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1 – 10 of over 1000Recent research has found significant relationships between internet search volume and real estate markets. This paper aims to examine whether Google search volume data can serve…
Abstract
Purpose
Recent research has found significant relationships between internet search volume and real estate markets. This paper aims to examine whether Google search volume data can serve as a leading sentiment indicator and are able to predict turning points in the US housing market. One of the main objectives is to find a model based on internet search interest that generates reliable real-time forecasts.
Design/methodology/approach
Starting from seven individual real-estate-related Google search volume indices, a multivariate probit model is derived by following a selection procedure. The best model is then tested for its in- and out-of-sample forecasting ability.
Findings
The results show that the model predicts the direction of monthly price changes correctly, with over 89 per cent in-sample and just above 88 per cent in one to four-month out-of-sample forecasts. The out-of-sample tests demonstrate that although the Google model is not always accurate in terms of timing, the signals are always correct when it comes to foreseeing an upcoming turning point. Thus, as signals are generated up to six months early, it functions as a satisfactory and timely indicator of future house price changes.
Practical implications
The results suggest that Google data can serve as an early market indicator and that the application of this data set in binary forecasting models can produce useful predictions of changes in upward and downward movements of US house prices, as measured by the Case–Shiller 20-City House Price Index. This implies that real estate forecasters, economists and policymakers should consider incorporating this free and very current data set into their market forecasts or when performing plausibility checks for future investment decisions.
Originality/value
This is the first paper to apply Google search query data as a sentiment indicator in binary forecasting models to predict turning points in the housing market.
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Jae Young Choi, Yeonbae Kim, Yungman Jun and Yunhee Kim
The purpose of this paper is to reveal the core determinants and adoption patterns of the major enterprise information systems.
Abstract
Purpose
The purpose of this paper is to reveal the core determinants and adoption patterns of the major enterprise information systems.
Design/methodology/approach
This study incorporated the core representative and meaningful explanatory variables in the major previous literatures and analyzes the core determinants of businesses' adoption of the essential information systems and the substitutionary patterns among them, using a Bayesian multivariate probit model, which is based on McFadden's random utility model and capable of handling multiple response data.
Findings
It was found that not only factors from the classical technological diffusion viewpoint but also factors such as organizational tools and strategic behaviors play an important role in firms' adoption of information systems. Specifically, epidemic effect generally outweighs size effect, and putting more effort into the intensity of information strategy planning is more influential than the hiring of a professional chief information officer. On the other hand, such variables as age of the firm, labor intensity, and number of PCs per person generally have no significant impacts. Finally, a relatively strong complementary relationship exists between enterprise resource planning and customer relationship management adoption, and between e‐buy and groupware adoption.
Originality/value
The results presented in this paper have important implications for firms on a minimal budget that want to maximize their productivity through the adoption of information systems. They also provide important information for government policymakers whose job it is to design strategies for the successful deployment of information systems.
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A growing number of econometric examinations show that works councils substantially shape the personnel policy of firms in Germany. Firms with works councils make greater use of…
Abstract
Purpose
A growing number of econometric examinations show that works councils substantially shape the personnel policy of firms in Germany. Firms with works councils make greater use of various human resource management (HRM) practices. This gives rise to the question of whether employers view the shaping of personnel policy positively or negatively. Against this background, the purpose of this paper is to examine the influence of works councils on employer attitudes toward HRM practices.
Design/methodology/approach
Using data from manufacturing establishments, multivariate and recursive multivariate models are applied to estimate the determinants of employer attitudes toward HRM practices.
Findings
The incidence of a works council increases the probability of positive employer attitudes toward the incentive effects of performance pay, profit sharing, promotions, further training and worker involvement in decision making. However, it decreases the probability of positive employer attitudes toward high wages. The results suggest that works councils play a redistribution role in wages and a collective voice role in the other HRM practices.
Originality/value
The study complements examinations focusing on the influence of works councils on the formal presence of HRM practices. There are two potential limitations of focusing solely on formal HRM practices. First, the formal presence of a practice does not necessarily mean that the practice is effectively used. Second, a firm may informally use HRM practices even though the practices have not been formally adopted. The study provides insights into the question of whether or not works councils influence employers’ support for the various practices. This support can be important for the effective use of the practices, regardless of whether they are of formal or informal nature.
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Jeetendra Prakash Aryal, M.L. Jat, Tek B. Sapkota, Arun Khatri-Chhetri, Menale Kassie, Dil Bahadur Rahut and Sofina Maharjan
The adoption of climate-smart agricultural practices (CSAPs) is important for sustaining Indian agriculture in the face of climate change. Despite considerable effort by both…
Abstract
Purpose
The adoption of climate-smart agricultural practices (CSAPs) is important for sustaining Indian agriculture in the face of climate change. Despite considerable effort by both national and international agricultural organizations to promote CSAPs in India, adoption of these practices is low. This study aims to examine the elements that affect the likelihood and intensity of adoption of multiple CSAPs in Bihar, India.
