Tobit Regression Model Research Articles

Dynamic evolution and influencing factors of green total factor productivity in the Yangtze River Economic Belt: a study based on the three-stage SBM-ML index model

Achieving sustainable development that harmonizes environmental protection with economic growth in the Yangtze River Economic Belt (YREB) remains a critical area of research. Examining green total factor productivity (GTFP) aids in pinpointing the key factors and pathways essential for fostering green economic development. On the basis of 108 prefecture-level cities in the YREB, a three-stage SBM-ML index model was constructed to measure the GTFP level from 2009 to 2022. ArcGIS software was used to analyze the spatiotemporal evolution of GTFP dynamically. Finally, the multidimensional factors affecting GTFP were systematically analyzed via the Tobit model. The study revealed that (1) GTFP exhibits notable spatial disparities among the upper, middle, and lower reaches of the YREB, with the downstream areas showing higher levels than the upstream and midstream areas do. (2) After excluding environmental factors and random errors, the true GTFP level significantly decreases, indicating a notable environmental masking effect, with a masking effect of up to 63.9%. (3) The spatial distribution of GTFP overall shows a “low-high-low-high” pattern from west to east, forming an “N”-shaped spatial pattern. (4) The Tobit model regression results show that government governance enhances GTFP, while economic growth and intergovernmental fiscal decentralization hinder real GTFP. Although urbanization was initially insignificant, it significantly boosted real GTFP post-COVID-19. Finally, policy recommendations to promote green development in river basins are proposed.

The Agricultural Labor Market: Farmer Perception and the Influence on The Efficiency of Rice Farming

Therefore, this research aims to analyze the factors that influence the farmer's perspective regarding the labor provider service and the effect of the service that is used by the farmers on the technical efficiency level. This research uses the methodology that involves the utilization of logit regression analysis to test the cross-sectional data that was obtained from 200 farmers in Ngawi, Lumajang, Pasuruan, Malang in Indonesia as a sample. The measurement of technical efficiency uses the Cobb-Douglas production function with the Stochastic Production Frontier approach and the Tobit Regression model to determine the effect of labor provider business on technical efficiency. This research found that factors that influence the farmer's perception of the labor provider are age, land area, the worker’s wage, and the use of agricultural tools. The technical efficiency level can certainly still be improved by addressing the influencing factors, namely the use of information technology, agricultural mechanization, and the positive response towards the organizations that help in the availability of input, such as the labor provider service. The findings in this research provide an overview of how a farmer should perceive the agricultural labor provider service, especially in agriculture in the industrial or high labor wages areas.

Innovating with impact: CEO attributes and their influence on firm innovation in Australia

PurposeThis study examines the influence of CEO characteristics on firm innovation within the Australian market, using R&D expenditure as a proxy for innovation. The aim is to analyze how factors such as CEO gender, educational background and dual roles (CEO-chairman) impact firms' R&D investment across various industries.Design/methodology/approachPanel and Tobit regression models are employed to assess the relationship between CEO characteristics and R&D expenditure. The study controls for endogeneity and applies firm-level control variables to ensure robustness, examining CEO traits like gender, educational qualifications and CEO-chairman duality.FindingsThe study reveals that CEO gender and educational level significantly impact firm innovation, particularly R&D expenditure, compared to other characteristics like CEO-chairman duality. Female CEOs and those with PhD degrees are associated with higher R&D spending, with variations across industries such as basic materials and healthcare.Research limitations/implicationsThe study is limited by its focus on Australian firms and the time span of 2006–2016. Additionally, mixed results for CEO-chairman duality and CEO location may reduce the generalizability of the findings across all industries on the ASX.Practical implicationsThe findings highlight the importance of gender diversity and CEO education in driving firm innovation. Companies aiming to enhance competitiveness and performance through R&D activities, especially in industry-specific contexts, should consider these CEO characteristics.Originality/valueThis study provides novel insights by analyzing the impact of CEO characteristics, such as gender and education level, on firm innovation in the underexplored Australian market. By using R&D expenditure as a proxy for innovation and employing both panel and Tobit regression models, it highlights the significance of CEO traits, particularly in specific industries. The findings emphasize the stronger influence of CEO gender and educational level compared to CEO-chairman duality and location, offering valuable implications for gender diversity and industry-specific innovation strategies in enhancing firm competitiveness.

