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1 – 10 of 155Jeetendra 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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The link between confidence and economic decisions has been widely covered in the economic literature, yet it is still an unexplored field in tourism. The purpose of this paper is…
Abstract
Purpose
The link between confidence and economic decisions has been widely covered in the economic literature, yet it is still an unexplored field in tourism. The purpose of this paper is to address this gap, and investigate benefits in forecast accuracy that can be achieved by combining the UNWTO Tourism Confidence Index (TCI) with statistical forecasts.
Design/methodology/approach
Research is conducted in a real-life setting, using UNWTO unique data sets of tourism indicators. UNWTO TCI is pooled with statistical forecasts using three distinct approaches. Forecasts efficiency is assessed in terms of accuracy gains and capability to predict turning points in alternative scenarios, including one of the hardest crises the tourism sector ever experienced.
Findings
Results suggest that the TCI provides meaningful indications about the sign of future growth in international tourist arrivals, and point to an improvement of forecast accuracy, when the index is used in combination with statistical forecasts. Still, accuracy gains vary greatly across regions and can hardly be generalised. Findings provide meaningful directions to tourism practitioners on the use opportunity cost to produce short-term forecasts using both approaches.
Practical implications
Empirical evidence suggests that a confidence index should not be collected as input to improve their forecasts. It remains a valuable instrument to supplement official statistics, over which it has the advantage of being more frequently compiled and more rapidly accessible. It is also of particular importance to predict changes in the business climate and capture turning points in a timely fashion, which makes it an extremely valuable input for operational and strategic decisions.
Originality/value
The use of sentiment indexes as input to forecasting is an unexplored field in the tourism literature.
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Fredrik Sunnemark, Emil Gahnström, Hedvig Rudström, Erika Karlsson and Per Assmo
Social sustainability is a concept frequently referred to in public debates concerning how to construct the governance of future societies. The interpretations of its meaning…
Abstract
Purpose
Social sustainability is a concept frequently referred to in public debates concerning how to construct the governance of future societies. The interpretations of its meaning, however, are ambiguous, and practices often dubious. Confronting top-down technocratic governance structures, this paper aims to argue for for tripartite collaborations between residents, higher education institutions (HEIs) and local government, as an approach toward social sustainability that involves residents’ interests in local governance.
Design/methodology/approach
This study argues that a specific time-spatial method of analysis can benefit the co-creation of knowledge as it passes through the spectrum of resident–HEI–local government. It provides a way for resident perceptions to become structured knowledge that originates from the residents, effectively engendering a bottom-up governance structure.
Findings
This study shows how to include residents in policymaking and implementation processes as co-creators of knowledge, and thereby displays the possibility of examining knowledge and competence within municipal projects for social sustainability.
Originality/value
The model developed in this study can be used as a methodological instrument to analyze and expand resident participation in local social sustainability work. It thereby provides a toolbox for inclusive policymaking and strategies.
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Alesandra de Araújo Benevides, Alan Oliveira Sousa, Daniel Tomaz de Sousa and Francisca Zilania Mariano
Adolescent pregnancy stands as a societal challenge, compelling young individuals to prematurely discontinue their education. Conversely, an expansion of high school education can…
Abstract
Purpose
Adolescent pregnancy stands as a societal challenge, compelling young individuals to prematurely discontinue their education. Conversely, an expansion of high school education can potentially diminish rates of adolescent pregnancy, given that educational attainment stands as the foremost risk factor influencing sexual initiation, the use of contraceptive methods during initial sexual encounters and fertility. The aim of this paper is to analyze the impact of the implementation of the public educational policy introducing full-time schools (FTS) for high schools in the state of Ceará, Brazil, on early pregnancy rates.
Design/methodology/approach
Using the difference-in-differences method with multiple time periods, we measured the average effect of this staggered treatment on the treated municipalities.
Findings
The main result indicates a reduction of 0.849 percentage points in the teenage pregnancy rate. Concerning dynamic effects, the establishment of FTS in treated municipalities results in a 1.183–1.953 percentage point decrease in teenage pregnancy rates, depending on the timing of exposure. We explored heterogeneous effects within socioeconomically vulnerable municipalities, yet discerned no impact on this group. Rigorous tests confirm the robustness of the results.
Originality/value
This paper aims to contribute to: (1) the consolidation of research on the subject, given the absence of such research in Brazil to the best of our knowledge; (2) the advancement and analysis of evidence-based public policy and (3) the utilization of novel longitudinal data and methodology to evaluate adolescent pregnancy rates.
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The purpose of this study is to examine the effect of bank-specific, industry-specific and macroeconomic determinants of bank profitability amongst domestic UK commercial banks.