Design/methodology/approach
The probability and intensity of adoption of CSAPs are analyzed using multivariate and ordered probit models, respectively.
Findings
The results show significant correlations between multiple CSAPs, indicating that their adoptions are interrelated, providing opportunities to exploit the complementarities. The results confirm that both the probability and intensity of adoption of CSAPs are affected by numerous factors, such as demographic characteristics, farm plot features, access to market, socio-economics, climate risks, access to extension services and training. Farmers who perceive high temperature as the major climate risk factor are more likely to adopt crop diversification and minimum tillage. Farmers are less likely to adopt site-specific nutrient management if faced with short winters; however, they are more likely to adopt minimum tillage in this case. Training on agricultural issues is found to have a positive impact on the likelihood and the intensity of CSAPs adoption.
Practical implications
The major policy recommendations coming from of our results are to strengthen local institutions (public extension services, etc.) and to provide more training on CSAPs.
Originality/value
By applying multivariate and ordered probit models, this paper provides some insights on the long-standing discussions on whether farmers adopt CSAPs in a piecemeal or in a composite way.
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Kimberly Lynn Jensen, Karen Lewis DeLong, Mackenzie Belen Gill and David Wheeler Hughes
This study aims to determine whether consumers are willing to pay a premium for locally produced hard apple cider and examine the factors influencing this premium. This study…
Abstract
Purpose
This study aims to determine whether consumers are willing to pay a premium for locally produced hard apple cider and examine the factors influencing this premium. This study examines the influence of hard apple cider attributes and consumer characteristics on consumer preferences for local hard apple cider.
Design/methodology/approach
Data from a 2019 survey of 875 Tennessee consumers regarding their preferences for a local hard apple cider were obtained. Probit estimates were used to calculate the premium consumers were willing to pay for a locally made hard apple cider and factors influencing this premium. A multivariate probit was used to ascertain factors influencing the importance of attributes (e.g. heirloom apples, sweetness/dryness, sparking/still and no preservatives added) on local hard apple cider preference.
Findings
Consumers would pay a $3.22 premium for local hard apple cider compared with a $6.99 reference product. Local foods preferences, urbanization, weekly purchases of other alcoholic beverages and shopping venues influenced premium amounts. Other important attributes were sweetness/dryness and no preservatives. Influence of consumer demographics suggests targeted marketing of local ciders could be successful.
Originality/value
Few studies examine consumer preferences for hard apple ciders. This study represents a cross-sectional analysis of the premium consumers would pay for local hard apple ciders and the importance of other hard apple cider attributes.
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Alebachew Destaw Belay, Wuletaw Mekuria Kebede and Sisay Yehuala Golla
This study aims to examine determinants of farmers’ use of climate-smart agricultural practices, specifically improved crop varieties, intercropping, improved livestock breeds and…
Abstract
Purpose
This study aims to examine determinants of farmers’ use of climate-smart agricultural practices, specifically improved crop varieties, intercropping, improved livestock breeds and rainwater harvesting in Wadla district, northeast Ethiopia.
Design/methodology/approach
A cross-sectional household survey was used. A structured interview schedule for respondent households and checklists for key informants and focus group discussants were used. This study used both descriptive statistics and a multivariate probit econometric model to analyze the collected data. The model was used to compute factors influencing the use of climate-smart agricultural practices in the study area.
Findings
The results revealed that households adopted selected practices. The likelihood of farmers’ decisions to use improved crop varieties, intercropping, improved livestock breeds and rainwater harvesting was 85%, 52%, 69% and 59%, respectively. The joint probability of using these climate-smart agricultural practices was 23.7%. The model results confirmed that sex, level of education, livestock holding, access to credit, farm distance, market distance and training were significant factors that affected the use of climate-smart agricultural practices in the study area.
Originality/value
The present study used the most selected locally practiced interventions for climate-smart agriculture.
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Wondimagegn Tesfaye and Lemma Seifu
The purpose of this paper is to analyze smallholder farmers’ perceptions of climate change and its adverse effects, identify major adaptation strategies used by farmers and…
Abstract
Purpose
The purpose of this paper is to analyze smallholder farmers’ perceptions of climate change and its adverse effects, identify major adaptation strategies used by farmers and analyze the factors that influence the choice of adaptation strategy by smallholder farmers in eastern Ethiopia.
Design/methodology/approach
The study was based on a cross-sectional survey of 296 sample households selected from three districts in east Ethiopia. Data were collected with the aid of a semi-structured questionnaire and review of literature, documents and databases.
Findings
The study provides empirical evidence that majority of farmers in the study area are aware of climate change patterns and their adverse effect on income, food security, diversity, forest resources, food prices and crop and livestock diseases. In response to these adverse effects, major adaptation strategies used by farmers include cultivating different crops, planting different crop varieties, changing planting dates, use of soil and water conservation techniques, conservation agriculture practices and engaging in non-farm income activities. Choice of adaptation strategies are influenced by gender of household head, household size, farm size, distance from market and number of farm plots.
