• Title/Summary/Keyword: Product Risk Management

Search Result 323, Processing Time 0.043 seconds

Factors Influencing the Reuse Intention of Social Commerce Foodservice Product - Perceived Risk and Price Consciousness - (소셜커머스 외식상품 재이용의도의 영향요인 - 지각된 위험과 가격의식성을 중심으로 -)

  • Jeon, Hyeon-Mo;Kwon, Na-Kyung
    • Culinary science and hospitality research
    • /
    • v.22 no.4
    • /
    • pp.114-127
    • /
    • 2016
  • The study, focused on social commerce food service consumers, attempted to test the relationship between perceived risk and price consciousness, and suggested that perceived risk and price consciousness, the the degree to which price is considered when purchasing goods, affect reuse intention. Through such test results, the study aimed to provide useful practical implications for establishing marketing strategies of companies related to food service social commerce, and those looking into behavioral intentions of social commerce using food service consumers. The subjects of the study were male and female residents of Korea over 2-years of age who have had some experience purchasing a dining out item through social commerce. The social commerce company selected for sampling was Coupang, which was the number 1 shopping App in 2014 based on the number of yearly visitors. A questionnaire-based survey was conducted on respondents who had indicated that they had experience purchasing foodservice goods through Coupang. The results revealed that source risk, privacy risk, psychological risk, and time-loss risk had negative influences on reuse intention. However, social risk and financial risk did not exhibit any influences. Price consciousness had positive influences on reuse intention. The study explored perceived risk and price consciousness as elements to affect continuous use of social commerce of foodservice consumers.

Innovation Strategy For New Product Development Process by Indicative Planning & QM Tools (유도계획과 QM 도구들을 활용한 신제품 개발과정의 혁신 전략)

  • Ryu, Ji-Hyun;Jung, Tae Wook;Song, In-Cheol;Oh, Hyun-Seung;Lee, Sae-Jae;Cho, Jin-Hyung
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.40 no.4
    • /
    • pp.78-86
    • /
    • 2017
  • The new businesses started by the companies usually results in being unsuccessful. The main reasons for that are either aiming targeting wrong customers, unsatisfaction of customers' requesting quality standards, or taking wrong actions against the competitors in the market. Therefore, companies should aim the targets for the newly developing products based on the fulfilling values for the customers when they start the new businesses, and should take good cares for risk managements at the each step of the new business to prevent the failure in advance. In addition to that, the companies starting new businesses not only need to take the customers attributes (CA) into account, but they also should apply the new technologies as one system to initiate a new business to satisfy the basic wants of the customers. This article suggests the New Product Development Pursuing Model using the Indicative Planning methodology and the Quality Management tools. The New Product Development Pursuing Model would be completed by the following steps as below; 1. Drawing the CTQ (Critical To Quality) for setting up the new product development objectives by : i) using the VOC (Voice Of Customers) obtained by the QFD (Quality Function Deploypment) if the market is mature, ii) applying AHP (Analytic Hierarchy Process) to information in the QIS (Quality Information System) if the market is unmature to get enough need information of the customers. 2. Risk Management in NPD : The NPD pursuing model consisted of the IP (indicative planning) is suggested not by the process of top-down-way mandatory planning process, but by the tools used in the administrative science and economic fields, namely by governance. The companies could apply innovative methodology for new products development processes to fulfil the customers satisfaction in the fields, through the CA (Contingency Approach) of the NPD (New Product Development) process.

Assessing Safety Requirements Based on KANO Model (KANO 모형 기반 안전요구사항 평가)

  • Sejung Lee;Seongrok Chang;Yongyoon Suh
    • Journal of the Korea Safety Management & Science
    • /
    • v.25 no.3
    • /
    • pp.9-15
    • /
    • 2023
  • As the first step of risk management, risk identification is inevitable to understand the degree of work safety. However, the safety requirements can be divided in necessary factors and additional factors. Thus, we propose a safety requirements assessment model using Kano model derived from Herzberg's two-factor theory, classifying safety requirements into ideal elements and must-be elements. The Kano model is usually applied to evaluate customer satisfaction divided into three major requirements in the fields of product development and marketing: attractive, must-be, and one-dimensional requirements. Among them, attractive requirement and must-be requirement are matched with ideal element and must-be element for safety requirement classification, respectively. The ideal element is defined as preventive safety elements to make systems more safe and the must-be element is referred to as fatal elements to be essentially eliminated in systems. Also, coefficients of safety measurement and safety prevention are developed to classify different class of safety requirements. The positioning map is finally visualized in terms of both coefficients to compare the different features. Consequently, the proposed model enables safety managers to make a decision between safety measurement and prevention.

