The objective of this study is to identify the priority of elements for effective implementation of MES in small and medium-sized manufacturing enterprises trying to develop into smart factories. For this purpose, the Delphi method and the Analytic Hierarchy Process(AHP) mothod are applied. As a result of the study, the cooperation of the members in the supply chain is the most important factor for small and medium-sized enterprises in order to survive in the global competitive environment. Therefore, the enterprises need to make various efforts to create synergies through the technical strength of suppliers and the cooperation in the process of introducing and operating MES.

Recently, as ESG management has become an important issue, major companies in the automotive parts manufacturing industry are conducting ESG evaluations of their suppliers for the purpose of supply chain management. The results of these evaluations are being incorporated into contractual agreements. However, many small and medium-sized enterprises(SMEs) are lacking in their capacity and resources to effectively respond to ESG evaluations. Furthermore, existing ESG management guidelines do not provide an industry-specific guidance, making it necessary to establish industry-specific guidelines that SMEs can refer to. Therefore, in this study, the evaluation Indicators of ESG supply chain assessments are surveyed, which is conducted by domestic major automotive parts companies and global automobile manufacturers. Then 56 supply chain ESG evaluation Indicators are derived. Also, ESG management indicators for SMEs is analyzed through the Importance-Performance Analysis(IPA), based on an interview of expert groups. Therefore, this study could propose industry-specific ESG guidelines, based on the results of the derived indicators, which reflects the need for SMEs to practice ESG management within certain boundaries.

As the 4th industrial revolution emerges, the implementation of smart factories are essential in the manufacturing industry. However, 80% of small and medium-sized enterprises that have introduced smart factories remain at the basic level. In addition, in root industries such as injection molding, PLC and HMI software are used to implement functions that simply show operation data aggregated by facilities in real time. This has limitations for managers to make decisions related to product production other than viewing data. This study presents a method for upgrading the level of smart factories to suit the reality of small and medium-sized enterprises. By monitoring the data collected from the facility, it is possible to determine whether there is an abnormal situation by proposing an appropriate algorithm for meaningful decision-making, and an alarm sounds when the process is out of control. In this study, the function of HMI has been expanded to check the failure frequency rate, facility time operation rate, average time between failures, and average time between failures based on facility operation signals. For the injection molding industry, an HMI prototype including the extended function proposed in this study was implemented. This is expected to provide a foundation for SMEs that do not have sufficient IT capabilities to advance to the middle level of smart factories without making large investments.

Recently, the Severe Disaster Punishment Act (January 27, 2022) was implemented, and the importance of industrial safety and health is being re-recognized. In addition, the reality is that the management burden is increasing, such as investing huge costs in reducing safety accidents centered on large companies. In this situation, we would like to help improve the working environment consistent with safety and health by deriving diagnosis and improvement measures for the current situation through a survey of production workers working in mid-sized and small-sized enterprises.

Developed countries that have experienced decline in productivity due to the economic crisis in the past have come to recognize the smart factory as an important means to strengthen the competitiveness of the manufacturing industry due to the increase in labor costs, the avoidance of the manufacturing industry, and the resolution of the shortage of skilled manpower. The necessity of nurturing manpower for self-maintenance was felt through identifying factors for successful smart factory introduction by companies and providing smart factory education. Therefore, the effects of educational satisfaction and operational competency on self-efficacy as a parameter and self-efficacy as a parameter were analyzed using research models and hypotheses to determine whether there was an effect between job satisfaction as a dependent variable. As a result of the analysis, it was found that the mediating effect of self-efficacy and self-efficacy on job satisfaction was found to have significant effects on operational competency and self-efficacy as parameters, as well as educational satisfaction and operational competency. The implication of this study is that continuous education and innovation activities are important in order to increase the business performance of companies, and through this, the manufacturing competitiveness of SMEs can be improved.

