An economic agent-based model of coupled housing and land markets (CHALMS)

This paper describes a spatially disaggregated, economic agent-based model of urban land use, which is named for its innovative feature of coupled housing and land markets (CHALMS). The three types of agents—consumer, farmer and developer—all make decisions based on underlying economic principles, and heterogeneity of both individuals and the landscape is represented. CHALMS simulates the conversion of farmland to housing development over time, through the actions of the agents in the land and housing markets. Land and building structures in the housing bundle are treated explicitly, so the model can represent the effects of land and housing prices on housing density over time. We use CHALMS to simulate the dynamics of land-use changes as a representative suburban area grows. The presence of agent and landscape heterogeneity, stochastic processes, and path dependence require multiple model runs, and the expression of spatial dispersion of housing types, overall housing density, and land prices over time in terms of the most likely, or ‘average’, patterns. We find that CHALMS captures both the general tendency for diminishing population density at greater distances from the center city, and dispersed leapfrog patterns of development evident in most suburban areas of the US.     

Decentralized markets and the emergence of housing wealth inequality

Recent studies suggest that the traditional determinants of housing wealth are insufficient to explain its current inequality levels. Thus, they argue that efforts should focus on understanding institutional factors. From the perspective of complex adaptive systems, institutions are more than the ‘the rules of the game’, they also consider the interaction protocols or the ‘algorithm’ through which agents engage in socioeconomic activities. By viewing markets as complex adaptive systems, I develop a model that allows estimating how much housing wealth inequality is attributable to the market institution. It combines virtues from two different modeling traditions: (1) the microeconomic foundations from overlapping-generation models and (2) the explicit interaction protocols of agent-based models. Overall, the model generates prices and housing inequality endogenously and from bottom-up; without needing to impose assumptions about the aggregate behavior of the market (such as market equilibrium). It accounts for economic and institutional factors that are important to housing consumption decisions (e.g., wages, consumption of goods, non-labor income, government transfers, taxes, etc.). I calibrate the model with the British Wealth and Assets Survey at the level of each individual household (i.e., ~25 million agents). By performing counter-factual simulations that control for data heterogeneity, I estimate that, in the United Kingdom, the decentralized protocol interaction of the housing market contributes with one to two thirds of the Gini coefficient. I perform policy experiments and compare the outcomes between an expansion in the housing stock, a sales tax, and an inheritance tax. The results raise concerns about the limitations of traditional policies and call for a careful re-examination of housing wealth inequality.     

A hybrid fuzzy regression-fuzzy cognitive map algorithm for forecasting and optimization of housing market fluctuations

This paper presents a hybrid algorithm based on fuzzy linear regression (FLR) and fuzzy cognitive map (FCM) to deal with the problem of forecasting and optimization of housing market fluctuations. Due to the uncertainty and severe noise associated with the housing market, the application of crisp data for forecasting and optimization purposes is insufficient. Hence, in order to enable the decision-makers to make decisions with respect to imprecise/fuzzy data, FLR is used in the proposed hybrid algorithm. The best-fitted FLR model is then selected with respect to two indicators including Index of Confidence (IC) and Mean Absolute Percentage Error (MAPE). To achieve this objective, analysis of variance (ANOVA) for a randomized complete block design (RCBD) is employed. The primary objective of this study is to utilize imprecise/fuzzy data in order to improve the analysis of housing price fluctuations, in accordance with the factors obtained through the best-fitted FLR model. The secondary objective of this study is the exhibition of the resulted values in a schematic way via FCM. Hybridization of FLR and FCM provides a decision support system (DSS) for utilization of historical data to predict housing market fluctuation in the future and identify the influence of the other parameters. The proposed hybrid FLR-FCM algorithm enables the decision-makers to utilize imprecise and ambiguous data and represent the resulted values of the model more clearly. This is the first study that utilizes a hybrid intelligent approach for housing price and market forecasting and optimization.     

Endogenous rise and collapse of housing price: An agent-based model of the housing market

On the basis of interviews with local real estate agents, this study develops an agent-based model of housing market to determine the cause of rise and collapse of US housing price during the years immediately preceding the US financial crisis (2007–2009). We study the key factors affecting housing price volatility, such as lenient financing and speculation. The dynamic simulation findings in the study show in concrete terms how lenient lending practices combined with speculation can lead to increased volatility in housing price, including sharp rises immediately followed by collapses. The exploratory work in this study will contribute to the understanding of the causes of housing bubbles and inform policy decisions.     