Measuring the Ecoefficiency of Tourism in Typical Tourist Cities and Analyzing the Influencing Factors—Anhui Huangshan City as an Example

To protect the environment, promote sustainable tourism, and enhance the quality and efficiency of the tourism industry, accounting for and identifying the ecological efficiency of tourism is crucial. In this study, we constructed a scientific measurement system for assessing the ecological efficiency of tourism in Huangshan City from 2011 to 2022 using a Super-SBM (slack-based measure) model and a Tobit regression model. Our findings revealed the following: (1) The overall trend in the total efficiency in Huangshan City fluctuated considerably during the period under study but demonstrated an overall positive trend of development. Scale efficiency mostly showed consistent annual improvement, while pure technical efficiency remained relatively stable. (2) Economic, social, environmental, and human-resource- and transportation-related factors all exerted significant positive influences on the ecological efficiency of tourism in Huangshan City. Based on these results, in aiming to enhance the ecological efficiency of tourism in Huangshan City, comprehensively considering multiple factors, such as the economy, society, the environment, human resources, and transportation, is recommended. Attention should be paid to balancing industrial expansion with technological innovation while simultaneously investing in the development of education and human resources. Emphasis should also be placed on protecting and improving the environment alongside efforts to improve capabilities in technological innovation and the level of management. The research findings presented in this article offer a valuable theoretical underpinning, as well as practical guidance for Huangshan City and other representative tourist destinations on how they can enhance the efficiency of their tourism ecosystems, thereby facilitating high-quality and sustainable development within the tourism industry.

Characteristics of Spatial–Temporal Evolution of Sustainable Intensification of Cultivated Land Use and Analysis of Influencing Factors in China, 2001–2020

The rapid growth of the global population, the acceleration of the urbanization process, and the demands of economic development, place enormous pressure on scarce land resources. Cultivated land use presents a series of problems, hindering its socioeconomic and ecological sustainability. The sustainable intensification of cultivated land use (SICLU) is a development model designed to maximize land use efficiency, while minimizing environmental pollution. It is considered to be an efficient method to achieve three aspects of sustainable goals, namely in regard to society, the economy, and ecology, simultaneously. This approach has significant theoretical and practical implications for China’s food security and ecological safety. This study incorporates the “agricultural carbon emissions” indicator into the indicator evaluation system. Using the super-efficiency SBM model, we estimate the SICLU levels in China from 2001 to 2020. ArcGIS and the Dagum Gini coefficient decomposition model are employed to explore the temporal and spatial evolution characteristics and non-equilibrium spatial dynamics of SICLU in China. Finally, the Tobit regression model is used to reveal the driving factors. The results show the following: (1) Since 2003, China’s SICLU levels demonstrate an overall ascent amid fluctuations, sustaining a relatively high average annual level of 0.945. (2) In terms of spatial evolution patterns, China’s SICLU levels demonstrate significant spatial disparities, with distinct differences among the four major regions. Regions with similar SICLU levels show a certain degree of spatial adjacency. (3) There are significant regional disparities in China’s SICLU levels, which overall exhibit a declining trend. The differences between regions are the primary source of spatial variation, followed by hypervariable density and intra-regional disparities. (4) The regional industrial structure, the level of agricultural modernization, the agricultural cropping structure, and the per capita sown area, positively influence the enhancement of SICLU levels in China. Throughout the study period, the SICLU levels in China continuously improved and the overall regional disparities diminished. However, significant inter-regional imbalances persist, necessitating tailored optimization measures, based on local conditions. Establishing a coordinated mechanism for orderly and synergistic regional development is crucial, in order to provide references to decision-makers to promote the rational use of arable land in China.

