Production Sector Research Articles

Effect of Cultivation at Different Altitudes on the Chemical, Functional and Pasting Properties of Starch Medians Cultivar Potato (Solanum tuberosum L.)

The cultivation elevation of potatoes plays a crucial role that influences starch quality. Little is known on the impact of varying altitudes on starch quality. Therefore, this new study analyzed the starch attributes of the Median?s potato variety (Solanum tuberosum L.) cultivated at three distinct altitudinal zones: lowlands, midlands, and highlands. The objective was to elucidate the impact of these varying altitudes on the chemical composition, functional qualities and pasting behavior of starch derived from the Median?s cultivar. Utilizing a randomized block design with quadruplicate trials, the data was subjected to one-way ANOVA and Duncan?s Multiple Range Test, at a 5% significance threshold. The results show that highland and midland plantings yielded a higher starch production. The cultivation altitude had a significant influence (p < 0.05) on several chemical parameters of the starch, including its moisture, protein, lipid content, total starch, amylose, ash and phosphorus contents. The functional properties, such as swelling volume, solubility, water and oil absorption capacities, syneresis, gel strength, and colors (a*, b*, L* values) also exhibited significant variance with altitude. Furthermore, pasting qualities also were altered by the altitude of potatoes cultivation. X-Ray Diffraction (XRD), particle size analysis, granule morphology via microscopy and Fourier Transform Infrared Spectroscopy (FTIR), revealed significant differences (p < 0.05) across starches from different altitudes, confirming the influence of environmental conditions on starch quality and its functional properties. These results provide valuable recommendations for customizing potato farming methods to enhance starch yield and their applications in various food production sectors.. KEYWORDS :Cultivation altitude, Cultivar, Farming methods, Functional properties, Starch quality.

Development of gadgets and systems in plastic for use in freshwater aquaculture

The usage of plastics has transformed the agricultural production sector and has great impactin improving the overall scenario in all production systems including fisheries and aquaculture.Nylon fishnets, components of RAS, aquaponics and biofloc (BF)systems, plastic pipe framed nylon net cages, pen culture in water locked areas, etc. are some of the important uses of plastics in aquaculture. The AICRP on PEASEM, ICAR-CIFA, Bhubaneswar Centre is working since its inception in 1988 and contributed several plasticulture technologies and products for the development of aquaculture systems and processes (APA/CIFA 1988-2005; Mohapatra et.al., 2003, 2011 and 2016). The design and fabrication of the plastic gadgets and systems have been done considering the biological requirements of the aquaculture. The developed technologies are fully or partially adopted and accepted by the farming communities of the country. The paper presents some of the developed gadgets and systems that are presently in use in aquaculture in the country. Those are portable FRP carp hatchery having capacity of 1.0-1.2 million spawn production per cycle; portable FRP magur hatchery for incubation of 50,000 eggs per cycle; portable FRP pabda hatchery for production of 25,000-30,000 early fry per operation; different types of fixed and floating cages; live fish transportation tank of 1200l capacity which can be transported in a jeep trailer, power trailer or trolley; FRP silos of different sizes for fish rearing; feeders of different types such as demand, semiautomatic and automatic for fish feeding; plastic covered ponds for raising fishes in winter season; floating nursery for fish seed and aquaponics.. KEYWORDS :Modern farming Technique, Gedgets Plastic, Aquaculture

Analysis of the Communication of Social Responsibility by Energy Companies in Romania

Abstract The awareness towards global changes has increased in recent years and has created pressure for energy providers to improve not only their activity but also the way they communicate their actions, initiatives and commitments and how they report them to the general public. Recognizing this imperative, in January 2022, the European Commission proposed the Corporate Sustainability Reporting Directive (CSRD) to revise and strengthen the existing Non-Financial Reporting Directive (NFRD). With the CSRD's help, sustainability reporting is getting a significant improvement. Now, everything is more transparent and matches up better than other reports created before because it was built around transparency first. This means way less guesswork for anyone needing this information whether it is an investor trying not to worry about their next big decision, consumers, or regulatory bodies. We analyzed the top 15 entities in the electrical energy production sector in Romania, based on their turnover reports at the end of their financial activities for 2022, and we wanted to find out how they articulated and showcased their commitment to social responsibility through their websites and non-financial reports. By examining these reports closely, we uncovered layers of commitment across different sectors from ESG pillars (environmental, social, and governance) – how businesses dedicated to sustainable growth and interacted with stakeholders and by looking closely at these reports, the analysis is not only a point of reference for industry practices but also a better understanding of social responsibility in the specific context of the energy sector.

