Ruwan Gamage and Hui Dong
Efficiency of server side search engines is very low in cases of slow internet connections. Therefore, this study aims to examine use of client side search tools.
Abstract
Purpose
Efficiency of server side search engines is very low in cases of slow internet connections. Therefore, this study aims to examine use of client side search tools.
Design/methodology/approach
A previously introduced client side JavaScript search model was used. New data were obtained for response times against an array of different sized index files. A simple linear regression model was used to obtain the limitation of file size for the search tool. Response times for repeated searches were obtained for the client side search model and selected server side search tools.
Findings
It was found that the search model could be used only for a small‐sized data set. Still, it was useful against server side search methods for repeated searches during a single session.
Research limitations/implications
Response time differs according to the network traffic, connection speed, and so on. Therefore, use of the search model is context‐specific.
Originality/value
The model is easy to use and maintain. Therefore, organizations that wish to make their small data collections searchable on the web can use the model. The model is especially suitable for users with slow internet connections who experience very low efficiency in searching large server side databases. The paper introduces the model, solutions and technical aspects for practical execution.
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Evangelos Vasileiou, Elroi Hadad and Martha Oikonomou
We examine the aggregate price trend of the Greek housing market from a behavioral perspective.
Abstract
Purpose
We examine the aggregate price trend of the Greek housing market from a behavioral perspective.
Design/methodology/approach
We construct a behavioral real estate sentiment index, based on relevant real estate search terms from Google Trends and websites, and examine its association with real estate price distributions and trends. By employing EGARCH(1,1) on the New Apartments Index data from the Bank of Greece, we capture real estate price volatility and asymmetric effects resulting from changes in the real estate search index. Enhancing robustness, macroeconomic variables are added to the mean equation. Additionally, a run test assesses the efficiency of the Greek housing market.
Findings
The results show a significant relationship between the Greek housing market and our real estate sentiment index; an increase (decrease) in search activity, indicating a growing interest in the real estate market, is strongly linked to potential increases (decreases) in real estate prices. These results remain robust across various estimation procedures and control variables. These findings underscore the influential role of real estate sentiment on the Greek housing market and highlight the importance of considering behavioral factors when analyzing and predicting trends in the housing market.
Originality/value
To investigate the behavioral effect on the Greek housing market, we construct our behavioral pattern indexes using Google search-based sentiment data from Google Trends. Additionally, we incorporate the Google Trend index as an explanatory variable in the EGARCH mean equation to evaluate the influence of online search behavior on the dynamics and prices of the Greek housing market.
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Abdul Lateef Olanrewaju and Arazi Idrus
The purpose of this paper is to investigate the determinants of the affordable housing shortage in the Greater Kuala Lumpur from the suppliers’ perspectives.
Abstract
Purpose
The purpose of this paper is to investigate the determinants of the affordable housing shortage in the Greater Kuala Lumpur from the suppliers’ perspectives.
Design/methodology/approach
Primary data were collected through a cross-sectional survey questionnaire comprising 21 determinants and 111 experts in the housing industry.
Findings
The affordable housing shortages are consequences of regulations and policies on land allocations, building materials and the affordable housing market. The government should provide more lands to the developers or the government should directly build affordable housing on their lands. To lower the cost of construction, the government should reduce the importation tax and procedures, and the housing industry should find alternative building materials.
Originality/value
Theoretically, the research provided fresh insights into the causes of housing shortages and reasons for the increase in housing prices. The results will be useful to policymakers towards affordable housing delivery and to the developers and contractors on measures to increase profit margins and increase housing supply.
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The information and knowledge about a product and its assembly are necessary to generate all feasible assembly sequences of that product. Assemblies contain a very large amount of…
Abstract
Purpose
The information and knowledge about a product and its assembly are necessary to generate all feasible assembly sequences of that product. Assemblies contain a very large amount of information and complex relationships. Identifying assembled parts as well as their contact surfaces is very important in design and manufacturing since this information is essential. The problem is to not only make the information available but also use the relevant information for making decisions, especially determination of the optimum assembly sequence. This paper aims to address these issues.
Design/methodology/approach
This paper describes a system for processing assembly models and extracting assembly related data using application programming interface (API) of the computer‐aided design (CAD) software. These data are used to identify the relationships between different components of an assembly thus encouraging generation of feasible assembly sequences.
Findings
Instead of total human interpretation of the assembly design, a direct CAD database interface approach has been proposed to extract the relation with minimal manual involvement. The information extracted is used to generate a list describing the links between the assembled parts, the involved features and the type of link explicitly to facilitate assembly analysis and planning.
Originality/value
The methodology of using the API of the CAD modeling package SolidWorks, is a novel approach in which the assembly mate information is captured. Instead of total human interpretation of the assembly design, a direct CAD database interface approach has been proposed to extract the relation with minimal manual involvement.