Smart factories can be defined as intelligent factories that produce products through IoT-based data. In order to build and operate a smart factory, various new technologies such as CPS, IoT, Big Data, and AI are to be introduced and utilized, while the implementation of a MES system that accurately and quickly collects equipment data and production performance is as important as those new technologies. First of all, it is very essential to build a smart factory appropriate to the current status of the company. In this study, what are the essential prerequisite factors for successfully implementing a smart factory was investigated. A case study has been carried out to illustrate the effect of implementing ERP and MES, and to examine the extensibilities into a smart factory. ERP and MES as an integrated manufacturing information system do not imply a smart factory, however, it has been confirmed that ERP and MES are necessary conditions among many factors for developing into a smart factory. Therefore, the stepwise implementation of intelligent MES through the expansion of MES function was suggested. An intelligent MES that is capable of making various decisions has been investigated as a prototyping system by applying data mining techniques and big data analysis. In the end, in order for small and medium enterprises to implement a low-cost, high-efficiency smart factory, the level and goal of the smart factory must be clearly defined, and the transition to ERP and MES-based intelligent factories could be a potential alternative.

The purpose of this study is to examine the relationship between internal corporate, supplier, and customer integrations for domestic SMEs on non-financial and financial performance through SCM performance such as flexibility and reduction of uncertainties. To this end, data was collected on 286 SMEs in Korea, and the structural relationships between SCM integration level, SCM performances, and management performance were analyzed. As a result of the analysis, first, it was found that the SCM integration level had a significant positive effect on the flexibility and reduction of uncertainties, which are SCM performances. Second, the flexibility and reduction of uncertainties showed significantly positive effects on the non-financial performance of the companies, but did not directly affect the financial performance positively. Third, the non-financial performance was found to have a positive effect on the financial performance. In addition, the SCM integration level did not have a direct effect on the financial and non-financial performance, but it was found that it affected management performance by mediating the flexibility and reduction of uncertainties, which are SCM performances. That is, although the SCM integration level did not directly affect financial and non-financial performance, it was confirmed that it affects management performance by mediating SCM performances, flexibility and uncertainty reduction. In other words, it was confirmed that the SCM integration level directly or indirectly affects SCM performances and overall management performance. These results imply the necessity to focus on competency in the supply chain management area according to the SCM performance expected by SMEs, and the step by step approaches to the expected effects. In a situation where prior SCM related studies have not been able to present SCM performances and management performance of SMEs that are relatively lacking in their capital and SCM construction capabilities, the findings of this study could suggest the importance of SCM integration from the perspective of SMEs. In addition, from the viewpoint of SMEs, this study suggested that a sequential approach for performance measurement is required (SCM performance → management performance) in relation to the performance factors to be established through SCM. 1

본 연구는 중소기업의 임원보수, 기업성과, 국제화에 대한 소유구조의 역할을 고찰한다. 소유와 경영의 엄격한 분리를 상정한 기존 문헌과 달리 소유와 경영이 중첩되는 임원의 주식소유에 주목한다. 임원 소유지분을 지배주주 소유지분과 분리․취급함으로써 임원보수, 기업성과, 국제화에 미치는 소유지분의 순효과를 임원과 지배주주의 몫으로 분해하여 측정할 수 있다. 이에 2014~2018년 기간 비금융산업에 속하는 국내 상장 중소기업의 공시정보를 활용하여 소유지분 및 임원보수가 기업성과와 국제화에 각각 어떠한 효과를 가져오는지를 주로 분석하였다. 주요 분석 결과는 다음과 같다: (1) 임원보수는 기업성과와 국제화에 직접 영향을 미치는 요인이며, (2) 임원 지분소유는 임 원보수와 양의 상관관계를 통해 간접 경로로 기업성과와 국제화에 영향을 주고 있으나, (3) 지배주주 지분소유은 기업성과 및 국제화에 직․간접 관계가 있다고 판단하기 어렵다. 이 결과를 통해 소 유와 경영의 일치가 기업성과와 국제화에 직․간접적으로 중요한 요소라는 점을 확인할 수 있다.

In this study, we analyzed the factors affecting the introduction of Smart Factory by domestic SMEs through AHP analysis and tried to provide implications for the introduction of Smart Factory. It was confirmed that the manufacturing and introduction group, the non-manufacturing introduction group, and the already introduced group had the highest weight in the cost reduction in the first hierarchy standard. At this time, it can be seen that the weight for cost reduction is relatively high in the manufacturing introduction group and the introduction group, and the weight for the productivity improvement is relatively high in the non-manufacturing introduction group. It can also be seen that the portion of marketing enhancement does not have a significant impact on smart factory choices. It was confirmed that image enhancement is the highest in the manufacturing introduction group and the non-manufacturing introduction group in the first hierarchy standard, and the marketing has the highest weight in the introduction group. In the two - tiered standard, customer - friendly and proper inventory maintenance weights were relatively high in all the introduced groups, except for the high rankings.