Neutronic optimization of thorium-based fuel configurations for minimizing slightly used nuclear fuel and radiotoxicity in small modular reactors

  • Nur Anis Zulaikha Kamarudin;Aznan Fazli Ismail;Mohamad Hairie Rabir;Khoo Kok Siong
    • Nuclear Engineering and Technology
    • /
    • v.56 no.7
    • /
    • pp.2641-2649
    • /
    • 2024
  • Effective management of slightly used nuclear fuel (SUNF) is crucial for both technical and public acceptance reasons. SUNF management, radiotoxicity risk, and associated financial investment and technological capabilities are major concerns in nuclear power production. Reducing the volume of SUNF can simplify its management, and one possible solution is utilizing small modular reactors (SMR) and advanced fuel designs like those with thorium. This research focuses on studying the neutronic performance and radionuclide inventory of three different thorium fuel configurations. The mass of fissile material in thorium-based fuel significantly impacts Kinf, burn-up, and neutron energy spectrum. Compared to uranium, thorium as a fuel produces far fewer transuranic elements and less long-lived fission products (LLFPs) at the end of the core cycle (EOC). However, certain fission product elements produced from thorium-based fuel exhibit higher radioactivity at the beginning of the core cycle (BOC). Physical separation of thorium and uranium in the fuel block, like seed-and-blanket units (SBU) and duplex fuel designs, generate less radioactive waste with lower radioactivity and longer cycle lengths than homogeneous or mixed thorium-uranium fuel. Furthermore, the SBU and duplex feel designs exhibit comparable neutron spectra, leading to negligible differences in SUNF production between the two.

Study on Failure Classification of Missile Seekers Using Inspection Data from Production and Manufacturing Phases (생산 및 제조 단계의 검사 데이터를 이용한 유도탄 탐색기의 고장 분류 연구)

  • Ye-Eun Jeong;Kihyun Kim;Seong-Mok Kim;Youn-Ho Lee;Ji-Won Kim;Hwa-Young Yong;Jae-Woo Jung;Jung-Won Park;Yong Soo Kim
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.47 no.2
    • /
    • pp.30-39
    • /
    • 2024
  • This study introduces a novel approach for identifying potential failure risks in missile manufacturing by leveraging Quality Inspection Management (QIM) data to address the challenges presented by a dataset comprising 666 variables and data imbalances. The utilization of the SMOTE for data augmentation and Lasso Regression for dimensionality reduction, followed by the application of a Random Forest model, results in a 99.40% accuracy rate in classifying missiles with a high likelihood of failure. Such measures enable the preemptive identification of missiles at a heightened risk of failure, thereby mitigating the risk of field failures and enhancing missile life. The integration of Lasso Regression and Random Forest is employed to pinpoint critical variables and test items that significantly impact failure, with a particular emphasis on variables related to performance and connection resistance. Moreover, the research highlights the potential for broadening the scope of data-driven decision-making within quality control systems, including the refinement of maintenance strategies and the adjustment of control limits for essential test items.

A Model Development of Injury Prevention for Application in the Semiconductor Industry (반도체 산업에서의 재해 예방 모델 개발)

  • Yoon, Yong-Gu;Hong, Sung-Man;Park, Peom
    • Journal of the Korea Safety Management & Science
    • /
    • v.4 no.3
    • /
    • pp.1-11
    • /
    • 2002
  • It has been Management for stabilize Enterprise-Management for Economic demand for to Productivity, Automation, customer satisfaction, Especially Semiconductor-Industry has been, potential-risk in working to factory to machine equipment, all kinds of utility, gas, chemical, electronic, Fire. This study of basic-purpose has Research Different From as Follow to analysis and Solution For semiconductor product Factory of a actual point Data and specific-gravity to Relation for company-Injury. 1. It has been try to Injury-Tendency and cause-Analysis for our County-Manufacture-Occupation. 2, Semiconductor Injury of Actual-condition in Enforcement for problem and Analysis that Injury Problem has occupated it Submitted to Solution for ordinary Injury theory View to point Solve at for New Model has applicated to that nilem for processed to Solution.

