Integrated production and intermodal transportation planning in large scale production–distribution-networks

We present a model and solution approach for combining production and intermodal transportation planning in a supply network. A close and detailed integration of both decision fields is missing in the literature so far. The model includes relevant decisions regarding production setups and output volumes of plants, cargo consolidation at intermodal terminals, and capacity bookings for road and rail transports. A Branch-and-Cut method and heuristics are designed for solving the problem. A comprehensive case study for a chemical company identified a 6%-cost saving from the integrated planning. At the same time, companies are successfully supported in establishing eco-friendly distribution processes.     

An airline connection builder using maximum connection lag with greedy parameter selection

This paper introduces a methodology for designing an airline connection builder (CB) and adjusting its parameter settings. The objective of the proposed CB is to construct relevant connections that attract passenger demand while avoiding operationally infeasible and commercially irrelevant connections. Using worldwide MIDT booking data, we examined the sensitivity of CB results to the setting of the standard CB parameters maximum connection time and geographical detour. We demonstrated that CB performance can be increased by replacing these two parameters with connection lag, a measure that combines the impact of connection time with geographical detour on the total travel time of a given connection. We also found that the willingness of a passenger to book slower connections and the relationship between the number of passenger bookings and generated connections strongly depends on the O&D distance. Better results can thus be obtained by greedily determining the distance-specific CB parameter settings. The greedy adjustment of parameter settings reduces the number of unattractive connections generated, while keeping the number of covered passenger bookings high.     

A Linear Programming approach for robust network revenue management in the airline industry

The classical revenue management problem consists of allocating a fixed network capacity to different customer classes, so as to maximize revenue. This area has been widely applied in service industries that are characterized by a fixed perishable capacity, such as airlines, cruises, hotels, etc.It is traditionally assumed that demand is uncertain, but can be characterized as a stochastic process (See Talluri and van Ryzin (2005) for a review of the revenue management models). In practice, however, airlines have limited demand information and are unable to fully characterize demand stochastic processes. Robust optimization methods have been proposed to overcome this modeling challenge. Under robust optimization framework, demand is only assumed to lie within a polyhedral uncertainty set (Lan et al. (2008); Perakis and Roels (2010)).In this paper, we consider the multi-fare, network revenue management problem for the case demand information is limited (i.e. the only information available is lower/upper bounds on demand). Under this interval uncertainty, we characterize the robust optimal booking limit policy by use of minimax regret criterion. We present an LP (Linear Programming) solvable mathematical program for the maximum regret so our model is able to solve large-scale problems for practical use. A genetic algorithm is proposed to find the booking limit control to minimize the maximum regret. We provide computational experiments and compare our methods to existing ones. The results demonstrate the effectiveness of our robust approach.     

Platform coopetition in the tourism industry: conflicts and tensions caused by the closure of Booking.com in Turkey

In March 2017, as a result of a precautionary interim decision made by the courts based on the case relating to ‘unfair competition practices’, Booking.com closed its platform for inbound tourism in Turkey and ceased operations. This was the first instance of an online booking platform halting access for inbound bookings for the domestic market. This platform-based relationship involves both cooperation and competition, and thus this paper identifies this relationship as platform coopetition. Based on the governance network theory and employing a case-study approach, the Booking.com case is examined from the viewpoint of tourism coopetition from two perspectives: industry-wide and agent-specific. The paper provides an analysis of these perspectives and the past and on-going process of Booking.com’s platform closure. The constitutive dynamics this case endangers the coopetitive environment of the tourism industry and thus creates destructive uncertainties, especially for small hotels. This analysis also reveals the issues in terms of political representation for digital service platform companies.     

Air cargo revenue management under buy-back policy

Few researches address the application of financial “buy-back” concept in the air cargo revenue management. This paper examines the air cargo booking and execution procedure to measure the applicability of the buy-back policy in the air cargo revenue. By applying buy-back policy during the period of order release and order execution, a revenue model is built which incorporates Hellermann's capacity option model into the Black-Scholes pricing model. The results demonstrated that buy-back policy not only answers the questions of whether to buy-back, when to buy-back and how much to buy-back, but also increases the revenues of both asset provider and intermediary. Further study is extended in the overbooking and partial buy-back scenarios. The buy-back policy showed better performance in these two scenarios compared with current approach.     

Stochastic resource allocation for containerized cargo transportation networks when capacities are uncertain

We consider the stochastic resource allocation problem for containerized cargo transportation with uncertain capacities and network effects, in which a freight operator needs to allocate a certain amount of capacity to each product to maximize the expected profit. We formulate the problem as a constrained stochastic programming model and provide theoretical results that completely characterize the optimal solution to the model under a special case. Under a general case, we build an approximation model of the problem and propose a sampling based algorithm to solve the approximation model. A number of numerical experiments are offered to test the algorithm.     

Revenue management policies for the truck rental industry

In this paper, we consider the problem of managing a fleet of trucks with different capacity to serve the requests of different customers that arise randomly over time. The problem is formulated via dynamic programming. Linear programming approximations of the problem are presented and their solutions are exploited to develop partitioned booking limits and bid prices policies. The numerical experiments show that the proposed policies can be profitably used in supporting the decision maker.     