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

본 연구는 2011년과 2013년 중소기업기술통계 조사에 응답한 4,000개 기업 중 본사가 부산에 소재한 중소기업(5인 이상 300인 미만) 481개사를 대상으로 기업의 혁신전략에 따른 민간 연구개발 투자에 미치는 영향요인을 살펴보았다. 기업의 혁신전략과 관련해서는 R&D 포트폴리오, 연구개발조직 및 인력, 조직의 혁신전략 방향 설정자로서의 CEO 역할을 독립변수로 제시하였다. 또한, 산업을 제조업 기술수준별 4개 그룹과 지식서비스업 등 총 5개로 구분하고, 종속변수 민간 연구개발 투자비에 대한 영향을 선형 회귀 분석하였다. 이에 따른 분석 결과는 기업의 혁신전략 중 복합적인 R&D포트폴리오, 체계적인 연구조직 보유, 연구인력 증가는 모두 민간 연구개발비 투자에 정(+)의 영향을 미친다. 이를 산업별로 구분 하여 분석하여도 연구개발 조직과 연구인력 보유가 유의미한 영향요인으로 나타났다. 위의 결과를 살펴볼 때, 지역 중소기업의 민간 연구개발투자를 활성화하기 위해서는 다양한 R&D 포트폴리오를 갖추고 체계적인 연구개발 조직과 충분한 연구인력을 확보한 기업을 중심으로 R&D 투자가 확대할 수 있도록 산업별 특성을 고려한 정책 지원이 필요하다고 할 수 있다.

본 연구는 특허출원이 기업 성과에 영향을 미친다는 가정 하에 중소중견 기업을 위한 산업별 맞춤형 특허 활동성 제고 전략 5가지를 제안함으로서 향후 중소 중견기업의 특허활동 성과 제고에 기여하고자 하였다. 연구대상은 특허 활동이 활발한 25개 산업을 대상으로 2010년부터 5년간의 특허 활동성 통계자료와 2014년도 기준 기업성과 통계자료를 활용하였다. 연구절차는 DEA-BCC 효율성 분석과 특허 활동성 분석, 그리고 특허 포트폴리오 분석을 각각 실시한 후, 이를 종합한 특허 활동성 제고 전략을 제안하는 순으로 진행하였다. 연구 결과, 특허 활동성이 높고 IRS(규모 수익체증)형태를 보인 5개 산업의 경우, 특허 효율성이 높은 산업으로서 기업성과 향상에 실질적인 도움이 되고 있음을 확인하였다, 반면, 특허 활동성은 높으나 규모수익 이 IRS(규모수익체중)/DRS(규모수익체감)형태로 나타난 12개 산업을 비롯, 특허 활동성도 낮고 규모수익이 DRS(규모수익체감)형태, CRS/IRS 혼합형태, 그리고 IRS 형태 로 나타난 8개 산업 모두, 산업별 특성에 따라 특허 효율성도 다양한 형태로 나타날 수 있음을 확인하였다.

Small and Medium-sized Enterprises (SMEs) are being faced with rapid changes in their business environments due to evolution of technologies and innovation in societal eco-systems. Particularly, dynamic interactions between such environments and enterprise activities have become significant, so technology planning, which is a process of identifying appropriate directions regarding product and technology development, has received much attention to cope with such dynamics proactively. However, SMEs typically have limits in performing independent, strategical and systematical technology planning activities due to the lack of human, material and financial resources. This paper proposes the development of a product roadmapping method so that SMEs carry out efficient technology planning activities with interconnections of external business environments. The present work provides product roadmap templates that directly accommodate the influence of business environments on the product’s system and its associated super/sub-systems with the use of external environment analysis techniques including TRIZ methodology, PEST and 5Forces analysis. These templates are useful to efficiently forecast the directions of product’s development and evolution, which arise from changes in external environments. Consequently, the present work enables SMEs to flexibly cope with the era of the next R&D generation, which pursues value creation through mutual interconnection between business environments and technology development.