Crop Disease Prediction Using Web Application

Abstract: Agriculture plays a very vital role in our life. Without agriculture, the existence of human beings is not possible as it is the main source of our food supply to sustain on the earth and it also helps to grow our economy across the world. Plant disease detection is one of the most important aspects of maintaining an agriculturally developed nation. The timely and efficient detection of plant diseases is essential for a healthy and productive agricultural sector. Various diseases like Common Rust, Bacterial Spot, Leaf Mold, Mosaic Virus, Powdery Mildew and others that could affect a plant and cause farmer to lose a substantial sum yearly. Deep Learning (DL) can play a crucial role in helping farmers to prevent crop failure by early disease detection in plant leaves. In the experiment, examination conducted by Convolution Neural Network (CNN) model on dataset (which consists of images of healthy and infected leaves) to detect plant diseases and Web Application is used for real-life crop disease prediction. The proposed Web Application aims to assist farmers in detection of plant diseases by analyzing images of the plant leaves. The proposed application uses the CNN model to distinguish healthy and infected leaves. The goal is to help farmers and prevent economic loss by detecting plant diseases early

The Consumer Price Index and its Role in Influencing Exports, Food Imports, and the Local Output of the Jordanian Agricultural Sector

Jordan is in the east of Asia, with 91971 km2 of land and water of 329 km2. The study examined the consumer price index as an independent factor and its impact on exports, food imports, and the agricultural sector’s local output as dependent factors in the Jordanian economy. The study took the period from 2006 to 2016 as a sufficient period for measurement, as the agricultural sector is important in the process of economic development, so it was necessary to study the factors affected by the process of changing the price structure represented in the index of the consumer price, as this factor is important in decision-making by businessmen and government alike. To express these variables, statistical measures had to be taken in the analysis, based on finding the simple linear regression of the dependent and independent factor by least squares and testing the estimated equation to avoid measurement errors. The relationship between the different variables influenced by the consumer price index, which the study was taken into, represents the column of this sector of production, export, and import. Under globalization, a country cannot be satisfied with its production and self-sufficiency. Still, there is an external world that carries out open international trade according to each country’s comparative advantage, and we believe that Jordan possesses this comparative advantage in the agricultural sector due to its land and work resources. Still, the circumstances surrounding the rise in prices affect this sector. As for the trade balance and Jordan’s entry into the International Trade Organization, the door has been opened for external work in intra-trade with external knowledge until the price increase affects the exported products’ prices. Imported goods can enter at lower prices, which affects the sector. The study found a strong direct relationship between the consumer price index and the agricultural sector’s domestic product, with the addition of economic justifications for these results and the study reached the results and recommendations, the most important of which was finding direct support for citizens in light of the conditions of rising prices and increasing immigrants.

Detection of bacterial spot disease on tomato leaves using a Convolutional Neural Network (CNN)

Tomato diseases have become a major concern to the tomato production sector around the world. A huge proportion of tomato crops deteriorate yearly during growth or after harvesting due to the infections caused by fungus, viruses and bacteria. Early detection of these diseases plays a crucial role in alleviating overall production loss. Over the past decades, farmers have been using visual observation to identify a crop disease in a field. However, the visual observation method is labour intensive, time consuming, and prone to human error. Currently, intelligent approaches have been widely used to detect and classify these diseases. The objective of this study is to design a convolutional neural network VGG16 net architecture that is able to detect tomato diseases on tomato leaves. A model that can successfully detect 5 tomato leaf diseases was developed: (1) Bacterial spot, (2) Early blight, (3) Late blight, (4) Septoria leaf and (5) Yellow leaf curl with a training accuracy of 0.9328.

Simulation Approaches Used for Management and Decision Making in the Beef Production Sector: A Systematic Review.