Customer perspective on overbooking: The failure of customers to enjoy their reserved services,accidental or intended?

Overbooking is widely applied in the service industry to hedge against undesirable situations, such as cancellations and no-shows. However, during the implementation of overbooking, service providers may turn down some customers when the number of arrivals exceeds their capacity on the target date. Therefore, this paper examines overbooking from the customers' perspective to offer them a clear perception on the possibility for their reservations to be denied by the service provider. By establishing a Stackelberg model between a service provider and an online travel agency, we explore how optimal overbooking strategy is developed by the service provider. Afterward, by analyzing the obtained optimal overbooking pad, we calculate the probabilities of denied service under different levels of monetary compensation that is paid to denied customers. A higher monetary compensation guarantees a higher chance of successful service. This paper also provides customers with some reference when booking services.     

Service charge and capacity selection of an inland river port with location-dependent shipping cost and service congestion

The inland waterway transportation has attracted a lot of attention worldwide in the last fifteen years. This paper studies the location, service charge and capacity decision of an inland river port to maximize its revenue or profit. The cargo shippers are assumed to be uniformly distributed along the inland river and can be shipped to the junction port via pure road transportation service or transshipment service with the inland river port. The natural heterogeneity of the river’ navigational condition is modeled by a location-dependent waterway transportation cost and the service congestion on the port is captured by the M/M/1 queueing model. We analytically investigate the properties of the optimal solutions for various decision problems associated with the inland river port. The effects of the natural heterogeneity and port service congestion of those optimal solutions are investigated. Those theoretical results are carefully examined in the case study of the Yangtze River.     

The decline of the traditional travel agent model

This article analyzes the struggle between traditional travel agencies and airlines to gain control of the Spanish airline services market. Also analyzed is the strong emergence of a third player, online travel portals that act as online travel agencies. We use a multinomial logit model to study the influence of 27 socio-economic factors and trip attributes on passenger purchase channel choice. The results show that the profile of a passenger who has a greater likelihood of making his/her bookings online is that of a young person, a student or educated to a high level, a habitual traveler, booking a simple journey and using an LCC. The factors linked to an increased likelihood of making purchases by phone include: being male, middle-aged, on a business or short trip, and the passengers usually use a travel agency. Finally, passengers who are over 65 years of age, with a lower academic level, who use a travel agency and are going to make a more complicated journey, are more likely to purchase their tickets in-store.     

In-transit perishable product inspection

We determine the value of monitoring perishable freight in-transit for a single vehicle traveling from an origin to a destination. We develop a computationally practical approach for determining the optimal expected cost function and an optimal policy, based on an infinite horizon partially observed Markov decision process model. Structural properties of the optimal expected cost function and optimal policy are determined. These results can lend insight when deciding whether to acquire the capacity to monitor freight status in transit and what actions to take, based on the data from the in-transit monitoring, that optimally increase expected supply chain productivity.     

Carrying capacity procurement of rail and shipping services for automobile delivery with uncertain demand

The determination of the optimal carrying capacity procurement of rail and shipping services in the automobile intermodal network with unique characteristics is essential to save automobile delivery cost. In this research we develop a two-stage stochastic programming model for the tactical-level decision problem arising in the special automobile intermodal network. Furthermore, we improve the sample average approximation algorithmic procedure to solve the model. We apply the model and solution method to a case study associated with the Shanghai Automobile Industry Corporation. We believe that this study deals with an emerging new research topic with practical significance for the automobile industry.     

A matheuristic approach to the air-cargo recovery problem under demand disruption

Air cargo transport is subject to unpredictable changes in expected demand, necessitating adjustments to itinerary planning to recover from such disruptions. We study a flight rescheduling problem to react to cargo demand disruptions in the short run. To increase flexibility, we consider two different cargo assignment policies. We propose a matheuristic approach to solve the problem that provides high-quality solutions in a short computational time, based on column generation in which each subproblem is solved using an ad-hoc heuristic. The approach is tested on demand disruption instances containing up to 75 air cargo orders with different penalty levels. The results show that the proposed method improves profit by 54% over the solution generated by a commercial MIP solver within a 1-h time limit, and by 15% over the solution with the routes fixed as in the original flight planning that only allows cargo to be re-routed. We also show that there exist incremental benefits in the range of 3–5% by allowing cargo for a given order to be transported by various aircraft.     

A GRASP algorithm for the container stowage slot planning problem

This work presents a generalization of the Slot Planning Problem which raises when the liner shipping industry needs to plan the placement of containers within a vessel (stowage planning). State-of-the-art stowage planning relies on a heuristic decomposition where containers are first distributed in clusters along the vessel. For each of those clusters a specific position for each container must be found. Compared to previous studies, we have introduced two new features: the explicit handling of rolled out containers and the inclusion of separations rules for dangerous cargo. We present a novel integer programming formulation and a Greedy Randomized Adaptive Search Procedure (GRASP) to solve the problem. The approach is able to find high-quality solution within 1 s. We also provide comparison with the state-of-the-art on an existing and a new set of benchmark instances.     