Multidimensional child poverty and its determinants: Empirical Evidence from Sub-Saharan Africa

Poverty has been a subject of global discourse most especially in sub-Saharan Africa where little progress has been achieved. Most literature sources regard poverty mainly as a household threat rather than one to affectsthe children living within the household. Thus, through a multidimensional approach, this study analyses poverty, specifically in the context of its effect on children. In carrying out this study, the General Household Survey dataset for Nigeria (the mostpopulous country in sub-Saharan Africa) for 2018/2019 obtained from the National Bureau of Statistics (NBS) was used. Descriptive statistics, the Multidimensional Poverty Measure, and the Tobit Regression Model were usedin this study. The results showed that there are more male children (52.17%) than females (47.83%), with most of the children falling within the middle-age group of households (45.51%). Less than half of the household heads were found to be literate, while the mean size of the household amounted to nine. This study found that the poverty dimension,mainly affecting the research sample of Nigerian children,was their deprivation in terms of sanitation, while the least significant dimension was their lack of food. Child poverty is prevalent among the three respective age groups of children, among rural dwellers (57.16%), and among residents in the northern divide of the country. The rural sector, the residents in the north-eastern region of the country, and the gender of the household head were found to be significant variablesinfluencing child poverty in Nigeria. As such, poverty reduction strategies directed towards the rural sector, the northern region, and the identified age groups of children should be of primary focus in tackling child poverty in Nigeria to achieve the United Nations’ Sustainable Development Goal (SDG1) -“End poverty in all its forms everywhere”.

Exploring the association of adverse drug reactions with medication adherence and quality of life among hypertensive patients: a cross-sectional study.

Effective hypertension management requires medication adherence to prevent complications. However, adverse drug reactions (ADRs) can undermine adherence and negatively affect patients' quality of life. Limited research has explored the association between ADRs, medication adherence, and health-related quality of life (HRQoL) in individuals with hypertension. To investigate the association between ADRs, medication adherence, and HRQoL among patients with hypertension. A cross-sectional study using telephone interviews and medical record reviews was conducted in 11 primary care facilities in Indonesia. The causality of reported ADRs was assessed using the Naranjo algorithm, validated by a panel of experts in pharmacy practice and medication safety. The severity of ADRs was classified using the Hartwig scale. Adherence to antihypertensive drugs was estimated using the Medication Adherence Report Scale-5 (MARS-5). The EuroQoL EQ-5D-5L was used to measure HRQoL. The association between ADRs and medication adherence was assessed using multivariate logistic regression, while the association with HRQoL was evaluated through the Tobit regression model. A total of 507 patients were included in this study. We found that 20.32% (n = 103) of the patients experienced ADRs, with the most commonly reported ADRs being polyuria and urgency, gastrointestinal symptoms, leg swelling, dizziness/hypotension, palpitations, and dry cough. The majority experienced mild ADRs (n = 75, 72.82%), while 27.18% (n = 28) had reactions of moderate severity. Experiencing ADRs was associated with reduced medication adherence (adjusted odds ratio (OR) 7.15, 95% CI 4.07-12.55) and decreased HRQoL (coefficient: - 0.037). Patients experiencing ADRs were seven times more likely to be non-adherent to their medication regimen and reported a reduced quality of life compared to those without ADRs, placing them at a higher risk of suboptimal treatment outcomes. This finding highlights the need for additional monitoring and education for patients affected by ADRs, particularly through more frequent clinical and laboratory assessments, timely management of ADRs, and personalized education on the importance of adherence to prevent hypertension-related complications.

EQ‑5D‑Y-3L population norms for children and adolescents in Jiangsu, China

ObjectiveThis study aims to establish EQ-5D-Y-3L population norms in Jiangsu, China by conducting a large-scale cross-sectional survey.MethodsChildren and adolescents aged 9–17 from three cities of Jiangsu Province were selected by multistage stratified random sampling to complete the EQ-5D-Y-3L instrument independently. Population norms for Jiangsu, China were determined by calculating statistics based on age and gender. Logistic and Tobit regression models were employed to explain the relationship between HRQoL and factors such as sociodemographic characteristics/recent acute symptoms (experienced fever/cough/sore throat/diarrhea in the past two weeks).ResultsThree cities yielded 37,574 valid samples (a sample validity rate of 95.4%). The EQ-5D-Y-3L utility values (mean ± SD) were 0.964 ± 0.085 for males and 0.958 ± 0.077 for females. Males scored 85.94 ± 19.62 and females scored 84.83 ± 18.45 on the VAS (mean ± SD), while the percentages of respondents reporting full health ranged from 58.3 to 78.8%. The dimension in which most respondents reported having no problems was “feeling worried, sad, or unhappy” (23.0%). And the lowest HRQoL was shown in the 14-year-old age group. Gender, age, board at school, and BMI were found to have an association with HRQoL. In addition, recent acute symptoms also correlate with some aspects of HRQoL.ConclusionsThis study established EQ-5D-Y-3L population norms in Jiangsu, China for the first time. These norms will support resource allocation decision-making and be used as a reference for health evaluation studies.