Simulation models are used in various areas of agriculture to better understand the system and assist in decision making. In the beef production sector, a variety of simulation research focusing on various dimensions of the system is available. However, an overview of the available research is lacking. Therefore, a systematic review was conducted to provide an overview of simulation studies of beef production and create an understanding of the simulation approaches used. Scopus, Web of Science, and ProQuest Central research databases were used to search the relevant articles, with the last search conducted in June 2023. Studies that developed or used simulation strategies and used beef cattle as a primary focus of the study were included. The 105 studies included in this review were examined thoroughly to record the authors, year of publication, country of study, type of study, focus area of the study, simulated scenarios, validation methods, and software programs used. There has been growing research interest in simulating beef production systems worldwide, with most studies conducted in North America and Europe. Among these studies, the majority (84.76%, n = 89) are biophysical or bioeconomic study types and use deterministic approaches (n = 42). Additionally, most studies have a whole-farm scope (38.09%, n = 40) and focus on productivity (51.43%, n = 54). Since only less than half of the studies mentioned the validation techniques and software programs used, there is a need to improve the availability of this information to ensure that the models are adopted effectively in decision making.

Projected effects of climate change in precipitation and streamflows of the Upper Orinoco River Basin from global and regional climate models

ABSTRACT We studied the projections of streamflows under climate change scenarios in the Upper Orinoco River Basin by using precipitation from 15 global and regional climate models for the period 2020–2099. For this purpose, we calibrated and validated a hydrological model with a very good performance. Our results show that both precipitation and streamflow have a significant reduction for the RCP8.5 scenario that ranges from 5 and 7% in relation to the long-term means at the end of the century. The changes in both variables are not significant for the RCP2.6 scenario. Moreover, we compute several indicators of change in the streamflow to quantify alterations in high-, mid-, and low-range flows. Our results suggest that the main alterations for the future runoff would be evidenced in the mid-range and low flows, which could increase around ∼5 and ∼25%, respectively. These alterations could lead to changes in the hydrological, environmental, and ecological balance of the basin. This work provides information regarding the possible effects of climate change on the streamflow of one of the most important river basins of northern South America, which is pivotal for supporting future decision-making on water supply for social, environmental, and productive sectors.

Current Challenges and Future Outlook: Trends and Forecasts in the Mariculture Sector

Aquaculture, defined by the United Nations Food and Agriculture Organization (FAO), encompasses the farming of aquatic organisms for food production, offering a promising solution to global food security challenges. Over the past three decades, global aquaculture production has consistently grown at approximately 8% annually, outpacing other major animal food production sectors. Mariculture, a subset of aquaculture focusing on marine organisms, has emerged as a critical component, accounting for a third of global aquaculture production.However, mariculture faces numerous challenges, including environmental impacts, reliance on wild inputs, and concerns about genetic interactions with wild populations. Biotechnological advancements offer potential solutions but must be balanced with considerations of ecosystem health and societal impacts.Integrated mariculture techniques and bioremediation approaches present opportunities to mitigate environmental impacts, but legislative frameworks and monitoring procedures are essential for ensuring compliance and minimizing adverse effects. Collaborative efforts between the public and private sectors are crucial for advancing sustainable practices and unlocking the full potential of the mariculture sector.In conclusion, addressing the challenges facing mariculture requires a comprehensive approach that prioritizes environmental sustainability, regulatory compliance. By embracing sustainable practices and fostering collaboration, the mariculture sector can navigate its challenges and contribute to global food security in a responsible and resilient manner.

Assessment of antimicrobial activity and GC-MS using culture filtrate of local marine Bacillus strains

Secondary metabolites produced by Bacillus species from marine sources encompass a variety of compounds such as lipopeptides, isocoumarins, polyketides, macrolactones, polypeptides and fatty acids. These bioactive substances exhibit various biological activities, including antibiotic, antifungal, antiviral, and antitumor properties. This study aimed to isolate and identify a particular species of Bacillus from marine water and organisms that can produce bioactive secondary metabolites. Among the 73 Bacillus isolates collected, only 5 exhibited antagonistic activity against various viral and bacterial pathogens. The active isolates were subjected to 16S rRNA sequencing to determine their taxonomical affiliation. Among them, Bacillus tequilensis CCASU-2024-66 strain no. 42, with the accession number ON 054302 in GenBank, exhibited the highest inhibitory potential. It displayed an inhibition zone of 21 mm against Bacillus cereus while showing a minimum zone of inhibition of 9 mm against Escherichia coli and gave different inhibition against pathogenic fungi, the highest inhibition zone 15 mm against Candida albicans but the lowest inhibition zone 10 mm was against Botrytis cinerea, Fusarium oxysporum. Furthermore, it demonstrated the highest percentage of virucidal effect against the Newcastle virus and influenza virus, with rates of 98.6% and 98.1%, respectively. Furthermore, GC-MS analysis was employed to examine the bioactive substance components, specifically focusing on volatile and polysaccharide compounds. Based on these results, Bacillus tequilensis strain 42 may have the potential to be employed as an antiviral agent in poultry cultures to combat Newcastle and influenza, two extremely destructive viruses, thus reducing economic losses in the poultry production sector. Bacteria can be harnessed for the purpose of preserving food and controlling pathogenic fungi in both human and plant environments. Molecular docking for the three highly active derivatives 2,3-Butanediol, 2TMS, D-Xylopyranose, 4TMS, and Glucofuranoside, methyl 2,3,5,6-tetrakis-O-(trimethylsilyl) was carried out against the active sites of Bacillus cereus, Listeria monocytogenes, Candida albicans, Newcastle virus and influenza virus. The data obtained from molecular docking is highly correlated with that obtained from biology. Moreover, these highly active compounds exhibited excellent proposed ADMET profile.