Practical implications
The study suggests that developing more effective climate change adaptation strategies need support from the government. Such an effort needs provision of the necessary resources such as credit, information and extension services on climate change adaptation strategies and technologies, and investing in climate smart and resilient projects.
Originality/value
The study adopts multivariate probit model that models farmers’ simultaneous adaptation choice behavior which has been rarely addressed by previous researches.
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Thanh Cong Nguyen, Hang Dieu Nguyen, Hoa Thu Le and Shinji Kaneko
This purpose of this paper is to understand residents’ choice of preferred measures and their willingness-to-pay (WTP) for the measures to improve the air quality of Hanoi city.
Abstract
Purpose
This purpose of this paper is to understand residents’ choice of preferred measures and their willingness-to-pay (WTP) for the measures to improve the air quality of Hanoi city.
Design/methodology/approach
Questionnaire surveys were conducted to collect the opinions of 212 household representatives living in Hanoi City. The survey tools were tested and adjusted through an online survey with 191 responses. Multivariate probit and linear regression models were used to identify determinants of respondents’ choices of measures and their WTP.
Findings
Respondents expressed their strong preferences for three measures for air quality improvements, including: (1) increase of green spaces; (2) use of less polluting fuels; (3) expansion of public transportation. The mean WTP for the implementation of those measures was estimated at about 148,000–282,000 Vietnamese dong, equivalent to 0.09–0.16% of household income. The respondents’ choices appear to be consistent with their characteristics and needs, such as financial affordability, time on roads and their perceived impacts of air pollution. The WTP estimates increase with perception of air pollution impacts, time on roads, education and income; but are lower for older people.
Practical implication
Increase of green spaces can be the measure to which policy makers should pay more attention. The match-up of residents needs and well-informed plans will be an important key to success.
Originality/value
This appears to be the first attempt to test the validity of public opinions on choices of measures for improving urban air quality in Vietnam. Our WTP estimates also contribute to the database on the values of improved air quality in the developing world.
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Abstract
Purpose
Promoting clean heating in rural areas is crucial for achieving a low-carbon transition of energy consumption and China's dual-carbon target. The study aims to consider the energy stacking behavior in heating energy use, reveals the determinants that affect household cleaner heating choices under the winter clean heating plan (WCHP), and proposes policy recommendations for the sustainable promotion of clean heating.
Design/methodology/approach
With unique rural household survey data covering the clean heating pilot regions in northern China in 2020, this study estimates the relationship between driving factors and heating energy choices through binary and multivariate probit models.
Findings
The regression estimates show that the main drivers of heating energy choices include household income per capita, education level of household head, knowledge of the WCHP, access to heating subsidies and perception of indoor air pollution. There is energy stacking behavior in rural household heating energy use. Household decisions to adopt electricity or clean coal heating are correlated with firewood or soft coal use.
Originality/value
This study is one of the few to investigate the heating energy use of rural households by allowing for the adoption of multiple energy types. Combined with a unique microsurvey dataset, it could provide rich information for formulating proper energy transition planning. The findings also shed light on the importance of heating subsidies, households' knowledge of WCHP and awareness of environmental health in choosing clean heating energy, which has not been fully valued in related research.
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Marianne Lefebvre, Dimitre Nikolov, Sergio Gomez-y-Paloma and Minka Chopeva
The purpose of this paper is to analyze the determinants of agricultural insurance adoption in Bulgaria, using a purpose-built survey of 224 farmers interviewed in 2011. The…
Abstract
Purpose
The purpose of this paper is to analyze the determinants of agricultural insurance adoption in Bulgaria, using a purpose-built survey of 224 farmers interviewed in 2011. The insurance decision is analyzed conjointly with other risk management decisions on the farm such as having contracts with retailers or processors, diversifying farm activities and using irrigation.
Design/methodology/approach
The agricultural insurance sector in Bulgaria is presented in the broader context of the transition to a market-oriented economy and integration of Bulgarian agriculture into the EU Common Agricultural Policy. The recent developments on the determinants of farm insurance adoption in the agricultural economics and finance literature are discussed. A multivariate probit model is used in order to determine the factors explaining the adoption or non-adoption of various risk management tools by the surveyed farmers, including farm insurance.
Findings
The authors find that farmers with diversified activities, using irrigation or having contracts with retailers or processors, are more likely to adopt insurance, after controlling for farms and farmers’ structural characteristics. Additionally, the authors find that the main characteristics distinguishing farmers who purchase agricultural insurance from non-users are farm size and farm location. The existence of strong regional effect suggests the importance of adapting the insurance products to the different regional contexts in Bulgaria.
Originality/value
This paper contributes to the (limited) literature on agricultural insurance adoption in transition countries, currently shifting from a system where compensation against natural hazards tended to come from a State damage mitigation fund, inherited from the centrally planned governments to private and voluntary agricultural insurance. This research provides a unique data source on the Bulgarian case study.
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