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This paper investigates the semantic association mechanisms of weak demand signals that facilitate innovative product development in terms of conceptual and temporal precedence, despite their inherent ambiguity and uncertainty.

To address this challenge, a domain ontology approach is proposed to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identification. The framework provides a basis for identifying such signals and introduces evaluation indices, such as depth, novelty and association, which are integrated to propose a three-dimensional weak signal recognition model based on domain ontology that outperforms existing research.

Empirical analysis is carried out based on customer comments of new energy vehicles on car platform such as “Auto Home” and “Bitauto”. Results demonstrate that in terms of recognition quantity, the three-dimensional weak demand signal recognition model, based on domain ontology, can accurately identify six demand weak signals. Conversely, the keyword analysis method exhibits a recognition quantity of four weak signals; in terms of recognition quality, the three-dimensional weak demand signal recognition model based on domain ontology can exclude non-demand signals such as “charging technology”, while keyword analysis methods cannot. Overall, the model proposed in this paper has higher sensitivity.

This paper proposes a novel method for identifying weak demand signals that considers the frequency of the signal's novelty, depth and relevance to the target demand. To verify its effectiveness, customer review data for new energy vehicles is used. The results provide a theoretical reference for formulating government policies and identifying weak demand signals for businesses.

The purpose of this paper is to review recent studies published from 2007 to 2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field.

Articles on tourism and hotel demand modeling and forecasting published mostly in both science citation index and social sciences citation index journals were identified and analyzed.

This review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, whereas disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area.

The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting.

This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices.

The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.

This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households.

A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding.

Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R² > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects.

This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums.

All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas.

This paper uses primary survey data (collected by the authors) to assess housing affordability for the urban poor of Lucknow city. It makes the results of the study credible and useful for further applications.

The lens used by the courts and much of the antitrust literature on predatory selling and/or buying is based on partial equilibrium methodology. We demonstrate that such methodology is unreliable for assessments of predatory monopoly or monopsony conduct. In contrast to the typical two-stage dynamic analysis involving a predation period followed by a recoupment period, we advance a general equilibrium analysis that demonstrates the critical role of related industries and markets. Substitutability versus complementarity of both inputs and outputs is critical. With either monopolistic or monopsonistic market power (but not both), neither predatory overselling nor predatory overbuying is profitably sustainable. Two-stage predation/recoupment is profitable only with irreversibility in production and cost functions, unlike typical estimated forms from the production economic literature. However, when the market structure admits both monopolistic and monopsonistic behavior, predatory overbuying can be profitably sustainable while overselling cannot. Useful distinctions are drawn between contract versus non-contract markets for input markets.

In recent years, centrality measures have been extensively used to analyze real-world complex networks. Water distribution networks (WDNs), as a good example of complex networks, exhibit properties not shared by other networks. This raises concerns about the effectiveness of applying the classical centrality measures to these networks. The purpose of this paper is to generate a new centrality measure in order to stick more closely to WDNs features.

This work refines the traditional betweenness centrality by adding a hydraulic-based weighting factor in order to improve its fit with the WDNs features. Rather than an exclusive focus on the network topology, as does the betweenness centrality, the new centrality measure reflects the importance of each node by taking into account its topological location, its demand value and the demand distribution of other nodes in the network.

Comparative analysis proves that the new centrality measure yields information that cannot be captured by closeness, betweenness and eigenvector centrality and is more accurate at ranking the importance of the nodes in WDNs.

The following practical implications emerge from the centrality analysis proposed in this work. First, the maintenance strategy driven by the new centrality analysis enables practitioners to prioritize the components in the network based on the priority ranking attributed to each node. This allows for least cost decisions to be made for implementing the preventive maintenance strategies. Second, the output of the centrality analysis proposed herein assists water utilities in identifying the effects of components failure on the network performance, which in turn can support the design and deployment of an effective risk management strategy.