Unlocking Global Innovation

In the dynamic landscape of global innovation, researchers increasingly adopt an integrated approach using nonparametric and regression techniques. This study highlights the significance of this method in enabling countries to understand external factors shaping innovation outcomes. Data Envelopment Analysis (DEA) serves as a robust framework for evaluating innovation efficiency, helping countries optimize their innovation processes by scrutinizing resource utilization and identifying areas for improvement. Complementing DEA, Tobit regression analysis offers insights into the nuanced influence of external drivers on innovation. The findings reveal a mixed landscape: while high-income countries dominate innovation efficiency, some lower-middle and low-income countries show notable proficiency. China, classified as an upper-middle-income country, emerges as the most referenced benchmark. Based on benchmarking, inefficient countries can enhance their innovation policies and strategies, helping to bridge the global innovation gap. Despite all input capabilities showing a negative correlation with innovation efficiency, all output variables exhibit a positive correlation. Notably, there was no association between R&D and innovation efficiency in 2020, highlighting the need for judicious use of innovation inputs to avoid wastage. Additionally, the Tobit regression model exhibits a remarkable R-squared value of 0.8523, indicating that the 16 independent factors account for 85.23% of the variation in the innovation efficiency. Amidst technology-driven transformations, leveraging nonparametric analysis methodologies is essential for organizations aiming to thrive in the global innovation arena. This study highlights the crucial role of DEA in assessing innovation efficiency and emphasizes the importance of incorporating nonparametric analysis and regression techniques into strategic decision-making processes to formulate effective innovation policies.

Digitalization and Operational Efficiency in Fisheries: Evidence from China

Fisheries contribute significantly to the global economy while playing a crucial role in environmental conservation, food security, and socio-economic development. Analyzing the operational efficiency of the fisheries industry not only enhances its economic and social benefits but strengthens the sector’s capacity for sustainable growth. This study initially evaluates the operational efficiency of Chinese fishery-listed companies using the DEA-BCC model and Malmquist index, both statically and dynamically, from 2012 to 2022. It then investigates the impact of digital transformation on the operational efficiency of these companies using the Tobit regression model. The findings reveal that the mean values of comprehensive, technical, and scale efficiency for Chinese fishery-listed firms are below 1, with scale efficiency exhibiting particularly low mean values under static conditions. Additionally, during the observation period, these companies’ average total factor productivity decreased by 0.1% annually compared to the base period. From a dynamic perspective, the decline in total factor productivity can primarily be attributed to reduced technical efficiency resulting from decreased scale efficiency. Ultimately, it can be reasonably concluded that the operational efficiency of listed fishing firms can be significantly enhanced by implementing digital transformation. This underscores the potential of digitalization as a critical factor in advancing the fisheries sector, facilitating modernization, and enabling intelligent upgrading across the industry.

Analysis of Factors Influencing Agricultural Commercialisation Among Youth Group in Agricultural Output Market: Empirical Evidence from Mwanza City and Ukerewe Districts, Tanzania

Although agriculture has great potential for Sub-Saharan Africa particularly in the creation of decent jobs for youth, the youth are less attracted and reluctant to pursue agriculture as both a career and activity for livelihood due to several aspects. For this reason, the study examined the Agricultural Commercialisation among youth groups in the agricultural Output Market in the Mwanza region, Tanzania. The cross-sectional study used a quantitative and qualitative approach and included ninety-three (93) youth groups from two selected Districts (Mwanza City and Ukerewe District) Data were analyzed with the Commercialisation Index and Tobit Regression Model with the aid of statistical tools for analysis which were R-Software (Ri3863.6.1) and SPSS version 20. The results showed that the commercialisation index for this study is about 79.4 %, then empowered youth groups were highly participating in the agricultural output market for both Mwanza City and Ukerewe District. This justifies the assumption of the Commercialisation Index (CI) when CI is greater than 50% of farmers are considered they be commercial oriented which in other words they participate in agricultural output markets. Moreover, the degree of participation in agricultural output among empowered youth groups was also influenced by market experience, market arrangement and market infrastructure. The participation of empowered youth groups from both agricultural output markets seemed also to be determined by the education level of group leaders. Youth groups in which their leaders had attained diploma education level had less participation in the agricultural output market as compared to groups with leaders who attained primary school education level

