Demand Segments Research Articles

Urban Air Mobility Passengers’ Profiling: Evidence from Milan Airports, Italy

Urban air mobility (UAM) is expected to offer new travel options for passengers to and from airports in the near future, despite uncertainties associated with regulatory issues, environmental concerns, and societal impacts. This paper analyzes the socioeconomic and behavioral factors that could influence users’ modal choices (including UAM services) for accessing and egressing airports. Using revealed and stated preference data collected at Milan airports (Italy), mixed logit and hybrid choice modeling specifications are estimated and compared with profile potential UAM passengers. Our findings suggest that the level of service, socioeconomic factors, and trip-related variables explain passengers’ choices better than latent traits such as fear of flying, propensity for technological advances, and expectations about the safety of UAM services. In other words, the additional complexity of hybrid choice modeling is not justified by the slight gain in likelihood compared with the estimated mixed logit model. The results also indicate that high-income individuals traveling for business purposes are the most likely demand segment to use UAM services, at least initially. Moreover, highly educated individuals and employees who have their travel expenses reimbursed for work trips are less likely to choose UAM services for airport access or egress, preferring traditional ground taxis.

A COMPARATIVE STUDY OF HEADWAY-BASED AND TRANSPORT SYSTEM-BASED ASSIGNMENTS OF PUBLIC TRANSPORT IN VISUM: THE CITY OF KRYVYI RIH CASE

Many researchers have explored public transport assignment methodologies employing transport modelling software. Nevertheless, there remains a gap in evaluating real-world public transit networks utilizing diverse assignment procedures within Visum software. This paper introduces a thorough comparison of algorithms involved in public transport assignment processes, using the transport model of the city of Kryvyi Rih in Ukraine. The three scenarios of the model were developed depending on the public transport assignment procedure: headway-based, transport system-based utilized to all links, turns, and major turns in the network graph, and transport system-based applied only to the links, turns, and major turns traversed by the active public transport lines. The model of the network comprises 13 transport systems, 7 transport modes, 27598 links, 10097 nodes, 83270 turns, 238 zones, 1748 connections for private transport, 3013 connections for public transport, 534 stops, 1165 stop areas, 1190 stop points, 130 lines and 218 line routes. The transport demand model encompassed 14 demand segments. Compared to the outputs of the model calculation using the headway-based procedure, in the scenarios with transport system-based assignment, passenger flows on rail tram lines significantly decreased. Also, the results of scenarios with transport system-based assignment showed that the passengers extremely use parallel streets for travel from an origin to a destination. The modelling outputs for an actual urban network illustrate that the choice of the shortest route in the transport system-based assignment is closely linked to the main urban roads. This circumstance could potentially result in a rise in the number of transfers needed to sustain accessibility to districts residing far from the central highway.

High-Speed Rail in Tourism: Demand Segments and Factors of Their Potential Transition to Alternative Modes of Transport

High-Speed Rail in Tourism: Demand Segments and Factors of Their Potential Transition to Alternative Modes of Transport

Reorganization of human resources in the tourism industry from the perspective of recent years, in relation to Transylvania

Nowadays, employment in various economic fields and the possession of appropriate professional knowledge are of considerable importance, especially in the services sector, where properly qualified personnel is a key factor in terms of the development of satisfaction in the demand segment. As an apropos of this, the human resource reorganizations taking place in the Transylvanian region and the willingness to work form the subject of the research, focusing on the tourism industry, which was a difficulty for businesses providing various services during the period of the Covid-19 epidemic that spread in 2020. In a significant part of the international studies related to the topic, the difficulties arising because of the change in the attitude of the tourist human resources are mentioned, which can lead to a disadvantageous situation in the long term of the operation of tourist facilities. As a result, the sixteen Romanian counties that make up the Transylvania region became the target of the investigation. Projected on the mentioned counties, relevant data from the Romanian National Statistical Institute (INSSE) were first used, examining the time interval between 2010 and 2022, both yearly and monthly. According to the data used, it is important to focus on the investigation of tourist traffic, as well as on the number of people employed in the sector and its change, as well as on the wages received for doing their work and the associated benefits, which can serve as a motivational factor in addition to valuing employees. An examination of the data related to the topic shows that the 2008 global crisis had a more drastic impact on employment in Romania than the Covid-19 pandemic that spread in 2020, the effects of which can still be felt today.

Segmentation by motivations in religious tourism: A study of the Christ of Miracles Pilgrimage, Peru.

