• 제목/요약/키워드: price response

검색결과 459건 처리시간 0.032초

시계열 데이터를 활용한 항공 화물 물동량 영향 요인에 관한 연구 : 인천-상하이, 광저우, 톈진, 베이징을 중심으로 (A Study on the Factors Affecting Air Cargo Volume Using Time Series Data : Focusing on Incheon-Shanghai, Guangzhou, Tianjin, and Beijing)

  • 신승연;문승진;박인무;안정민;한용희
    • 산업경영시스템학회지
    • /
    • 제43권4호
    • /
    • pp.15-22
    • /
    • 2020
  • Economic indicators are a factor that affects air cargo volume. This study analyzes the different factors affecting air cargo volume by each Chinese cities according to the main characteristics. The purpose of this study is to help companies related to China, airlines, and other stakeholders predict and prepare for the fluctuations in air cargo volume and make optimal decisions. To this end, 20 economic data were used, and the entire data was reduced to 5 dimensions through factor analysis to build a dataset necessary and evaluated the influencing factors by multi regression. The result shows that Macro-Economic Indicators, Production/Service indicators are significant for every cities and Chinese manufacture/Customer indicators, Korean manufacture/Oil Price indicators, Trade/Current indicators are significant for each other city. All adjusted R2 values are high enough to explain our model and the result showed excellent performance in terms of analyzing the different factors which affects air cargo volume. If companies that are currently doing business with China can identify factors affecting China's cargo volume, they can be flexible in response to changes in plans such as plans to enter China, production plans and inventory management, and marketing strategies, which can be of great help in terms of corporate operations.

The Stimulus Factors Influencing Intention to Participate in Shopping during the Distribution of the 12.12 Online Shopping Festivals in Malaysia

  • MAHMUDDIN, Yasmin;ABDULLAH, Mazilah;RAMDAN, Mohamad Rohieszan;MOHD ANIM, Nur Aqilah Hazirah;ABD AZIZ, Nurul Ashykin;ABD AZIZ, Nurul Aien;YAHAYA, Rusliza;ABD AZIZ, Noreen Noor
    • 유통과학연구
    • /
    • 제20권8호
    • /
    • pp.93-103
    • /
    • 2022
  • Purpose: Online shopping festivals have quickly become the newest trend in online shopping worldwide due to the COVID-19 pandemic. This has led to marketing distribution channels that traditionally emphasized traditional techniques having turned to electronic commerce platforms. Although the pandemic scenario encourages online purchasing, other factors, such as the influence of participation intention to shop during the Online Shopping Festival, must also be considered. Research design, data and methodology: Multiple linear regression analysis was used to test the hypothesis based on data from 121 respondents who are actively involved with online shopping activities in Klang Valley, Selangor. Results: The results of this study show that promotion categories and the perceived influence of mass participation have a significant influence on participation intention. Meanwhile, the perceived temptation of price promotion and perceived fun promotional activities did not significantly influence participation intention. Conclusions: Theoretically, this study contributes to the literature by using the Theory of Planned Behavior and Stimulus-Response models to explain the factors that drive participation intention for online shopping. In practice, this study attracts and encourages customers to shop during the festival day because various attractive promotions are offered by sellers in Malaysia.

온라인 식품 구독서비스 특성이 지각된 가치와 고객인게이지먼트에 미치는 영향 (Effects of Online Food Subscription Economy Characteristics on Perceived Value and Customer Engagement)

  • 김차영;박철
    • 한국IT서비스학회지
    • /
    • 제21권2호
    • /
    • pp.1-26
    • /
    • 2022
  • This study classified five types of online food subscription economy: replenishment, curation, surprise, membership, and visitation. An online survey was conducted with 314 customers who experienced 5 types of online subscription economy. This study selected the characteristics of the food subscription economy as convenience, perceived personalization, economic utility, and timeliness through previous studies. The effect of the four characteristics on perceived value (utilitarian and emotional) and the relationship between customer engagement and perceived value, which are dependent variables that have never been used in the food subscription economy, were verified through the S-O-R model. In this relationship, we demonstrated how consumers' personal tendencies, such as need for cognitive closure and self-efficacy, mediate between timeliness and perceived value related to online food delivery. The study results are as follows. Perceived personalization, convenience, and timeliness had a positive effect on the utilitarian value in the order. It also had a positive effect on emotional values in the order of perceived personalization and timeliness. On the other hand, economic utility had no significant effect on practical branches. Customer engagement had a positive effect in the order of emotional value and utilitarian value. The lower the need for cognitive closure the more positive the utilitarian value. The lower the self-efficacy, the more positive the emotional value was perceived. Through the above study, companies that want to operate or start an online food subscription economy need a strategic approach rather than unreasonable price discounts in pricing policy. In addition, it is necessary to focus on marketing activities that provide emotional value by focusing on perceived personalization, which is the satisfaction factor of online food subscription.