An integrative study on the green cultural industry and its determinants in Jiangsu province, China under the cultural revitalization initiative: a global perspective.

The cultural industry is pivotal in promoting sustainable economic development. This study aims to evaluate the economic efficiency of the cultural industry in Jiangsu Province by establishing a Data Envelopment Analysis (DEA) model and analyzing influencing factors using the Tobit model, all within the broader context of China's cultural industry. A DEA model was developed to assess the economic efficiency of the cultural industry across Chinese provinces, allowing for a comparative analysis of performance. The Tobit regression model was utilized to investigate factors influencing these efficiency outcomes, with a particular emphasis on inter-provincial comparisons to understand the position and challenges faced by Jiangsu's cultural industry. Despite Jiangsu's cultural industry ranking among the largest in scale nationally, its economic efficiency is only moderate, consistently experiencing diminishing returns to scale. The study identifies low scale efficiency, small enterprise size, and suboptimal urbanization processes within the province as the main issues. The inefficiencies highlighted by the DEA model suggest a misalignment between the scale of operations and the economic outputs in Jiangsu's cultural industry. Urbanization emerges as a crucial factor, with current practices not sufficiently supporting the growth potential of the cultural sector. Based on these findings, the study proposes targeted policy recommendations for Jiangsu, including avoiding blind scale expansion, adjusting industrial structures, encouraging enterprise consolidation and optimization, and identifying new growth areas to better support the cultural industry's development and contribute to sustainable economic progress.

ASSESSMENT OF AGRICULTURAL LIVELIHOOD DIVERSIFICATION FOR SELF-CARE AMONG FEMALE YOUTH FARMERS IN KADUNA SOUTH LOCAL GOVERNMENT AREA, KADUNA STATE, NIGERIA

The study examined the agricultural livelihood diversification strategies for self-care among female youth farmers in Kaduna South Local Government area of Kaduna State. The specific objectives were to: examine the extent of female youth diversification strategies in agricultural livelihood activities in the study area; examine the extent of use of livelihood income on female youths’ self-care, and determine the factors influencing categories of livelihood diversified among the female youths in the study area. A multi-staged sampling procedure was used in selecting 131 respondents and primary data were collected with the aid of structured questionnaire. Descriptive statistics and Tobit regression model were used for data analysis. The results showed that 44.0% of female youth were engaged in processing and value addition activities while 21.2% of them were engaged in production activities and about (48.0%) of them were engaged in more than one livelihood activities. The findings further revealed that livelihood diversification strategies were influenced by level of education (2.550), agricultural experience (0.001) and number of livelihood activities (0.626) among others. Thus, the study recommends that government and private organization should provide financial support and entrepreneurial training to female youth to boost their capacity to diversify to more and better livelihood activities, thereby keeping them away from youth restiveness

Towards environmental sustainability: an empirical study on airports efficiency

ABSTRACT The transition to more environmentally sustainable production processes and managerial practices is an increasingly important topic. Many industries need to undergo radical change to meet environmental sustainability requirements; the air transport industry is no exception. In this respect, a particular aspect that needs further attention is the relationship between airport performances and investments in environmental sustainability policies. This work represents the first attempt to provide empirical evidence about this relationship. Through the application of a non-parametric method, we first assess the efficiency of the Italian airports’ industry. Secondly, we investigated the relationship between airports’ performance and management commitment towards the ecological transition using a Tobit regression model. The results show that airports’ adherence to formal multi-year ecological transition programmes has a positive and consistent impact on their performance.