The right literacy on the right performance: Does Islamic financial literacy affect business performance through Islamic financial inclusion?

This study examines how Islamic financial literacy and Islamic financial access contribute to the performance of Halal MSMEs using knowledge-based theory. Micro, small, and medium-sized halal businesses (MSMEs) have an important role in the economy and the rapid growth of the world halal industry. The success of halal MSMEs depends on a number of factors, including the availability of Islamic funding and the financial literacy of Islamic finance. This study adopted a hierarchical regression model to examine quantitative data from a sample of 209 halal MSMEs' owners and managers in Malang Raya, Indonesia. The findings demonstrate that a high level of Islamic financial literacy can encourage Islamic financial inclusion, while inclusive Islamic financial institutions have a significant impact on MSMEs’ performance. In promoting inclusive Islamic finance, this study contributes by describing how Islamic financial inclusion affects the performance of Halal MSMEs and the level of society's knowledge on Islamic finance. Implications: Once MSMEs have a strong understanding of the Islamic finance principles, they are more likely to use these resources to increase access to Islamic finance; thereby leading to business growth and expansion. For this study, the halal industry within the food and beverage sector is a noteworthy production sector.

Going all in or spreading your bet: a configurational perspective on open innovation interaction channels in production sectors

Abstract Using different interaction channels within open innovation partnerships holds the potential to enhance the chance of success in production sectors. However, our comprehension of how open innovation partnerships are affected by varying combinations of interaction channels, and how this corelates with their level of open innovation output, remains limited. There are discrepancies in the current literature regarding the individual and combined effects of open innovation interaction channels. Our study aims to resolve these inconsistencies by using a configurational perspective, which allows for the identification of multiple successful pathways. Employing fuzzy-set Qualitative Comparative Analysis (fsQCA) to a dataset of European open innovation partnerships in production sectors, we uncover specific combinations of interaction channels that explain high levels of innovation outcomes. Subsequently, we distinguish between two successful pathways. Notably, we observe that the relationship between interaction channels is causally complex, high engagement in open innovation may not guarantee favorable innovation outcomes. This finding highlights the intricate causal dynamics at play. Thus, our study is a significant step toward reconciling the disparate perspectives in the literature concerning the impact of interaction channels on open innovation output.

Impact of Remittance on Educational Outcomes: Empirical Evidence from Nepal

The remittances are the treasure for irrigating Nepal's economy. Because emigration is increasing, per capita remittance is also increasing in Nepal. However, the question is signaling in its utilization for educational attainment. In this context, the study examines the impact of remittance on educational outcomes in Nepal. The study applied autoregressive distributed lag (ARDL) estimations, Granger causality, forecast error variance decomposition (FEVD) technique, and impulse response functions (IRFs), with time-series data spanning from 1981 to 2021. The overall findings revealed that remittance had a positive impact on educational outcomes in Nepal. In the short run, remittance was found to be crucial for secondary schooling; in the long run, remittance had a significant effect on tertiary schooling in Nepal. The FEVD confirmed that remittance might be the inevitable predictor of educational outcomes in Nepal. The Granger causality also found a unidirectional causality from remittance to educational outcomes. The policymakers and stakeholders, therefore, should focus on funneling remittance toward financing education as well as a productive sector to accelerate per capita GDP and on cropping the demographic dividend in the Nepali economy.

