• Journal of Smart Tourism
• /
• 제2권3호
• /
• pp.31-38
• /
• 2022

Understanding demand for travel websites can help hoteliers better evaluate their own multi-channel distribution and reputation management strategies. In this study, we estimated demand for eight major travel websites based on the user percentage in 3,120 U.S. counties. Results highlighted the importance of four types of factors: sociodemographic, economic, Internet use-related, and travel-related. Differences between websites were also compared based on estimated coefficients. For example, the demand for Expedia.com appeared to be driven by age, education background, income, and foreign travel history, whereas the demand for Hotels.com was driven by the proportion of the African American population and domestic travel history. Lastly, implications are provided.

• 대한교통학회지
• /
• 제27권6호
• /
• pp.167-176
• /
• 2009

교통수요관리(travel demand management)는 통행수요를 적절히 제어함으로서 교통혼잡을 최소화시키려는 목적으로 시행되는 제반 교통정책이라 할 수 있다. 교통수요를 적절히 관리하기 위해서는 먼저, 정책목표를 설정하고 이를 달성할 수 있는 최적의 정책변수들을 찾아야 하는데, 현재 이에 대한 연구는 미흡한 실정이다. 이런 측면에서 본 연구는 설정된 정책목표를 달성하기 위한 교통수요관리모형과 이를 풀기 위한 알고리듬을 제시한다. 교통수요관리모형은 2가지로 개발되는데, 첫 번째 모형은, 기점과 종점간 평균 통행시간을 대상으로 목표치를 설정한 후 이 목표치를 달성하기 위한 적정 통행수요를 구하는 문제이며, 두 번째 모형은 혼잡이 심한 특정한 지역을 대상으로 해당지역에 포함된 링크의 교통량/용량비가 일정한 목표수준을 유지되도록 하는 최적 통행수요를 구하는 문제이다. 간단한 예제 교통망을 대상으로 본 연구에서 제시한 모형들을 평가한다.

• 경영과학
• /
• 제25권1호
• /
• pp.93-106
• /
• 2008

This study is focused on the problem of seat allocation for group travel demand in airlines. We first explain the characteristic of group demand and its seat allocation process. The group demand in air travel markets can be classified into two types : incentive and package groups. Allocating seats for group demand depends on the types of group demand and the relationship between airlines and travel agents. In this paper we concentrate on the package group demand and develop an optimization model for seat allocation on the demand to maximize the total revenue. With some assumptions on the demand distribution and the linear approximation technique, we develop a mixed IP model for solving our problem optimally. From the computational experiments, we can find our optimization model can be applied well for real-world application.

• 한국경영과학회지
• /
• 제34권1호
• /
• pp.61-83
• /
• 2009

This study developed a variable demand traffic assignment model by stable dynamics. Stable dynamics, suggested by Nesterov and do Palma[19], is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with the user equilibrium model, which is based on the arc travel time function in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on congestion. It is therefore expected to be a useful analysis tool for transportation planners. In this study, we generalize the stable dynamics into the model with variable demands. We suggest a three stage optimization model. In the first stage, we introduce critical travel times and dummy links and determine variable demands and link flows by applying an optimization problem to an extended network with the dummy links. Then we determine link travel times and path flows in the following stages. We present a numerical example of the application of the model to a given network.

• 한국항만학회지
• /
• 제8권2호
• /
• pp.79-105
• /
• 1994

Today travel demand in the City of Pusan is increasing with the wide scope of activity and the better living circumstances as a big city with a population of about 4 million. Also, the transportation problem of Pusan city becomes one of the severest urban problems with travel demand increasing in spite of the continuous expansion of the transportation facilities. The purpose in this study is to find the travel characteristics on the arterial under the study, construct the optimal Transportation System Management(TSM) which could increase the travel capacity of the arterial based upon the optimal travel systems constructed. Thus, it was concluded that more emphasis should be of the automobiles into the Downtown areas, increase the travel capacity of the arterial through Mass Transportation System(MTS) including the HOV lanes or the Bus Exclusive Lanes instead.