Decision making in dynamic stochastic Cournot games

In this paper, the Cournot competition is modeled as a stochastic dynamic game. In the proposed model, a stochastic market price function and stochastic dynamic decision functions of the rivals are considered. Since the optimal decision of a player needs the estimation of the unknown parameters of the market and rivals’ decisions, a combined estimation-optimization algorithm for decision making is proposed. The history of the rivals’ output quantities (supplies) and the market clearing price (MCP) are the only available information to the players. The convergence of the algorithm (for both estimation and decision making processes) is discussed. In addition, the stability conditions of the equilibrium points are analyzed using the converse Lyapunov theorem. Through the case studies, which are performed based on the California Independent System Operator (CA-ISO) historical public data, the theoretical results and the applicability of the proposed method are verified. Moreover, a comparative study among the agents using the proposed method, naïve expectation and adaptive expectation in the market is performed to show the effectiveness and applicability of the proposed method.     

Typology of teacher perception toward distance education issues – A study of college information department teachers in Taiwan

The popularity of distance education has grown rapidly over the last decade in Taiwan’s higher education, yet many fundamental teaching–learning issues are still in debate. While teacher–student interaction is a key success factor in distance education, little work has been done on the teachers. The intent of this research was to clarify teacher’s perceptions on key distance education issues and to develop a discernible typology of different groups of teachers based on their perceptions. Because there may be a gulf between teachers and the technology used in distance education, the target of this study was teachers in information related departments in Taiwan’s colleges, who were more familiar with current technology. Factor analysis and cluster analysis were used to derive the typology. Five higher-level issue constructs emerged from the factor analysis: learning effect, customization, administrative challenges, geographic and resource integration, and instructional design challenges. Four groups of teachers, namely the skeptics, the optimists, the mild-promising group, and the outlier, were identified using cluster analysis of teachers’ perceptions on these five higher-level issue constructs. The profiles of the four groups of teachers were summarized and implications were discussed, which should provide useful insights to the policy makers of higher education on distance education decisions.     

具有公平关切的零售商对双渠道供应链决策影响分析

针对市场需求信息不对称的双渠道供应链,考虑零售商具有公平关切心理,研究零售商的公平关切行为对供应链各成员决策及效用的影响.通过定义制造商判断市场需求规模的阈值,以获取零售商订单中所传递的市场需求规模信息,并得到零售商的最优订货量和制造商的最优直销量.研究发现,阈值随零售商公平关切程度的增加呈现递减趋势,且最终趋于常数. 数值实验结果表明,零售商的公平关切行为有利于增加自身的效用,但会损害制造商的利润.     

Exploring the impact of use context on mobile hedonic services adoption: An empirical study on mobile gaming in China

Unlike traditional technologies, the use of mobile technology is exposed to shifting use contexts. Use context has frequently been described as an important factor influencing the adoption of mobile innovations. However, empirical evidence about the impact of use context is limited. This paper investigated the effect of use context on the formation of users’ perceptions of mobile hedonic services by using mobile gaming as an example. Through the employment of structural equation modelling technology, an adoption model of mobile gaming is proposed and assessed based on results from 267 questionnaires. The results show that use context is the strongest predictor of mobile game adoption. It directly or indirectly affects all different perceptions of mobile gaming in significant ways, including perceived ease of use, perceived usefulness, perceived enjoyment, cognitive concentration, attitude and behavioral intention. Additionally, perceived usefulness, perceived enjoyment and cognitive concentration all have a positive influence on the attitudinal variables of mobile game acceptance. We concluded that the formation of people’s perceptions about mobile gaming is conditional and based on the special consideration of certain use contexts. Both theoretical and practical implications are discussed.     