The new centrality measure, proposed herein, is distinct from the conventional centrality measures. In contrast to the classical centrality metrics in which the importance of components is assessed based on a pure topological viewpoint, the proposed centrality measure integrates both topological and hydraulic attributes of WDNs and therefore is more accurate at ranking the importance of the nodes.

This study aims to critically evaluate hospitality and tourism demand research and introduce a behavioral economics approach to solve the problems faced by researchers.

Current issues in hospitality and tourism demand analysis are identified through critical reflection, and a behavioral economics approach is adopted to develop a new conceptual framework.

Four issues in hospitality and tourism studies are identified from the microeconomic theory and econometric modeling perspectives. The study’s demand framework provides both a theoretical underpinning and quantitative models to resolve the identified issues. With a focus on consumers’ cost–benefit assessments in light of individual differences and environmental factors, the authors’ conceptual framework represents a new effort to quantify hospitality and tourism demand at the disaggregate level with interactive multiple demand curve estimations.

The study’s analytical framework for hospitality and tourism demand analysis is unique, and it fills the research gap. However, this research is still in the conceptual stage, and the authors leave it to future studies to empirically test the framework.

The proposed demand framework at the disaggregate level will benefit both private and public sectors involved in hospitality and tourism businesses in terms of pricing, marketing and policymaking.

The authors offer a new conceptual model that bridges the gap between aggregate and disaggregate hospitality and tourism demand analyses. Specifically, the authors identify research directions for future hospitality and tourism demand research involving individual tourists/consumers at the disaggregate level.

The field of supply chain management (SCM) evolves dramatically due to factors of globalization, innovation, sustainability, and technology. These changes raise challenges not only to higher education institutions, but also to students, employing organizations, and third parties like SCM-related professional bodies. To understand the challenge, the purpose of this paper is to examine the gap between demand and supply of SCM-related knowledge areas, answer-related design questions, and make recommendations to close the gaps.

To compare the demand and supply of SCM-related knowledge areas, demand data is collected from a professional career website and supply data is gathered from operations management (OM) and SCM course syllabi from AACSB-accredited business schools in the USA. Cluster analysis identifies how supply and demand are matched on the data collected.

First, gaps exist between SCM talent requirements from industry and the knowledge/skill training by US business schools. This paper identifies matching, under-supplying, and over-supplying knowledge areas. Under-supply in emerging areas such as SCM information technology and certain logistics management topics are found. Some traditional OM topics are over-supplied due to out-of-date industry applications and should be revised to reflect the field’s transition from an OM to SCM view. Last, this paper makes recommendations to different stakeholders in this matching supply with demand process.

This study contributes to the literature in two ways. First, it provides an up-to-date understanding on demand and supply of SCM talent in USA. Second, it provides insights and recommendations not only to educators on curriculum design, but also to potential candidates interested in SCM careers, to companies’ job recruiters, and to professional organizations (such as APICS and Council of Supply Chain Management Professionals) to reduce the gaps between demand and supply.

Attempts to propose a simplified framework from an economic perspective for analyzing education policy. The framework takes into account the demand for and supply of education, the education system structure, the economic effects and consequences, and their interrelations. Maps out some key economic areas, issues and concerns in analysis and discussions of education policy. The framework will serve to facilitate economic considerations and analyses in current education policy debate in different parts of the world.

Since the appearance of Simon Rottenberg's seminal paper on the baseball players' labour market in the Journal of Political Economy (1956), the literature on the economics of professional team sports has increased rapidly, fuelled by major changes in the restrictive rules which had pervaded these sports, themselves a consequence of battles in the courts and the collective bargaining arena. These changes have not been limited to North America, to which most of the literature relates, but also apply to Western Europe and Australia in particular. This monograph surveys this literature covering those various parts of the world in order to draw out both theoretical and empirical aspects. However, to argue that the existence of what is now an extensive literature “justifies” such a survey on professional team sports clearly begs a number of questions. Justification can be found in at least two major aspects.