In this study, a correlation between execution of quality management activities and their results was verified by applying the Malcolm Baldrige model (hereafter referred to as the MB model) as a quality management performance measurement indicator for small and medium enterprises (SMEs) in South Korea. To achieve this goal, we need to determine whether the categorical requirements in the MB model are recognized consistently in SMEs, as a prerequisite. To this end, factor analysis was conducted for measurement variables in each category, which revealed that the process indicator was made up of six factors and the outcome indicator was made up of five factors, like those configured in the MB model. This result can be interpreted to mean that the requirements in each category of the MB model were well produced and recognized consistently throughout SMEs in South Korea. In addition, the analysis of causality between the process indicator (quality management activities) and the outcome indicator (management results) showed high causality between them. Although the quality management levels of SMEs in South Korea are inferior to those of conglomerates or other national quality award-winning companies, this study is significant in that the causality between quality management activities and results was verified, since this study targeted SMEs in South Korea as the target of investigation. Thus, it is empirically proven that the MB model can contribute to improved management results for SMEs in Korea.

As the competitiveness of SMEs (small and medium enterprises) is getting more and more improved and globalized, the government provides various consulting services to secure the competitiveness of small and medium firms and support stable growth. However, the assessment of the result from the government’s support is generally focused on non-financial factors, such as customer satisfaction and analysis of improvement effect. This paper is in regards to the statistical analysis of how much the government’s support in the form of providing consulting services contributes to financial outcomes in terms of profitability and growth. ROA (return on asset) and ROS (return on sales), which are investment profitability and sales profitability respectively, are chosen as an indicator of profitability. For analysis of growth, sales revenue and total asset growth are used. The samples are 44 corporations which are supported by government, and 150 corporations which are selected for comparison, with corporate growth support center program by the Ministry of Trade, Industry, and Energy chosen as the consulting model. After gathering the yearly balance sheets and income statements of the samples from CRETOP, Korea Enterprise Data, the analysis is conducted in the way of identifying the statistical significance of financial difference in the same period between corporates taking consulting services and corporates which have not, and the difference of financial outcomes from the corporates taking consulting services before and after consulting services. As a result, in terms of business growth, it is turned out to have positive difference both in growth ratio and profitability compared to the compared corporations at the significant level. Therefore, it is obvious that the consulting program which government provides to SMEs have direct influence practically to the corporates’ management performance.

Competitiveness of small and medium companies often rely on the competency of their employees. Many employees however try to move to better environments if possible, which results in high uncertainty in maintaining solid human resources. The purpose of this paper is to investigate the influencing factors of turnover intention and organizational loyalty of the early experienced, especially three to five years experienced, employees in the small and medium enterprises. A survey had been conducted using both LMX (Leader Member eXchange) and TMX (Team Member eXchange) as an effort to test the impact of strategic human resource management factors on turnover intension and organizational loyalty. It has been observed that the level of LMX is critical on the turnover intension, while the levels of LMX and TMX are positively related to the organizational loyalty. Especially significant mediation effect affects on the organizational loyalty for TMX via LMX in the serial structure. The human resource management factors become effective under the circumstances where leader and team members exchange activities are activated. These findings can be used in reducing turnover intention and increasing organizational loyalty of early experienced employees by enhancing the leadership training of middle level managers of the small and medium enterprises organizations. Besides, a set of active communication channels should be provided for the young employees so that they can share their work experiences and difficulties within the organization. The key results of this study may help the practitioners set up a management plan to maintain a low turnover rate for their organizations.

Smart Manufacturing Factory is a paradigm of the future lead to the fourth industrial revolution that led Germany and the United States. Now the automation of the production facility and won a certain degree, and through the process of integrating the entire process, including planning, design, distribution of information and communication technology products in emerging as a core competitiveness of the national economy. In particular, the company accelerated the smart factory building in order to improve the manufacturing industry, cost savings and productivity simply to incorporate internet of things(IoT),Robot, artificial intelligence, big data technology as a factory automation level of sophistication of the system and out to progress to the level that replaces human labor have. In this we should look at the trend of promoting domestic and foreign factories want to present these smart strategies for Korea.

This study aims to analyze the performance of the beneficiaries of the SMEs(Small and Medium Enterprises) support project that has been handled online on the 'BizOK System', which is the integrated support system for SMEs in Incheon, by comparing before and after receiving support. Various performance indicators can be used, but this study used the rate of increase in sales, exports and employed manpower collected by the 'BizOK System'. Moreover, to analyze the trend of business performance by corporate feature, this study grouped the businesses into 7 categories including sales, business history, number of employees and capital. The results of this study are expected to be used in drawing implications for business support policies by utilizing them as basic data for enhancing efficiency of the support project and establishing corporate policies.