Beliefs about raw milk production and consumption and their relationship with health in Miraflores, Boyacá, Colombia

The consumption of raw milk in Colombia continues despite the regulations issued to standardize or prohibit it. In the municipality where this study was carried out, more than 90% of the population chooses to consume this product, being at potential risk of acquiring diseases. The objective of this study was to understand the beliefs surrounding the production and consumption of raw milk and its relationship with health. It was carried out in 2020. Ethnography was used as a method of data collection and analysis. It was found that this phenomenon is related to the economy, identity, and ecology and is a central axis and articulator of various socio-cultural activities. It is guided by traditional production practices that do not fully respect biosafety and hygiene. Furthermore, the consumption of raw milk is socially approved and is the result of a social construction that arose independently of the physicochemical and microbiological properties of raw milk. Furthermore, local and national government regulators are not interested in this productive sector or in the consequences that their practices may have on the health of consumers. Thus, the responsibility for the consumption of raw milk and the possible acquisition of diseases passes from the food industry to the consumer. It is up to each consumer to make raw milk a safe food.

Государственное регулирование занятости женщин и профессиональная сегрегация в российской сфере труда – 100 лет истории. Часть 2. 1945-1991 годы

This paper, based on a general analysis of political documents and legislative acts, examines the changes in the regulation of employment conditions and regimes for women, as well as the dynamics of gender industry segregation. The first part of the article was dedicated to the initial Soviet period and the period of the Great Patriotic War (1917-1945). The second part covers the entire post-war Soviet period (1945-1991), during which there remained a commitment to the idea of maximizing women's participation in the economy. However, perceptions of the conditions for achieving gender equality in employment changed when the country faced the threat of critically low birth rates. As this demographic problem was directly linked to the high total workload of women, a system of benefits and preferences exclusively addressed to working women began to be developed, aiming to create "the most favourable conditions for combining professional and family duties." The implementation of an ever-expanding system of benefits did not lead to the equalization of opportunities for men and women in the labour sphere but contributed to the expansion of labour discrimination by gender and the formation of stereotypical views about jobs most "suitable for men" and "most suitable for women." The article analyzes the dynamics of differences in the sectoral employment structure of women and men based on historical and contemporary statistics, demonstrating that in the Russian Soviet society, committed to traditional gender role divisions, and without pressure on women in their choice of workplace, there was an increase in gender professional segregation due to the concentration of women in non-production sectors and men in material production sectors. The empirical basis for this study relies on data from the Central Statistical Office of the Russian Soviet Federative Socialist Republic (RSFSR) and Rosstat. The statistical analysis of gender segregation dynamics in this study employed the Duncan index, which quantitatively assesses and compares differences between the distributions of women and men across sectors and types of economic activity.

Bridging operations research and machine learning for service cost prediction in logistics and service industries

AbstractOptimizing shared resources across multiple clients is a complex challenge in the production, logistics, and service sectors. This study addresses the underexplored area of forecasting service costs for non-cooperative clients, which is essential for sustainable business management. We propose a framework that merges Operations Research (OR) and Machine Learning (ML) to fill this gap. It begins by applying the OR model to historical instances, optimizing resource allocation, and determining equitable service cost allocations for each client. These allocations serve as training targets for ML models, which are trained using a combination of original and augmented client data, aiming to reliably project service costs and support competitive, sustainable pricing strategies. The framework’s efficacy is demonstrated in a reverse logistics case study, benchmarked against two traditional cost estimation methods for new clients. Comparative analysis shows that our framework outperforms these methods in terms of predictive accuracy, highlighting its superior effectiveness. The integration of OR and ML offers a significant decision-support mechanism, improving sustainable business strategies across sectors. Our framework provides a scalable solution for cost forecasting and resource optimization, marking progress toward a circular, sustainable economy by accurately estimating costs and promoting efficient operations.