Recovering from demand disruptions on an air cargo network

In this work we introduce the Air Cargo Schedule Recovery Problem (ACSRP). In this problem, a carrier airline has to reschedule flights and requests to adapt to last-minute demand changes. We consider three different possible crew management policies that translate into three different way to evaluate the costs of deviating from the original schedule. We formulated the ACSRP as a mixed integer linear programming problem, and tested our implementation on 24 original schedules with up to 30 orders and 8 airports, and 4 different disruption scenarios for each one. Our results show that, against a benchmark recovery policy where only cargo is re-routed, recovery can yield savings of roughly 10%.     

Estimation of the occurrence of “short-shipping” of air cargo

Many airlines use the main deck of aircraft to carry passengers and belly capacity to accommodate cargo and baggage. When problems regarding the weight and balance requirements of the aircraft arise, the cargo is the first to be considered for unloading: a practice is known as “short-shipping”. This paper develops a simulation model for estimating the probability of occurrence of short-shipping. Risk analysis is used to estimate the uncertainty of several factors such as the weight of passengers, baggage, and fuel.     

Responses of air cargo carriers to industrial changes

This study examines how product characteristics, values, inventory cost, shipping charges, shipping distance, and time affect an international firm's choice of air carrier. An individual choice model is constructed by assuming that the shipper in a specific industry chooses the optimal air cargo carrier with the minimal logistics cost. The study further aggregates air cargo demands on different routes for the carriers by considering the spatial distribution of the origin-destination pattern and any temporal changes in the industrial structure. A case study is used to illustrate the application of the proposed model using data from Taiwan Taoyuan International Airport and the industrial economics database in Taiwan. The results show that shippers with high product value and short delivery distance focus on the shipping charge and prefer choosing the air cargo carrier that offers more flights. Further a carrier may achieve a larger market share if its supply attributes match the industrial structure and the product characteristics of the market on the route. Finally, because dynamic changes in the industrial structure and product value have been captured, the results are more accurate than that from the Grey model.     

The potential of horizontal collaboration in airport ground freight services

Since the global economic crisis of 2007–2011, the increasingly dynamic and challenging air cargo market in Europe has forced freight forwarders to improve their performance. In addition to improving their internal transport efficiency, they have also started to look at previously unexplored opportunities for horizontal collaboration in landside airport transport. The aim of this study is to reveal the potential of air cargo transport collaboration on a horizontal level, i.e. between multiple freight forwarders within a single airport. Reviewing existing literature on horizontal collaboration, with a focus on the air cargo industry, we propose a conceptual framework for transport collaboration in the air cargo industry. Based on a comprehensive study on air cargo transport movements within Schiphol, using a simulation model based on company data of 10,747 shipments (6977 tons of cargo) for a period of 30 days, we find several interesting results. Our main finding is that horizontal collaboration can improve the transport performance, by maintaining a high frequency of transport movements and maintaining an acceptable throughput time for air cargo shipments, and at the same time reduce transport costs by up to 40%. For smaller freight forwarders, the frequency of transport deliveries can even increase, while still allowing them to improve the average load factor of transport movements.     

Istanbul Airport (IGA) and quest of best competitive strategy for air cargo carriers in new competition environment: A fuzzy multi-criteria approach

Our paper determines the best competitive strategy that can be implemented by existing and potential air cargo carriers in the Turkish Air Cargo Industry with the operationalization of Istanbul Airport (IGA) and reveals the competitiveness level of the industry for four bases. We look at the competitiveness levels by analyzing the competitive environment of the industry nationally and internationally both before and post IGA (estimated). We use fuzzy TOPSIS (FTOPSIS) based on the Fuzzy AHP (FAHP) to handle vagueness, which is inherent in the nature of new competition conditions integrating the framework of Porter's five forces analysis. In our study, we use the five forces as our main criteria (with a total of 19 sub-criteria) and the competitive strategies as our alternatives. Our results reveal that the cost-focused strategy is the best competitive strategy that can be implemented by existing and potential carriers in the industry. Another significant result underscores the fact that IGA increases the competitiveness level of the Turkish Air Cargo Industry both nationally and internationally to a fairly high level. Also, the threat of potential competitors is first among the five forces in the industry's new conditions. Our study fills the gap in the literature on the effects of major structural changes in an air cargo industry on the competition among carriers.     

Financial Disclosure in the Travel and Leisure Industry

This study explores the determinants of Internet financial disclosure in the travel and leisure industry. Studying the case of the firms that are listed in the London Stock Exchange, we employ the generalized method of moments in order to investigate the cross‐sectional variation in the quantity of financial information, which is disclosed on corporate websites of travel and leisure firms. We find that disclosure is positively associated with corporate size, financial leverage, concentrated ownership, dual listing and profitability. We also discover that profitability is not only a determinant of financial disclosure in the travel and leisure industry but also its consequence: More profitable firms yield more requests for transparency among their stakeholders, and they also have the necessary resources to respond to these requests. Copyright © 2016 John Wiley & Sons, Ltd.