근해 수산자원 증대사업의 경제적 타당성 평가 (Economic Valuation of the Off-Shore Fisheries Stock Enhancement Project)

  • 강석규;류정곤;심성현;오태건;임병권
    • 수산경영론집
    • /
    • 제52권2호
    • /
    • pp.1-31
    • /
    • 2021
  • This study is to evaluate the prior economic feasibility of the off-shore fisheries stock enhancement project. The main findings of this study can be summarized as follows: first, offshore fisheries stock enhancement project shall be implemented by dividing them into 1st·2nd·3rd projects for efficient promotion. The 1st·2nd·3rd projects will be conducted in a total of 50 locations (the eastern sea, the western sea, the southern sea, and the jeju sea areas), and the project period per unit will be five years, which will cost 1 trillion won. Second, according to the results of the survey on public awareness, the most consumed marine species in Korea over the past year were analyzed in the order of mackerel, hairtail, squid, yellow corvina, blue crab, and cod. The dominant response to the reason for consuming marine products in Korea was healthy well-being food and safe food. In addition, 67.9% of them have hesitated to purchase offshore fish species over the past year due to high prices, indicating that they are burdened by high prices. On the other hand, 79% of the respondents said that the government's policy was insufficient, according to a survey on whether the government's coastal marine resource creation policy was sufficient. Third, as a result of preliminary economic analysis of offshore fisheries stock enhancement project, the benefit-cost ratio is 4.01, net present price is 1,283.7 billion won, and internal rate of return is 91.7% per year, which means that the economic analysis ensures the feasibility of the projects. The results of this study provide useful information on securing or organizing budgets for offshore fisheries stock enhancement project by securing economic feasibility as a national infrastructure project that increases fishery income and public benefits such as consumption of marine products.

Market sentiment and its effect on real estate return: evidence from China Shenzhen

  • LI, ZHUO
    • 한국컴퓨터정보학회논문지
    • /
    • 제27권9호
    • /
    • pp.243-251
    • /
    • 2022
  • 부동산 산업은 경제와 높은 상관관계를 갖는 기초산업이다. 과거 20년 동안 중국경제성장을 가속화하면서 부동산 산업도 큰 변화를 보이고 있다. 이에 본 연구는 기존 경제성장지표인 GDP, 소득, 부동산 가격 및 금리 등 거시경제요인이 주택시장 가격상승을 종합적으로 설명하지 못한 점을 감안하여 행동경제학에서 심리지수가 주택시장에 미치는 영향을 분석한다. 방법론적으로 주성분분석법(PCA)을 활용하여 중국심천지역을 중심으로 부동산시장 수요자 심리지수 및 공급자 심리지수를 각각 도출하고 벡터자기회귀(VAR)모형을 통해 심리지수가 주택수익률에 대한 영향을 실증분석으로 진행한다. 그 결과 공급자의 심리는 주택시장에 긍정적인 영향을 미친 반면, 수요자의 심리는 부정적인 영향을 미치고 있다. 또한 공급자의 심리가 높은 경우에는 수요자의 심리가 높은 경우와 다른 영향을 미치고 있은 것을 밝혔다.

An Application of Machine Learning in Retail for Demand Forecasting

  • Muhammad Umer Farooq;Mustafa Latif;Waseemullah;Mirza Adnan Baig;Muhammad Ali Akhtar;Nuzhat Sana
    • International Journal of Computer Science & Network Security
    • /
    • 제23권9호
    • /
    • pp.1-7
    • /
    • 2023
  • Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

An Application of Machine Learning in Retail for Demand Forecasting

  • Muhammad Umer Farooq;Mustafa Latif;Waseem;Mirza Adnan Baig;Muhammad Ali Akhtar;Nuzhat Sana
    • International Journal of Computer Science & Network Security
    • /
    • 제23권8호
    • /
    • pp.210-216
    • /
    • 2023
  • Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