Impact of COVID-19 pandemic on some fiscal and monetary indicators in the kingdom of Saudi Arabia

PurposeThe purpose of this study is to investigate the impact of COVID-19 on some fiscal and monetary indicators in the Kingdom of Saudi Arabia.Design/methodology/approachThe research relied on data, studies and reports issued by the International Monetary Fund, Arab Monetary Fund, Saudi Central Bank, Investing Website and the World in Data Website.FindingsMany sectors have been affected by the COVID-19 pandemic, which outbreak has been associated with a high cost, in addition to increased inflation and prices, a result that was confirmed by the increase in consumer price indices for different sectors. The general consumer price index for the second period rose above that of the first period, while an upward shift occurred in the curve depicting the Saudi Riyal exchange rate against the United States (US) dollar during the second period above that of the first period, only in slope, due to outbreak of the pandemic. Impact of the number of daily new cases infected with COVID-19 was the highest on the opening and closing price indices of the food retail sector, the pharmaceutical sector and the transportation sector; while impact of the number of daily deaths by COVID-19 was the highest on the opening and closing price indices of the banking sector, the general index and the investment and finance sector. In addition, impact of the daily reproduction rate of COVID-19 was the highest on the opening price indices of the energy sector, the food production sector and the transportation sector.Research limitations/implicationsThe research aims to demonstrate measures taken by the Kingdom of Saudi Arabia through fiscal and monetary policies.Practical implicationsThe COVID-19 pandemic is still an ongoing global pandemic. The virus was first identified in Wuhan City in China at the beginning of December 2019. At the end of January 2020, the World Health Organization (WHO) declared that the outbreak of the virus represented a public health emergency, and later, on March 11, 2020, WHO declared the situation had transformed into a pandemic. Until January 17, 2022, the pandemic had caused more than 328 million cases and 545 million deaths, while 188 million of the cases had recovered. It is worth mentioning that the pandemic caused several social and economic disruptions, including a global economic recession; shortages in goods, supplies and equipment due to consumers' panic and thus tendency to buy; besides causing other disruptions like the negative impacts on health, as well as political, cultural, religious and sport events that influenced economic policies, including both the fiscal and monetary policies of world countries (Wikipedia, 2022).Social implicationsSocial implications steps that taken to reduce the impacts of the COVID-19 pandemic, in addition to measuring the impacts of the COVID-19 pandemic (as the main event next to which other events fade up) on some of the fiscal and monetary indicators for the Kingdom of Saudi Arabia.Originality/valueThe research aims to demonstrate measures taken by the Kingdom of Saudi Arabia through fiscal and monetary policies to mitigate the impacts of the COVID-19 pandemic, in addition to measuring the impacts of the COVID-19 pandemic (as the main event next to which other events fade up) on some of the fiscal and monetary indicators for the Kingdom of Saudi Arabia.

Coal price shocks, investor sentiment, and stock market returns

The development of energy finance and the financialization of bulk commodities has deepened the financial attributes of coal, resulting in coal price shocks not only affecting the macroeconomy through the production sector, but also further affecting the financial market. This study investigates the dynamic impacts of coal price shocks on stock market returns accounting for the macroeconomic path by using a time-varying parameter vector autoregressive with stochastic volatility (TVP-SV-VAR) model, as well as examines the role of investor sentiment in the transmission of coal price shocks to the stock market. The results show that coal price shocks have a significant negative impact on Chinese stock market returns, but the impact degree is time-varying, particularly larger during economic downturns. Moreover, individual investor sentiment provides an important channel in the transmission of coal price shocks to the stock market. Insights gleaned from the findings in this study are useful for coal industry regulation policy formulation, market investment decision-making and energy market risk management.

A methodological framework for assessing sustainability aspects of fruit and vegetables

Current European policies and the growing focus on sustainability show a clear need for defining and measuring aspects of sustainability at the food product level. The aim of this study was to develop an indicator-based framework to monitor the sustainability of fruits and vegetables. The framework includes production, packaging, transport, and distribution, and considers economic, ecological, and social aspects. The framework aims to be used by the food production and distribution sector and is intended to use specific data from the value chain for higher relevance for the food industry. Results of a sustainability assessment of carrots are presented, as the first example of application of the framework. Future research should focus on the framework's validity when applied to other products and other countries.

Evaluation of High-quality Development of the Construction Industry in the Beijing-Tianjin-Hebei Region

The construction industry is an important production sector of the national economy. The high-quality development level of the construction industry in the Beijing-Tianjin-Hebei region is explored, taking into account the role of the fast-growing areas in pulling the same industry to the surrounding areas. The high-quality development index system of Beijing-Tianjin-Hebei construction industry is constructed from three aspects of economic orientation, economic benefit and good life construction. A case study based on data from 13 cities in Beijing, Tianjin and Hebei proved that there is a big gap in the development of the construction industry in the region, Hebei region is an important breakthrough point.