• 대한교통학회지
• /
• 제26권5호
• /
• pp.163-174
• /
• 2008

기존의 4단계 교통수요추정 모형은 거시적인 장래 교통수요 예측을 위해 사용되어 왔으나 정확성에 대한 문제가 지속적으로 제기되어 왔다. 장래 수요추정의 정확성을 높이기 위해서는 신뢰성 있는 자료의 확보, 장래 사회 경제 지표의 예측의 합리성 등 근본적 해결방법이 있으며 모형의 추정방법을 달리하는 것도 상당히 중요한 해결방법이라 하겠다. 과거와 달리 교통수요추정 모형은 단순히 교통인프라 구축에 따른 교통수요추정과 같은 거시적인 분석뿐만 아니라 교통수요관리정책의 효과분석, 교통운영분석의 적용 등 미시적인 분석에 대한 요구가 증대되고 있다. 본 연구에서는 인간의 활동에 기반을 둔 활동기반 교통수요추정에 대하여 소개하며 통행자의 일일 활동에 대한 조사를 기반으로 한 시 공간 활동인구 추정을 통한 통행수요를 예측하였다. 연구결과 개별 건물단위의 시간대별 활동인구의 추정은 비교적 정확한 것으로 분석되었으며 예측된 통행수요 또한 정확성이 높은 것으로 나타났다. 본 연구의 결과는 인간의 활동에 기반을 둔 시 공간 활동기반모형은 거시적인 교통수요추정뿐만 아니라 미시적 추정이 가능하므로 다양한 미시적 교통체계분석에 활용될 수 있을 것으로 기대되며 이를 위해 활동기반 자료와 토지이용에 대한 공간자료(GIS)의 확보가 필수적이라 하겠다.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 1989년도 추계학술발표회 발표논문초록집; 이화여자대학교, 서울; 23 Sep. 1989
• /
• pp.5-5
• /
• 1989

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 2003년도 추계학술대회 및 정기총회
• /
• pp.239-242
• /
• 2003

The supply chain of the airline industry includes multiple airline companies, travel agencies and customers. Various air fares are offered by travel agencies. The travel agencies grant deposit to the airline company in advance and preoccupy seats with deep discount, which called group-discount-ticket. The group-discount-ticket offers the lowest air fare but it does not base on real demand. So the information flow generated by group-discount-ticket can cause the information distortion in airline supply chain. This study analyzes the bullwhip effect in the airline industry. A mathematical model is formulated and managerial suggestions is provided.

• 대한산업공학회지
• /
• 제32권1호
• /
• pp.61-73
• /
• 2006

This paper deals with traveling salesman problem(TSP) with the stochastic travel time. Practically, the travel time between demand points changes according to day and time zone because of traffic interference and jam. Since the almost pervious studies focus on TSP with the deterministic travel time, it is difficult to apply those results to logistics problem directly. But many logistics problems are strongly related with stochastic situation such as stochastic travel time. We need to develop the efficient solution method for the TSP with stochastic travel time. From the previous researches, we know that Q-learning technique gives us to deal with stochastic environment and neural network also enables us to calculate the Q-value of Q-learning algorithm. In this paper, we suggest an algorithm for TSP with the stochastic travel time integrating Q-learning and neural network. And we evaluate the validity of the algorithm through computational experiments. From the simulation results, we conclude that a new route obtained from the suggested algorithm gives relatively more reliable travel time in the logistics situation with stochastic travel time.

• 경영과학
• /
• 제17권2호
• /
• pp.87-95
• /
• 2000

This paper presents two analytical approaches to determine the vehicle fleet size for container shuttle service. The shuttle service can be defined as the repetitive travel between the designated places during working period. In the first approach, the transportation model is adopted in order to determine the number of vehicles required. Its advantages and disadvantages in practical application are also discussed. In the second approach, a logical network which is oriented on job is transformed from a physical network which is focused on demand site. Nodes on the logical network represent jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next job. Then a mathematical formulation is constructed similar to the multiple traveling salesman problem (TSP). A solution procedure is carried out based on the well-known insertion heuristic with the real world data.