Simulation of a neutron imaging detector prototype based on SiPM array readout

  • Mengjiao Tang;Lianjun Zhang;Bin Tang;Gaokui He;Chang Huang;Jiangbin Zhao;Yang Liu
    • Nuclear Engineering and Technology
    • /
    • 제55권9호
    • /
    • pp.3133-3139
    • /
    • 2023
  • Neutron imaging technology as a means of non-destructive detection of materials is complementary to X-ray imaging. Silicon photomultiplier (SiPM), a new type of optical readout device, has overcome some shortcomings of traditional photomultiplier tube (PMT), such as high-power consumption, large volume, high price, uneven gain response, and inability to work in strong magnetic fields. Its application in the field of neutron detection will be an irresistible general trend. In this paper, a thermal neutron imaging detector based on 6LiF/ZnS scintillation screen and SiPM array readout was developed. The design of the detector geometry was optimized by geant4 Monte Carlo simulation software. The optimized detector was evaluated with a step wedge sample. The results show that the detector prototype with a 48 mm × 48 mm sensitive area can achieve about 38% detection efficiency and 0.26 mm position resolution when using a 300 ㎛ thick 6LiF/ZnS scintillation screen and a 2 mm thick Bk7 optical guide coupled with SiPM array, and has good neutron imaging capability. It provides effective data support for developing high-performance imaging detectors applied to the China Spallation Neutron Source (CSNS).

패밀리 레스토랑의 핵심${\cdot}$고품질${\cdot}$기본서비스 요인과 요인 별 고객관리 차별화 전략에 관한 연구 (Core${\cdot}$Quality${\cdot}$Basic Service Factors of Family Restaurants and Differentiation Strategy for Customer Service Management)

  • 박정영
    • 한국식생활문화학회지
    • /
    • 제23권2호
    • /
    • pp.184-193
    • /
    • 2008
  • The purpose of this study was to determine the detailed customer satisfaction and dissatisfaction factors of family restaurants in Korea, and to then classify the factors into 3 groups, inlcuding core service, quality service, and basic service. ‘Core service’ represents the critical factors that generate both satisfaction and dissatisfaction; ‘quality service’ generates only satisfaction; and ‘basic service’ generates only dissatisfaction. This categorization is based on Herzberg’s motivation-hygiene theory (1976) as well as Cadotte & Turgeon (1988). Based on the characteristics of the three groups, differentiation strategies in managing customer service were suggested to the family restaurant managers. A qualitative research method, termed the critical incident technique (CIT), was used in the study. This method helps researchers find new factors or attributes by grouping key issues from the anecdotes (critical incidents) and then categorizing common factors from the key issues. This research categorized key satisfiers and dissatisfiers into 33 factors, which were from 402 critical incidents described by 261 respondents. Eleven factors (response to service failures, food taste and quality, attention paid to customers, coupon/mileage point/discount card, customer’s ordinary requests, waiting, food diversity, food price, facility sanitation, checking out, customer’s special requests) were classified into core service, which required maximum management not regarding the level of customer satisfaction. Six factors (employee attitude, event, education and explanation, complementary food, customer’s mistakes, attention paid to children) were classified into quality service, which required differentiation strategy management. Finally, nine factors (speed of food service, employee’s mistakes, food sanitation, atmosphere and interior, seating, forcing orders, parking, other customers, reservations) were classified into basic service, which required minimum management at the level of the industry standards.

실물교란과 화폐교란이 양 대국 경제에 미치는 영향 (The Effects of Real and Monetary Disturbances and Economic Interactions between the Two Large Countries)

  • 손일태
    • 국제지역연구
    • /
    • 제15권1호
    • /
    • pp.31-58
    • /
    • 2011
  • 본 논문의 목적은 양 대국에서 발생하는 실물교란과 화폐교란이 양 대국 경제에 미치는 영향을 분석하고, 이를 통해서 양 대국 중 일국에서 실시하는 재정정책과 통화정책이 자국과 해외에 어떤 영향을 미치는지 알아보는데 있다. 또한 양 대국에서 결정되는 임금연동지수에 의해서 양 대국에서 발생하는 실물교란과 화폐교란이 자국과 해외에 어떤 영향을 미치는지도 알아보았다. 이를 위해 양 대국 경제모형을 구성하고 우선 이론적으로 분석하였다. 이론적 분석을 토대로 일본과 미국을 대상으로 실증분석을 하여, 일본과 미국에서 발생하는 실물교란과 화폐교란이 양국경제에 미치는 영향을 분석하였다. 또한 일본과 미국에서 결정되는 임금연동지수에 의해서 양국에서 발생하는 실물교란과 화폐교란이 양국경제에 미치는 영향을 분석하였다. 실증분석결과에 의하면 미국이 일본에서 발생하는 경제교란에 의해서 영향을 받는 것보다는 일본이 미국에서 발생하는 경제교란에 의해서 더 커다란 영향을 받는 것으로 나타났다. 결국 해외의 경제정책이 일국경제에 미치는 파급효과는 미국보다는 일본의 경우에 더 큰 것으로 나타나, 일본이 해외경제충격에 더 취약한 것으로 나타났다.