The present study, focused on pilgrimages as part of religious tourism, aimed to achieve the following objectives: Identify the motivations of the demand for religious tourism focused on pilgrimages; analyze the segmentation of the demand; identify the relationship between demand segments with satisfaction and loyalty; and establish the sociodemographic aspects that characterize demand segments. The study was conducted during the Pilgrimage of the Christ of Miracles in Lima, Peru. The sample was taken on-site from 384 tourists. The statistical techniques used were factor analysis and the k-means clustering method. The results reveal five motivational dimensions: Religious Experience, Belief Experience, Escape, Touristic Experience, and Shopping. Three attendee segments were also identified: Believers, related to belief experience; Religious, related to religious experience; and Passive, tourists with low motivations. The Religious segment had the highest satisfaction and loyalty levels among these groups. Sociodemographic differences were also found in the demand segments. The findings will contribute to management guidelines for destination administrators with religious events and provide insights into academic literature.

Direct and moderating effects of COVID-19 on cultural tourist satisfaction

This paper proposes a model to determine the direct and moderating effects of COVID-19 on the overall satisfaction of cultural tourists with the heritage destination visited. The hypotheses put forward in the model have been tested employing non-linear structural equation models (SEM), estimated with data from the Resident Travel Survey of the National Statistics Institute (NSI), on domestic demand for cultural tourism in Spain. The data analyzed covers both a pre-covid and pandemic period, from January 2019 to September 2021. The results confirm that COVID-19 significantly impacted the decrease in cultural tourists' satisfaction with the visit. It highlights the negative relationship between cultural tourists' socioeconomic profile and satisfaction. This research provides knowledge on the impact of COVID-19 on the behavior of cultural tourists, with practical implications for the design of tourism policies for the promotion and marketing of heritage destinations through differentiated marketing that increases satisfaction for this demand segment in crisis scenarios.

Airline revenue management with segmented continuous pricing: methods and competitive effects

With the introduction of IATA’s New Distribution Capability (NDC), airlines will no longer be limited to discrete fare classes for their fare product distribution but could show fare quotes from continuous ranges to booking requests. NDC will also allow airlines to present different fare quotes to passengers from different demand segments as identified by the airline. In theory, airlines can better extract passenger willingness to pay, and thus, see gains in revenue, by offering segmented continuous fare quotes to different passengers requesting to book. This paper describes the revenue management (RM) methods for Segmented Continuous Pricing and examines their potential effects on airlines’ revenue through simulations in the Passenger Origin–Destination Simulator (PODS). We describe a class-based algorithm for continuous pricing, a straightforward extension from the traditional methods used with existing RM systems. Our simulation results show that in a calibrated scenario in which only one airline adopts Segmented Continuous Pricing and has an 80% accuracy in identifying business versus leisure passenger booking requests, the first-mover airline can see as much as a 17% revenue gain, at the expense of competitors. The revenue gains come primarily from the leisure passenger segment by offering lower fares than competitors closer to departure. The first-mover airline loses bookings but does not see losses in revenue from the business passenger segment. We also explore potential response strategies by the competing airlines. We discover that competitors can reverse the first-mover’s revenue gain by removing their fare restrictions while still using traditional RM methods. We conclude that although adopting Segmented Continuous Pricing is promising in theory, its gains in practice will depend heavily on the competitive situation and the responses made by competing airlines.

Pricing in Russian Universities: How Do Competing Universities Infl uence Tuition Fees?

The paper analyzes the pricing strategies of Russian state universities in the context of the competitors’ influence over the tuition-paying education market. The aim of the study is to find out how competition in local higher education markets affects the pricing strategies of Russian state universities. The empirical basis of the study is formed by the data of the Monitoring of Enrollment Quality at Russian Universities implemented by National Research University Higher School of Economics. With the help of pattern analysis methods (order-fixed and order-invariant pattern clustering), homogeneous groups of universities are identified taking into account indicators, which characterize the scale and quality of admission to bachelor and specialist programs. On the example of technical programs, the authors demonstrate the regression model for predicting the 2011–2019 education prices in universities of corresponding homogeneous groups. The results show that each homogeneous group of universities has one or several market leaders who serve as benchmarks for other universities in that group when setting tuition fees. At the same time, university pricing strategies involve orienting towards market leaders in their demand segments and specialty groups. The identified features confirm that competition among universities for students and funding leads to the appearance of market leaders in certain market niches. In some groups of universities, there are clear market leaders at the local and regional levels who have a significant lead over competitors due to the peculiarities of state policy and high heterogeneity of the Russian educational landscape.

Demand segmentation and sociodemographic aspects of food festivals: A study in Bahrain.