Evaluation of carsharing network’s growth strategies through discrete event simulation

Carsharing organizations are nowadays faced with the emergence of new markets due to the growing popularity of their services. To keep up with the growing demand, they have to constantly adapt their network and balance their stations’ capacities by implementing new strategies. These strategies involve creation of new carsharing stations, increasing the capacity of stations, merging or demerging carsharing stations etc. Currently, the decision makers rely on an intuitive strategy selection process which often results in inadequate decisions being made representing an immediate loss in resources, time and market penetration. This paper presents a discrete event simulation based decision support tool that assists the decision makers in selecting best network growth strategies to implement for meeting adequately the demand growth while maximizing the members’ satisfaction level and minimizing the number of vehicles used. Our discrete event simulation model allows modeling the activities at any given set of carsharing stations, regardless of their number and capacities. A benchmarking comparison of different potential strategies is done. An application of the proposed model on a region of Communauto’s Montréal (Québec, Canada) carsharing network is provided.     

A behavioral approach of the dynamics of financial markets

We introduce a non-linear dynamic deterministic multistocks multi-agents model. The model can be viewed as the centre of a decision support system in managing financial portfolios, that would allow the decision maker to formalize, test and analyze the impacts of strategies on a market. It takes into account explicitly the perceptions, strategies and decisions of actors and their actions on a market. This approach attempts to model the decision process of interacting agents and so furnishes a tool for decision making in order to analyze the impacts of various strategies of actors on a market. Even in this simple model, the non-linear interactions can drive the system to sudden and unexpected effects which shows the importance of the attempt of the understanding of the dynamics.     

Perceived values and prospective users’ acceptance of prospective technology: The case of a career eportfolio system

Technology-acceptance tests are traditionally conducted after users have obtained at least a certain amount of experience with a technology. Taking college students who had no real interaction with a prospective eportfolio system, this study investigated both their perceptions of the system and the perceptions’ association with attitude towards and intention of using the system. A pre-implementation value-assessment model was proposed, and the results indicate that for prospective users, attitudes appear to have the strongest significant direct effect on usage intentions. Perceived functional value serves as the preliminary conditions that mediate the effect of the perceived epistemic value on attitude. Perceived contextual value influences users’ attitude and intention via the mediation of perceived epistemic value and perceived functional value. This model provides a systemic understanding of prospective users’ perceptions of the system, and such an understanding can help change agents to examine their assumptions about prospective users’ perceptions concerning the value and acceptance of a new technology.     

Manufacturing production plan optimization in three-stage supply chains under Bass model market effects

The Bass model is a very successful parametric approach to forecast the diffusion process of new products. In recent years, applications of the Bass model have been extended to other operational research fields such as managing customer demands, controlling inventory levels, optimizing advertisement strategies, and so forth. This study attempts to establish an application for optimizing manufacturers’ production plans in a three-stage supply chain under the Bass model’s effects on the market. The supply chain structure considered in this research is similar to other common supply chains comprised of three stages, namely retailer, distributor and manufacturer. The retailer stage has to handle customer demands following the Bass diffusion process. Market parameters and essential information are assumed to be available and ready for access. Each stage is expected to determine its inventory policy rationally. That is, each stage will attempt to maximize its own profits. These decisions will back-propagate their effects to upper stages. This study adopts a dynamic programming approach to determine the inventory policies of each stage so as to optimize manufacturers’ production plans.     

Perceiving artificial social agents

Three experiments were conducted to examine perceptions of a natural language computer interface (conversation bot). Participants in each study chatted with a conversation bot and then indicated their perceptions of the bot on various dimensions. Although participants were informed that they were interacting with a computer program, participants clearly viewed the program as having human-like qualities. Participants agreed substantially in their perceptions of the bot’s personality on the traits from the five-factor model (Experiment 1). In addition, factors that influence perceptions of human personalities (e.g., whether one uses another’s first name and response latency) also affected perceptions of a bot’s personality (Experiments 2 and 3). Similar to interactions with humans, the bot’s perceived neuroticism was inversely related to how long individuals chatted with it.     

Why do you keep doing that? The biasing effects of mental states on IT continued usage intentions

Information Technology (IT) continued use decisions are typically assumed to be based on the results of a rational evaluation of the users' IT use experience, yet, recent findings suggest that continued use decisions might not be purely rational. In the current work, we build on the expectation-confirmation theory as well as cognitive dissonance theory to investigate possible mechanisms driving the continued use decisions of mobile phones. As an attempt to extend the existing paradigm in the IT continuance literature beyond rational decision making, we theorize three possible alternative mechanisms that might drive IT continued use decisions, namely psychological states (i.e., a cognitive and affective states of mind), reasoned action, and affective response. According to cognitive dissonance theory, human beings tend to reduce experienced cognitive dissonance by assimilating their post-behavior perceptions toward their prior expectations. As a result, in the context of IT continued use, we argue that experiencing psychological states such as technology addiction and excessive technostress might bias users' evaluations of their IT use experience, which in turn influence their post-use perceptions on the cognitive and affective levels, and consequently will influence the users' continued use decisions. A partial least squares analysis of 436 responses was used to validate and test our model. The study results generally support our model. The theoretical and practical implications of our study are discussed.     

