.065) (0.077) (0.051) (0.049)Ship once in a day 0.132* 0.308*** 0.099 0.197** -0.047 -0.227*** (0.077) (0.060) (0.062) (0.078) (0.036) (0.044)Ship a few times in a week 0.097 0.107* -0.001 0.110* -0.009 -0.088* (0.063) (0.059) (0.045) (0.057) (0.035) (0.050)Ship once in a week 0.127* 0.047 -0.007 0.053 0.061 -0.095* (0.070) (0.070) (0.050) (0.064) (0.046) (0.056)Ship once in a month -0.008 0.064 0.085 -0.021 0.023 -0.073 (0.084) (0.088) (0.071) (0.071) (0.052) (0.071)JIT with customer 0.226*** 0.083* -0.057* 0.158*** 0.058** -0.157*** (0.042) (0.046) (0.032) (0.036) (0.025) (0.042)Dispatch engineer to customer 0.179*** -0.032 -0.101** 0.059 0.071** -0.070 (0.053) (0.056) (0.041) (0.044) (0.032) (0.053)Customer dispatches engineer -0.008 0.141*** 0.066* 0.049 -0.048* -0.081* (0.051) (0.049) (0.037) (0.042) (0.029) (0.046)R&D 0.052 0.073* 0.013 0.056 0.004 -0.063 (0.042) (0.043) (0.031) (0.036) (0.026) (0.039)OJT 0.129*** -0.003 -0.066* 0.079** 0.036 -0.033 (0.044) (0.046) (0.035) (0.039) (0.025) (0.042)OFF-JT 0.079* 0.103** -0.007 0.101** -0.031 -0.072* (0.045) (0.046) (0.034) (0.039) (0.027) (0.042)Top has master/Ph.D. 0.010 0.122** 0.048 0.053 -0.036 -0.071 (0.048) (0.048) (0.037) (0.041) (0.027) (0.044)Top is engineer 0.006 0.087* 0.063** 0.011 0.004 -0.077* (0.047) (0.046) (0.032) (0.038) (0.028) (0.044)Top is MNC-experienced 0.025 0.047 -0.027 0.071** -0.041 -0.009 (0.044) (0.045) (0.033) (0.036) (0.027) (0.042)20-40% of engineers 0.015 0.170** 0.152* 0.002 0.000 -0.170*** (0.084) (0.081) (0.082) (0.068) (0.048) (0.061)40-60% of engineers 0.042 0.140* 0.061 0.087 -0.033 -0.081 (0.090) (0.084) (0.074) (0.085) (0.042) (0.073)60-80% of engineers -0.123** -0.016 0.055 -0.065 -0.042 0.072 (0.061) (0.067) (0.056) (0.051) (0.031) (0.064)80-100% of engineers -0.035 0.101* 0.055 0.030 -0.055* -0.022 (0.058) (0.058) (0.047) (0.051) (0.031) (0.054)Age 0.000 0.005*** 0.002 0.002* -0.002* -0.003* (0.001) (0.002) (0.001) (0.001) (0.001) (0.002) 28
  29. 29. (Continue) (1) (2) (3) (4) (5) (6) Required Adopted Turned No request Voluntarily by Adopted upon down & Not adopted customer request request adoptedSME -0.050 -0.132*** -0.052 -0.054 0.014 0.121*** (0.045) (0.046) (0.034) (0.039) (0.028) (0.041)Local -0.070 -0.153*** -0.044 -0.094** 0.025 0.111** (0.051) (0.053) (0.043) (0.045) (0.031) (0.047)Food -0.005 -0.116 0.025 -0.144*** 0.109** -0.015 (0.071) (0.072) (0.054) (0.047) (0.053) (0.064)Textile -0.147** -0.158** -0.084* -0.070 -0.058* 0.219*** (0.067) (0.073) (0.044) (0.058) (0.031) (0.073)Chemicals 0.004 0.017 -0.034 0.052 -0.041 0.047 (0.066) (0.067) (0.044) (0.060) (0.034) (0.064)Non-metal -0.287*** -0.021 0.113 -0.108 0.250 (0.100) (0.158) (0.152) (0.092) (0.153)Iron 0.101 0.024 -0.046 0.085 0.019 -0.037 (0.097) (0.102) (0.058) (0.098) (0.061) (0.087)Electronics 0.100 0.072 -0.011 0.090 0.007 -0.094 (0.074) (0.076) (0.050) (0.068) (0.044) (0.065)Other machines 0.074 0.064 -0.037 0.093* -0.022 -0.032 (0.059) (0.059) (0.040) (0.053) (0.033) (0.053)Indonesia -0.142** 0.013 0.003 0.012 -0.101*** 0.161** (0.062) (0.068) (0.051) (0.057) (0.025) (0.067)Philippines -0.170*** -0.070 0.017 -0.052 -0.072** 0.197*** (0.062) (0.070) (0.054) (0.052) (0.030) (0.069)Vietnam -0.173** 0.062 0.181*** -0.074 -0.037 0.018 (0.070) (0.074) (0.065) (0.058) (0.038) (0.069)Observations 833 833 833 833 820 833Pseudo R2 0.209 0.236 0.117 0.262 0.0868 0.254Notes: Marginal effect for binary probit estimation. Robust standard errors in parentheses. *** p<0.01, **p<0.05, * p<0.1. 29
  30. 30. 7. Concluding Remarks This paper attempts to provide new evidence on the adoption and impact of internationalstandards by using unique firm-level dataset that was constructed by the questionnaire surveyconducted in Indonesia, the Philippines, Thailand and Vietnam in 2009. Among a hugeresearch questions discussed by related literature, this paper focuses on the following threeissues: (1) Which performance indicator has a significant relationship with the adoption of international standards? (2) Whether there are differences in the performance between firms adopted international standards voluntarily and those adopted upon requirements from their customers? (3) Searching factors influential to adopt international standards. The empirical results from probit estimations show significant relationships between theadoption and performance indicators. In particular, firms adopted international standards aremore likely to reduce environmental impacts caused by factory operations and meetregulatory requirements on products. They also take advantage of international standards todevelop domestic and overseas markets. But the relationship between the adoption and profitis not robust. Differences between firms adopted international standards upon a requirement from theirmain customers and adopted voluntarily are the most obvious in terms of inventorymanagement and profit. The latter group of the firms voluntarily adopted internationalstandards tend to establish better inventory control and make profits than the former group ofthe firms passively adopted them. Reflecting these empirical findings, firms adopted standards without customers’ requestship out cargos frequently, practice JIT with their customers and have top managementexperienced in MNCs, in addition to providing training programs to their employees. Suchfirms have better organizational characteristics that foster self-motivations and create andshare tacit knowledge among employees. On the other hand, firms adopted standards upon a requirement from customers havebetter engineering capabilities. The firms that can decline a requirement from their customershave bargaining abilities backed up by technological and managerial edges on the customers.The uncertified firms not even be required the adoption of international standards shouldreview logistic management, set up training programs, and dispatch engineers to learn fromcustomers. 30

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