Abstract
Purpose
The purpose of this study is to examine the effect of bank-specific, industry-specific and macroeconomic determinants of bank profitability amongst domestic UK commercial banks.
Design/methodology/approach
This study used an empirically driven single equation framework that incorporates the traditional structure–conduct–performance (SCP) hypothesis. A generalised method of moments technique was applied to a panel of UK banks covering the period 1998–2018 to account for profit persistence.
Findings
The estimation results show that all bank-specific determinants, with the exception of credit risk, significantly affect bank profitability in the anticipated way. However, no evidence was found in support of the SCP hypothesis. Interest rates, especially longer-term interest rates, and the rate of inflation has a significant effect on bank profitability, with the business cycle having a symmetric insignificant effect once other variables have been accounted for. Profitability persists to a moderate extent within the UK banking market, indicating that there exists a departure from a perfectly competitive market structure.
Originality/value
The literature that examines the actual underlying determinants of UK domestic bank profitability is limited.
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The stock market anomalies have been studied across the globe with intermingled results for individual markets. The present study has investigated the financial year effect for…
Abstract
Purpose
The stock market anomalies have been studied across the globe with intermingled results for individual markets. The present study has investigated the financial year effect for Indian stock markets by testing month-of-the-year-effect anomalies.
Design/methodology/approach
The oldest stock exchange's index returns (Bombay Stock Exchange [BSE]) have been tested using ordinary least squares (OLS) and autoregressive conditional heteroskedasticity in mean (ARCH-M) models with Student's t and Student's t-fixed distributions for the period between 1991 and 2019. The Glosten, Jagannathan and Runkle-generalised autoregressive conditional heteroskedasticity (GJR-GARCH) model has been further used to find out existence of the leverage effect in returns.
Findings
The findings indicated no evidence for anomalies in the Indian stock market which may be used by investors for making unusual returns. However, the volatility in returns has shown weak but significant results due to the financial year impact. The leverage effect has not been found in the financial year cycle change over. The Indian market may be said to be moving towards a state of efficiency, leaving no scope for investors to gauge bizarre profits.
Research limitations/implications
The study has incorporated the Indian context for testing anomalies during the start and end of the financial year cycle. The model may be extended further to developed and developing nations’ markets for testing efficiency in their stock markets during the same cycle.
Originality/value
The paper may be the first of its kind to test for the financial year effect on standalone basis for Indian markets. The paper also adds to the existing literature on testing events’ effect.
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Sinyati Ndiango, Richard Jaffu and Neema P. Kumburu
The study aims to investigate how personal values (PVS) influence research self-efficacy (RSE) among academics in public universities in Tanzania.
Abstract
Purpose
The study aims to investigate how personal values (PVS) influence research self-efficacy (RSE) among academics in public universities in Tanzania.
Design/methodology/approach
A cross-sectional design was utilized by the study to gather data once through structured questionnaires administered to 247 academic staff from four public universities in Tanzania.
Findings
Generally, the results show that PVS positively and significantly influence RSE in universities. Specifically, OPC has β value of 0.284 and p < 0.001, SEFN has β = 0.352 and p < 0.001 and CONS has a β = 0.198 and p = 0.003.
Practical implications
University management should include PVS as among the criteria for recruitment of academic staff, as it determines their confidence in engaging in research.
Originality/value
The findings of this study broaden the applicability of Schwartz human values theory in Tanzania’s universities. Moreover, by carrying out empirical research on the influence of PVS on RSE in developing context such as Tanzania, the study contributes to the body of literature on PVS and RSE.
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Edoardo Ramalli and Barbara Pernici
Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model…
Abstract
Purpose
Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.
Design/methodology/approach
This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.
Findings
The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.
Originality/value
The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.
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This paper aims to empirically indicate the factors influencing stock liquidity premium (i.e. the relationship between liquidity and stock returns) in one of the leading European…
Abstract
Purpose
This paper aims to empirically indicate the factors influencing stock liquidity premium (i.e. the relationship between liquidity and stock returns) in one of the leading European emerging markets, namely, the Polish one.
Design/methodology/approach
Various firms’ characteristics and market states are analysed as potentially affecting liquidity premiums in the Polish stock market. Stock returns are regressed on liquidity measures and panel models are used. Liquidity premium has been estimated in various subsamples.
Findings
The findings vividly contradict the common sense that liquidity premium raises during the periods of stress. Liquidity premium does not increase during bear markets, as investors lengthen the investment horizon when market liquidity decreases. Liquidity premium varies with the firm’s size, book-to-market value and stock risk, but these patterns seem to vanish during a bear market.
Originality/value
This is one of the first empirical papers considering conditional stock liquidity premium in an emerging market. Using a unique methodological design it is presented that liquidity premium in emerging markets behaves differently than in developed markets.
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