Food festivals have been a growing tourism sector in recent years due to their contributions to a region's economic, marketing, brand, and social growth. This study analyses the demand for the Bahrain food festival. The stated objectives were: i) To identify the motivational dimensions of the demand for the food festival, (ii) To determine the segments of the demand for the food festival, and (iii) To establish the relationship between the demand segments and socio-demographic aspects. The food festival investigated was the Bahrain Food Festival held in Bahrain, located on the east coast of the Persian Gulf. The sample consisted of 380 valid questionnaires and was taken using social networks from those attending the event. The statistical techniques used were factorial analysis and the K-means grouping method. The results show five motivational dimensions: Local food, Art, Entertainment, Socialization, and Escape and novelty. In addition, two segments were found; the first, Entertainment and novelties, is related to attendees who seek to enjoy the festive atmosphere and discover new restaurants. The second is Multiple motives, formed by attendees with several motivations simultaneously. This segment has the highest income and expenses, making it the most important group for developing plans and strategies. The results will contribute to the academic literature and the organizers of food festivals.

Designing a centralized distribution system for omni‐channel retailing

We study the optimal supply chain design for a dual‐channel retailer that operates physical and web‐based stores and has traditionally managed each one separately. With increased pressures from customers and decreased profits due to marked‐down leftover inventories in each channel, the retailer considers integrating the supply chain operations of both channels and using in‐store inventory more effectively across different channels. In contrast to the existing literature, we focus on the firm's choice of the best omni‐channel strategies considering demand segmentation, cost structure, and, more importantly, the inventory rationing ability of the firm. We formulate our problem as a two‐stage stochastic programming model and use first‐order optimality conditions to study the optimal inventory ordering decisions. Based on different omni‐channel strategy decisions, we explore four supply chain design options. We identify the optimal inventory ordering policy under each option and explicitly describe the optimality conditions on cost and demand under perfect and imperfect demand information. When the demand information is imperfect, the demand fulfillment decisions can be characterized as nested protection‐level policies. First, we show that omni‐channel strategies are not necessarily profitable under all settings as dictated by market conditions. Second, we demonstrate that when the company can allocate its inventory perfectly, running omni‐channel strategies may help better serve web‐based customers and in‐store customers. Finally, we show that, in the worst case, the imperfect demand information may result in losing all the claimed inventory integration benefits when running omni‐channel strategies.

Design of a sales plan in a hybrid contractual and non-contractual context in a setting of limited capacity: A robust approach

Many companies face capacity limitations that impair them to satisfy potential demand. In this context, sales/marketing teams have to decide which demand segments the company should prioritize. In business-to-business contexts, it is common that this selection includes customers with and without a contract. On the operations side, the production teams are interested in finding the most efficient usage for the available capacity. However, decision-making approaches to face such a challenge are scarce. In this paper, we propose a scenario-based robust optimization model to support the sales and marketing teams to define the most profitable sales plan in a setting of limited capacity, to serve multiple customers that can be either non-contractual or operate under quantity-flexibility contracts. The proposed model integrates contract design, portfolio selection, and tactical production planning decisions. By employing our model, we are able to quantify how a product’s inclusion in a contract relates not only to its own profitability but also to the profitability of the remaining products that might be offered to the customer using the same resources. Regarding the optimal flexibility level to offer to a customer, it is explained by the expected sales volume, the discount rate depending on the flexibility level, and the demand variability expectation. We expect this approach supports industrial companies in defining the mid-term sales plan and deciding on the conditions to offer to contract customers.

Sources of price elasticity of demand variability among Spanish resort hotels: a managerial insight

设计/方法/途径该论文评估了位于西班牙不同目的地的七家四星级度假酒店在旺季期间的在线需求函数。比较不同的价格弹性值, 分析影响价格弹性的不同因素。研究目的本文的目的是使用需求行为估计来找出西班牙不同目的地度假酒店价格变化的来源。研究发现主要调查结果表明：（1）大多数旺季期间的需求弹性, 但诸如度假村的中心位置、最近的翻新、额外设施/服务的可用性以及针对夫妻和/的酒店等因素或半食宿使需求更加缺乏弹性; (2) 特内里费酒店的价格弹性需求最大; (3) 在离入住日期最近的预订期间, 需求通常更具弹性; (4) 更多的本地竞争者压低了酒店价格。研究原创性/价值本论文强调了酒店经营者应关注更有利可图的需求细分市场的管理意义。研究发现对于开发旨在改进预测的收益管理软件特别有价值。

Pioneering digital platform ecosystems: The role of aligned capabilities and motives in shaping key choices and performance outcomes