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Jianfu Shen and Frederik Pretorius
The purpose of this paper is to construct option pricing models for real estate development by considering and incorporating institutional arrangements, direct interactions and…
Abstract
Purpose
The purpose of this paper is to construct option pricing models for real estate development by considering and incorporating institutional arrangements, direct interactions and financial constraints in the model. It extends the application of real option theory from the framework borrowed from financial option pricing, and considers the case where a development company has restrictions from outside environment and financial constraint. It explores the effects of these additional practical factors on real asset project value and development timing. This paper makes contributions to bridge the theoretical models and practical applications.
Design/methodology/approach
Real estate development is modelled in the binomial option pricing framework with the considerations of time‐to‐build, foregone rent if delaying, institutional environment and capital budgeting. The investment timings are derived from the models and sensitivity analysis is conducted to explore the effects of these factors.
Findings
Apart from the factors in traditional option pricing theory, this paper confirms that the contractual covenants, positive synergies between properties and financial status of the firm, which enhance or restrict real flexibility embedded in the development land, influence project value and investment timing. Numerical examples illustrate the effects of these factors. It is argued that the valuation of real options should place emphasis on industry‐specific characteristics and start from the perspective of the firm rather than individual options.
Practical implications
The models constructed in this paper and the results can be directly used in the practical real estate development.
Originality/value
This paper incorporates many practical factors in real estate development which are not investigated in previous studies. It values the option project from the firm perspective rather than project perspective as previous studies. It also shows the effects of institutional arrangement and firm factors on project value and development timing.
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Shih-Liang Chao, Chin-Shan Lu, Kuo-Chung Shang and Ching-Chiao Yang
Evangelos Vasileiou, Elroi Hadad and Georgios Melekos
The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables…
Abstract
Purpose
The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.
Design/methodology/approach
In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.
Findings
Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.
Practical implications
The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.
Originality/value
This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.
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Jaeseung Park, Xinzhe Li, Qinglong Li and Jaekyeong Kim
The existing collaborative filtering algorithm may select an insufficiently representative customer as the neighbor of a target customer, which means that the performance in…
Abstract
Purpose
The existing collaborative filtering algorithm may select an insufficiently representative customer as the neighbor of a target customer, which means that the performance in providing recommendations is not sufficiently accurate. This study aims to investigate the impact on recommendation performance of selecting influential and representative customers.
Design/methodology/approach
Some studies have shown that review helpfulness and consistency significantly affect purchase decision-making. Thus, this study focuses on customers who have written helpful and consistent reviews to select influential and representative neighbors. To achieve the purpose of this study, the authors apply a text-mining approach to analyze review helpfulness and consistency. In addition, they evaluate the performance of the proposed methodology using several real-world Amazon review data sets for experimental utility and reliability.
Findings
This study is the first to propose a methodology to investigate the effect of review consistency and helpfulness on recommendation performance. The experimental results confirmed that the recommendation performance was excellent when a neighbor was selected who wrote consistent or helpful reviews more than when neighbors were selected for all customers.
Originality/value
This study investigates the effect of review consistency and helpfulness on recommendation performance. Online review can enhance recommendation performance because it reflects the purchasing behavior of customers who consider reviews when purchasing items. The experimental results indicate that review helpfulness and consistency can enhance the performance of personalized recommendation services, increase customer satisfaction and increase confidence in a company.
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Nan Lin, Yanlong Zhang, Wenhong Chen, Dan Ao and Lijun Song
The paper advances the argument that social capital operates on both the supply and demand sides of the labor market. Organizations have significant needs for employees with…
Abstract
The paper advances the argument that social capital operates on both the supply and demand sides of the labor market. Organizations have significant needs for employees with social capital capacity and skills as they do with human capital. We articulate a theory on why organizations have such needs and how social capital may be differentially and strategically deployed to different positions. Specifically, three types of positions (the top positions, the edge positions, and the exchange-oriented positions) are identified with such needs. We formulated two hypotheses derived from the theoretical articulation: (1) the deploying hypothesis – organizations are expected to strategically recruit and deploy workers with social capital capacity and skills to such key internal and edge positions and (2) the institutional contingency hypothesis – organizations in the more competitive environment (e.g., the private sector) are more likely to show such differential deployment than those in the less competitive environment (e.g., the state sector). The hypotheses were subjected to an empirical examination with a set of firm data from China. Both hypotheses were confirmed. Further, we also found evidence for differential deployment of human capital (education and experience) and hierarchical capital (statuses of prior positions and organizations) in different sectors. We discuss the implications of the theory and findings for future research on organizations in different economic sectors beyond China and how a theory of deploying various types of capital – social capital, human capital, and hierarchical capital – in different economic sectors may be developed.