Determinants of Microfinance Demand (Evidence from Chiredzi Smallholder Resettled Sugarcane Farmers in Zimbabwe)

Despite the MFI insurgency, agricultural financing remains critically low, even though microcredit is widely accepted as both a substitute and compliment to formal credit. Zimbabwe is an agro-based economy and very little is known about the determinants of microcredit demand and microcredit size in smallholder resettled sugarcane farmers. Research is concentrated in short-term agriculture activities. Thus, this study aims to fill the unattended gap in lagged returns agriculture activities such as sugarcane production which takes at least a year to mature, hence, the greater need for agriculture financing alternatives such as microfinance. The study examined the determinants of both microcredit demand and loan size (magnitude of microcredit participation) by smallholder resettled A2 sugarcane farmers in Chiredzi. Primary data from 370 smallholder resettled sugarcane farmers (214 borrower participants and 156 non-borrower participants) were used. Probit and Tobit regression models were used for data analysis in STATA. Operational costs, interest rate, grace period, and land size significantly affect both the demand for microcredit and microcredit size, while education, household farming assets, extension services, and payback period significantly affect microfinance demand, and risk attitude/perception additionally determine microcredit size. Special microfinance schemes best suitable for the agriculture sector and crop/plant-specific agriculture financing schemes, currency, and macroeconomic stability are the major policy recommendations.

GLOBAL–LOCAL DRIVING FORCES of CHINA’S GREENING of INDUSTRY

ABSTRACT The greening of industry is an inevitable path for developing economies to achieve sustainability transition. However, the specific roles of global and local driving forces are still not substantially understood. This study develops a three-dimensional framework, which includes coercive pressures, normative pressures, and technology acquisition to analyze the influence of global and local drivers on China’s greening of industry. We measure the industrial eco-efficiency (IEE) using Super-SBM model and analyze its influencing factors using the Tobit regression model at the provincial level in China from 2010 to 2020. China’s IEE evolution and its drivers are stage-specific and regionally differentiated, and differences also exist in the roles of global and local drivers. Developing countries initially start the green development of industry under global normative pressures through integration in the global production network. Thereafter, global coercive pressures and local forces, including domestic technologies, market demands, and effective regulations, drive the further greening of industry. The different potentials of regional coercive and normative pressures depend on industrial structures and socio-technical regimes. Policy recommendations for the greening of industry in developing economies are proposed.

Knowledge and perceptions towards organic farming: a case of pineapple farmers in central Uganda

This study examined the knowledge and perceptions as well as factors that influence the knowledge and perceptions of pineapple farmers towards organic farming in Uganda. Through multi-stage sampling procedures, purposive and random techniques were applied at different stages to select participants from both Luwero and Kayunga districts in central Uganda. Data was collected using a semi-structured questionnaire. A composite index for knowledge and perceptions was computed for each respondent and subjected to descriptive statistics while the censored Tobit regression model was used to determine factors that influenced farmers’ knowledge and perceptions of organic farming. Results showed that both organic and non-organic farmers had a high level of knowledge and favorable perceptions towards organic farming with no significant difference. Perceived environmental and economic benefits of organic farming did not significantly differ (p > 0.05) among organic and non-organic farmers. However, mean scores for perceived health and nutritional (4.30 vs. 3.94) benefits, and access to markets (4.10 vs. 3.89) differed significantly (p < 0.05) between organic and non-organic farmers. There was a positive and significant relationship between knowledge and perception of organic farming among non-organic farmers while for organic farmers, a significant and negative relationship was observed. Factors that significantly influenced farmers’ knowledge were information sources and farmers’ experiences. Farmer perceptions were influenced by education, information sources, group membership and extension services. Therefore, to enhance the adoption and growth of organic pineapple production in Uganda, policymakers and promoters should consider these factors when designing policy documents and sustainability strategies for the development of organic agriculture.