The Impact of Perceived Risks Upon Consumer Trust and Purchase Intentions (인지된 위험의 유형이 소비자 신뢰 및 온라인 구매의도에 미치는 영향)

  • Hong, Il-Yoo B.;Kim, Woo-Sung;Lim, Byung-Ha
    • Asia pacific journal of information systems
    • /
    • v.21 no.4
    • /
    • pp.1-25
    • /
    • 2011
  • Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

Feasibility Evaluation of High-Tech New Product Development Projects Using Support Vector Machines

  • Shin, Teak-Soo;Noh, Jeon-Pyo
    • Proceedings of the Korea Inteligent Information System Society Conference
    • /
    • 2005.11a
    • /
    • pp.241-250
    • /
    • 2005
  • New product development (NPD) is defined as the transformation of a market opportunity and a set of assumptions about product technology into a product available for sale. Managers charged with project selection decisions in the NPD process, such as go/no-go choices and specific resource allocation decisions, are faced with a complicated problem. Therefore, the ability to develop new successful products has identifies as a major determinant in sustaining a firm's competitive advantage. The purpose of this study is to develop a new evaluation model for NPD project selection in the high -tech industry using support vector machines (SYM). The evaluation model is developed through two phases. In the first phase, binary (go/no-go) classification prediction model, i.e. SVM for high-tech NPD project selection is developed. In the second phase. using the predicted output value of SVM, feasibility grade is calculated for the final NPD project decision making. In this study, the feasibility grades are also divided as three level grades. We assume that the frequency of NPD project cases is symmetrically determined according to the feasibility grades and misclassification errors are partially minimized by the multiple grades. However, the horizon of grade level can be changed by firms' NPD strategy. Our proposed feasibility grade method is more reasonable in NPD decision problems by considering particularly risk factor of NPD in viewpoints of future NPD success probability. In our empirical study using Korean NPD cases, the SVM significantly outperformed ANN and logistic regression as benchmark models in hit ratio. And the feasibility grades generated from the predicted output value of SVM showed that they can offer a useful guideline for NPD project selection.

  • PDF

A Case Study on Product Production Process Optimization using Big Data Analysis: Focusing on the Quality Management of LCD Production (빅데이터 분석 적용을 통한 공정 최적화 사례연구: LCD 공정 품질분석을 중심으로)

  • Park, Jong Tae;Lee, Sang Kon
    • Journal of Information Technology Services
    • /
    • v.21 no.2
    • /
    • pp.97-107
    • /
    • 2022
  • Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.

A Study of Adoption of The Fourth Industrial Revolution New Products (4차산업혁명 신제품 소비자 수용에 대한 연구)

  • Kim, Moon-Tae
    • Management & Information Systems Review
    • /
    • v.38 no.2
    • /
    • pp.165-182
    • /
    • 2019
  • This study investigated the consumer acceptance process of the fourth industrial revolution new product to be introduced into the market in the future. The 4th Industrial Revolution new products are technological advances compared to the existing ones. The technology acceptance model that was used in the past has been modified to reflect variables like the social effects of the 4th Industrial Revolution, expected experience, and perceived risk. Modified models were proposed and verified. Six representative new products of the 4th Industrial Revolution were selected and examined by 40 respondents, and the hypotheses were verified using programs such as SPSS and AMOS. And conclusions and implications are as follows. First, the innovativeness of the fourth industrial revolution new products influences positive evaluation factors such as expected experience and perceived usefulness and it also affect positively to the perceived risk. In addition, the expected experience of the fourth industrial revolution new products has a great effect on the perceived usefulness and social influence, but it didn't affect to the perceived risk. Like the results of the TAM model, purchase intention of the fourth industrial revolution new products are strongly influenced by perceived usefulness. Finally, the perceived risk of the new product of the 4th Industrial Revolution had no statistically significant effect on the purchase intention, and the social influence of the 4th Industrial Revolution had a significant effect on the purchase intention. In general, respondents are highly aware of the social impact of the Fourth Industrial Revolution and seem to be very positive in this respect.