AbstractResearch SummaryWe inductively analyze rich qualitative and quantitative data on the global census of pioneering mobile money firms to examine how firm characteristics shape digital platform ecosystem configuration choices regarding (a) internal versus external integration and (b) the creation of network externalities through open versus closed end‐user access. In contrast to received wisdom, we find pioneering firms were equally likely to engage in external and internal integration; moreover, diversifying entrants were less likely to internally integrate than startups. We uncover the important role of motives, in addition to capabilities, for creating alignment between pioneering firms and their partners. Such alignment was key for addressing path‐dependent implementation challenges through experimentation and navigating nascent industry uncertainty for success.Managerial SummaryOur study showcases how enterprising firms pioneered and diffused mobile money, a digital platform that improves access to financial services. The successful take‐off and growth of this industry, as revealed by our inductive analysis, was contingent on aligned capabilities and motives among platform co‐providers and critical partners. We illuminate why and how pioneer capabilities and motives influenced key platform choices regarding internal versus external integration, and open versus closed end‐user access. These choices then created different implementation challenges. The successful pioneers navigated these challenges to create a robust ecosystem for network effects by engaging in two actions: they developed lasting partner relationships, and they experimented to determine distinct demand segments, identify unmet needs, and develop value propositions.

Should antitrust regulators be wary of inter-firm coordination agreements through a tourism destination card?

Inter-firm coordination agreements through a destination card (DC) are a widespread profit-increasing strategy in tourism destinations. Literature on tourism economics argues that this type of coordination increases social efficiency. However, industrial organization studies consider heterogeneous consumers and warn that a DC-type agreement can be welfare impairing. Conflicting views have become an issue for tourism destinations, as collusion is in the crosshairs of antitrust regulators. This paper aims to clarify these contradictory results by developing a duopoly model with heterogeneous tourists. A sensible demand structure is assumed which, unlike previous literature, includes loyal demand segments. A policy prescription is obtained, namely, a DC alliance is welfare enhancing if DC price is equal to or lower than the cost of joint consumption under no coordination. However, a greater total surplus in markets may be accompanied by a reduction in consumer welfare, which differs from the conventional view in tourism economics.

Optimal targeting of latent tourism demand segments

This paper identifies for the first time the optimal target markets employing the latent tourism demand expenditure, a novel concept in tourism literature. The study quantifies latent tourism demand between each pair of origin-destination through distinguishing by type of tourism and seasonality. It works with market shares that are estimated via a fractional regression model. Moreover, latent demand is clustered using a market segmentation approach based on a latent class regression. Finally, the optimal target markets are chosen depending on the expected latent tourism expenditure. The result has clear policy implications in terms of which markets are promoted, the optimal channels of communication and the maximum budget for each marketing campaign.

Demand Segmentation in the Federal Funds Market

This paper outlines a model of demand segmentation in the federal funds market with two types of borrowers - the "interest on reserves (IOR) arbitrage'' type and the "regulatory'' type - which have different reservation prices and cannot always be separated. When fed funds trade above IOR, the "regulatory" type is revealed and consequently pays an interest rate closer to its real reservation price, pushing the fed funds rate further up. When fed funds trade below IOR, a decrease in the fed funds rate encourages entry in the market for IOR arbitrage purposes thus counteracting the downward pressure on the fed funds rate. We use probit regression models and daily data for the period April 2018 to February 2020 to provide empirical support for this model. We find the following: 1) When fed funds trade above IOR, there is, on average, a 10 percentage points increase in the probability that the fed funds rate increases the following period. Furthermore, analysis using confidential bank-level data shows that this increase in the probability is higher for banks that report their liquidity profile daily and that were present all trading days during this period. 2) When the fed funds trade below IOR, the probability of a decrease in the fed funds rate decreases with the widening of the spread between the fed funds rate and IOR.

Efficient subsidy distribution for hydrogen fuel cell vehicles based on demand segmentation

The transportation sector paradigm is being changed to achieve carbon neutrality by 2050. Governments have been actively providing subsidies as part of the effort to replace existing internal combustion engine vehicles with alternative fuel vehicles (AFVs). However, subsidization is not a sustainable approach. Some countries, including the United States, the United Kingdom, and China, are reducing AFV subsidies. Meanwhile, Korea, which ranks first in the global market share for hydrogen fuel cell vehicles (HFCVs), provides insufficient HFCV subsidies. Therefore, this study redefines demand to better distribute these limited subsidies. Demand is segmented into “new demand” and “transferred demand” according to the pattern of demand transfer; the effective subsidy level for each demand segment is discussed. We find that to maximize reductions in CO2, the most effective purchase subsidy is 70 % for transferred demand and 90 % for new demand. In addition, the most cost-effective purchase subsidy combination is 10 % for transferred demand and 60 % for new demand.