Influence of socio-economic variables and extension inhibitors on food sovereignty in Akwa Ibom State, Nigeria

This study assessed the influence of socio-economic variables and extension inhibitors on food sovereignty in Akwa Ibom State, Nigeria. This study identified and proffered solutions to extension inhibitors to food sovereignty. A multi-stage sampling technique was used to select one hundred and twenty respondents used for the study. Data analysis comprised the use of percentages, frequency, means and Tobit regression model. The result of the socio-economic characteristics of the respondents showed that 27.50% of the respondents were from 41 and more years of age, while 25.00% were within the age range of 31 to 40 years. 8.33% of them were in the age brackets of 20 to 30 years. Majority of the farmers were very strong, agile and could adopt extension teaching methods easily. About 49.17% of the respondents were at tertiary level of education, while 23.32% had primary level of education. The result showed the mean (x ̅) response rate of extension inhibitors on food sovereignty as follows; inadequacy of funds (x ̅ = 4.65), use of poorly trained personnel (x ̅ = 4.04), ineffective research extension linkage (x ̅ =4.21), lack of evaluation (x ̅ = 4.422), poor policy (x ̅ = 4.04) among other factors. The hypothesis showed that gender, marital status and farm size were positive and significant at 1% level of probability. The result of the HO1, showed that any increase in farm size led to a corresponding increase in the probability and intensity of extension inhibitors on food sovereignty in the study area. Also, the coefficient of education was positively signed but not significant. This showed that education though very important but had no severe influence on the extension inhibitors. In the result, there was significant relationship between socio-economic variables and extension inhibitors on food sovereignty in the study area. The study concluded that some of the inhibitors of extension on food sovereignty are; inadequate funding, lack of extension service evaluation on food sovereignty situations, ineffective research extension linkage and use of poorly trained personnel. The study also concluded that majority of the farmers are of age and well educated to positively influence extension inhibitors with the view to improving food sovereignty situations in the study area. It was recommended that women being the majority in the study area should be involved in extension activities and evaluation, with a view to improving on food sovereignty. Key words: Akwa Ibom, Extension, Food Sovereignty, Influence, Inhibitors, Socio-economic and Variables

Cultural Industry Agglomeration and Carbon Emission Performance: Empirical Analysis Based on 276 Cities in China

This study investigated the influence of cultural industry agglomeration on the energy carbon emission performance (CEP). Based on panel data from 276 cities in China, we used the Super-SBM model to measure the CEP. We then used the Tobit regression model to calculate the influence coefficient of cultural industry agglomeration and eight control variables on the CEP and analyzed the complex effects of cultural industry agglomeration on the CEP. The results showed that there is the phenomenon of “diseconomies of agglomeration” in cultural industry agglomeration, which cannot improve the CEP. For each unit of cultural industry agglomeration increase, the CEP decreases by 0.055; however, this phenomenon is not linear. Further research showed that the effects of cultural industry agglomeration showed a trend from good to inferior in the order of east, central, and west and did not improve with time. Finally, we used the panel quantile regression model and found that as the CEP levels rise, the negative impact of cultural industry agglomeration improves. Our research results show that strengthening the technical level to promote the upgrading of the cultural industry is the best way to achieve sustainable development. Governments at all levels should pay attention to the emission reduction potential of cultural industry agglomeration under high CEP levels and strengthen the benign agglomeration of the cultural industry.

Intensity of Adoption of Improved Malt Barley Production Technologies in Ethiopia: A Case Study in Oromia Region

Improved malt barley production technology packages are not yet widely adopted in Ethiopia. Stakeholders, including brewers, malt factories, research institutes, and farmer-based organizations, have been collaborating and promoting new malt barley production technologies in order to boost the intensity of acceptance. The aim of this study was to find out the intensity of improved malt barley production technologies adoption in Arsi zones, Oromia region, Ethiopia. A stratified random sampling approach with multiple stages was employed to collect primary data from 384 malt barley household heads. The data was analyzed using descriptive statistics, and the intensity of adoption of improved malt barley production technologies was determined using an econometric Tobit regression model. The findings specified that the most adopted improved malt barley variety was Traveler (47.92%), which was followed in descending order by Iboni (14.58%), Sabini (9.38%), Grace (5.47%), Holker (4.43%), and 18.23% unnamed varieties. The Tobit model result also depicted that the intensity to which improved malt barley varieties adopted were affected by, taking into account factors including contract farming involvement, cooperative membership, off-farm income, size of livestock holdings, access to training, and mobile ownership. Enhancing farmers’ knowledge of the advantages of contract farming, income diversification, and mobile phone-based information delivery are among the many ways to support access to and accelerate the adoption of improved malt barley technology in the research area and beyond.