Single-plant sourcing decisions with a multidimensional knapsack model

This paper addresses sourcing decisions and how those decisions can affect the management of a company’s assets. The study begins with a single-plant insourcing problem in which the facility chooses, from a list of parts, which parts to bring in-house. This model is extended to include an outsourcing element where, in addition to the decision of which parts to insource, parts currently in-house are considered for outsourcing. The selection is based on maximizing the value of the selected parts while remaining within the plant’s capacity. This is defined as the sourcing problem and modeled as a multidimensional knapsack problem (MKP). Characteristics of the sourcing problem are identified and compared to standard MKP test problems, then utilized to provide guidelines for generating industry-motivated data sets. Experiences with modeling and solving the sourcing problem for a sheet metal fabrication facility are reported.     

Product mix strategy and manufacturing flexibility

The manufacturing industry is facing a turbulent and constantly changing environment, with growing complexity and high levels of customisation. Any investment solution should address these problems for a dynamic market and within limited budget boundaries, so that companies try to remain competitive. The authors propose a real options model to support firms making important investment decisions, specifically decisions associated with the acquisition of new equipment aimed at allowing firms to increase their manufacturing flexibility for the production of both standard and customized products. This paper is partially based on a real operating experience related to visual finishing technology features in an industrial company that conforms to the definitions of the product mix. The authors’ motivation for this work is driven by firms’ desire to satisfy specific customer needs, and to respond to them quickly under uncertain demand. Our goal, using theories from finance, production management, and product offering management, is to conclude that there is a relevant difference between the evaluation of the technology that is to be chosen, and the potential value due to product mix adaptations that are able to provide the maximum return from investment. We address problems related to standard and customized production systems, and the decision to invest in a set of resources that will enable this choice.     

Market-oriented scheduling and economic optimization of continuous multi-grade chemical processes

In this paper an approach for flexible production scheduling for continuous multi-grade chemical processes is proposed. The approach integrates the economics of production and of company–market interaction for single-machine multi-grade continuous processes. The operation of a continuous multi-grade plant is modeled utilizing the detailed inclusion of grade transitions and sales orders and opportunities. The added value of the operation, which is used as the criterion function, is modeled by analyzing the costs and benefits of plant operation. The model results in a mixed integer linear program which is solved to compute suitable short term production and sales decisions. The approach is demonstrated on a gas phase HDPE manufacturing plant.     

Visualization of agreement and discussion processes during computer-supported collaborative learning

This study examined the effects of the shared space (SS) on students’ behaviors in a computer-supported collaborative learning (CSCL) environment. The SS visualizes discussion and agreement during online discussions. It was hypothesized the SS would increase the media richness of the CSCL-environment, would stimulate critical and exploratory group-norms, would lead to more positive perceptions of online collaboration, and would have an impact on students’ collaborative activities. In total, 59 students working in 20 groups had access to the SS visualization, while 58 students working in 20 groups did not. The results show that students with access to the SS visualization: (a) perceived higher media richness; (b) had a more exploratory group-norm perception; (b) perceived more positive group behavior; (c) perceived their group’s task strategies to be more effective; (d) engaged in different collaborative activities and (e) performed better on one part of the group task. These results demonstrate the potential benefits of visualizing agreement and discussion during CSCL.     

Exploring Koreans’ smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory

This study investigates factors that influence adoption and use of smartphones among Koreans and seeks to integrate two theoretical approaches: the technology acceptance model (TAM) and the uses and gratifications (U&G) approach. To that end, the study used data from a self-reported survey of 491 Korean adults who use Apple’s iPhone. A structural equation model employed in the current study demonstrates that Koreans’ smartphone use is affected more by motivations based on instrumental and goal-oriented use than by ritualized and less-goal oriented use. The findings suggest that to spread information system with innovative and active features, developers should pay attention to users’ intrinsic motivations as well as to their extrinsic perceptions.