Main trends and development forecast of bread and bakery products market

Bakery products are very important in human nutrition and are the basis of any daily diet. Their social significance is determined by the traditions and habits of the population of the countries, accessibility for all groups of the population, diverse assortment, including bakery products for functional and specialized purposes. The up-to-date trend is to expand the assortment of functional bakery products, the use of which will provide the body’s need for the necessary macro- and micronutrients for an active and healthy lifestyle. In the bread and bakery products market, consumer preferences are constantly changing. Consumers prefer products that contain less fat and sugar. The market is in demand for bakery products that are healthy, while taste remains an important success factor. Manufacturers include popular healthy additives (grains, seeds and legumes) in their products. Particularly popular at present are ingredients from Eastern Europe and Asia: yuzu, sesame, matcha, shiso. Tropical fruits (passion fruit, mango, bergamot) and fragrances (dried hibiscus, lavender and rose) are predicted to become popular. This causes the complexity of demand segmentation, features of merchandising and pricing policy, features of consumer behavior and consumption psychology, etc. An assessment is given of the dynamics of production and consumption of bread and exports of products, and a forecast is made for the development of the world market for bread and bakery products. The results of the analysis are necessary to assess the level of food safety and to develop a strategy that takes into account the current trends in the global bread and bakery products market. Prospective trends for sustainable production of frozen bakery products have been developed.

Contemporary issues, opportunities, and resources for the U.S. outdoor recreation profession

The purpose of this study was to understand the contemporary issues, opportunities, and resource needs of U.S. outdoor recreation professionals. In Spring 2021, we conducted focus groups with members of the Society of Outdoor Recreation Professionals and Association of Outdoor Recreation and Education. Iterative qualitative analysis of professionals' perspectives using both inductive and matrix coding yielded key themes including: 1) justice, equity, diversity, and inclusion (JEDI), 2) social-ecological health, 3) societal demand, 4) industry direction, and 5) professional identity. While certain themes (i.e., JEDI) existed in previous trends studies, others illustrate the relative novelty of professionals’ experiences of the outdoor recreation boom both pre- and during the COVID-19 pandemic. In sum, we provide an inventory of current issues, opportunities, and resource needs for outdoor recreation professionals, which can inform future advocacy and planning by professional organizations. The overall development in the field of outdoor recreation will be influenced by the aspects: • Key issues will be 1) justice, equity, diversity, and inclusion (JEDI), 2) social-ecological health, 3) societal demand, 4) industry direction, and 5) professional identity. • JEDI was the most salient theme across organizational membership affiliation, indicating the importance of ongoing social justice efforts led by the outdoor recreation industry. • Participants' focus on the negative ecological health impacts and positive human health benefits stemming from outdoor recreation solidly situates the industry within One Health and other ongoing public health efforts. • In some cases, different needs exist across the supply and demand segments of the outdoor recreation profession, particularly related to professional identity and livable wages. • Workforce development opportunities include, but are not limited to, investment and training in community and stakeholder engagement through SCORP processes, planning for social media's influence of recreation resources, and additional human resources to adapt to surging demand.

Aggregate models for planning nautical tourism: Basic, trend and seasonal demand

Nautical tourism sector has a strong impact on European GVA (Gross Value Added) and employment. For this sector, there are interesting works in the literature, some of which propose demand modelling in relation to the characteristics of users. These models are disaggregated and specific to territorial realities, they are interesting for the preparation of touristic port projects in the territory concerned, but are not usable for the planning of interventions in a large territorial area such as a region or a country.It is necessary to have studies that directly relate the main characteristics of demand with the structural characteristics of supply given by the berth quantity of a large area. The study of this relation is important for the planning of new touristic ports and / or for the strengthening of existing ones in a large area. It needs to have models of interaction between supply and demand at an aggregate level, useful for planning.The novelty of this paper is to point out modeling issues related to the simulation of nautical tourism demand segments. Aggregate data are the input of different classes of basic simulation models, specified and calibrated in relation to different demand segments. The advanced calibrated models are for trend and seasonal demand, combined in different specifications. The models are studied for a central area of the Mediterranean Sea, the Italy.The paper has the main objective to propose nautical tourism demand models of basic, trend and seasonal classes. The knowledge of the nautical tourism phenomenon and quantification of demand interacting with supply, support the activities planning and programming processes of touristic ports by technicians and researchers.