Input Technology Research Articles

Interventions in location specific technologies and material utilization through Women Technology Park in India

For any developing country, rural infrastructure development and expanding farming and the non-farming economy will be the major area to look forward to inclusive growth. To eradicate poverty and to have holistic growth primary approach should be towards developing employment potential, creation of enterprises and livelihood enhancement in rural people through region-specific technologies using indigenously available resources. The establishment of Women Technology Park (WTP) proposed in this research work will lay emphasis on promoting appropriate technological inputs that may improve productivity. Also, the quality of farm and non-farm sectors will be enhanced with supreme livelihood options in tandem with skill enhancement and capacity building. They also promote developing management skills coupled with the entrepreneurial mindset and will enable them to introduce new and innovative technologies. This kind of parks will promote usage of indigenous resources with increased energy and ecosystem management. Hence, it is envisaged that this kind of establishments, if done such as “Technology parks” will help to create a concrete and also tangible socio-economic benefits to the rural society by provision of newer technological solutions, alternate training method implementation which will end up in unique skill development and also will increase the support rendered for their implementation. In this research work, authors considered four different location-specific techniques for interventions including weaving technology, metal art skill development, banana fiber extracting and usage, habitat and construction technology development. Through the establishment of WTP, these technologies were tested first, and the rural women were trained to sustain via usage of those technologies for their livelihood.

COVID‐19 and Fiji: A Case Study

<scp>COVID</scp>‐19 and Fiji: A Case Study

An Integration of Business Model Canvas on Prioritizing Strategy: Case Study of Small Scale Nontimber Forest Product (NTFP) Enterprises in Indonesia

Nontimber forest products (NTFPs)‬ are one of the forest products that can provide direct benefits to communities living around forests. Some of the most used NTFPs in Indonesia are the stems, leaves and fruit of candlenut trees. Candlenut fruit is widely used in the cosmetics, pharmaceuticals, and biodiesel industries and is generally used as a cooking ingredient in Indonesia. However, only a limited number of people or community groups manage the forests to increase their income from this business. The aim of this study is to identify business models to serve as the basis for developing alternative business model organizational plans for candlenut extraction. A case study approach was adopted, with in-depth interviews used to collect data. The integration of Business Model Canvas, SWOT Analysis, Internal Factor Evaluation and External Factor Evaluation matrix were used to determine alternative strategies. The results exhibit that the value proposition is the largest barrier for the improvement of these businesses. The Positioning Quadrant SWOT shows that internal factors (strengths and weaknesses) are low, indicating that the candlenut business position is internally weak. However, the scores of external factors (opportunities and threats) are higher implying that there is a great opportunity in the development of candlenut. The alternative strategies to develop candlenut business are to maintain relationships with customers and partners; increasing the quantity and quality of products through technology inputs, promotion, product diversification, and partnership with the government.‬‬

The effect of trade openness on the relationship between agricultural technology inputs and carbon emissions: evidence from a panel threshold model.

The development of low-carbon agriculture systems has been a global consensus to reduce carbon emissions in the agricultural sector for addressing climate change challenges. This fact brings the need to study the agricultural carbon emissions (ACEs). Studies focusing on calculating the spatiotemporal changes of ACEs and analyzing the main factors for ACE changes have been conducted. The agricultural technology inputs (ATIs) as an important factor to influence ACEs have been identified. The traditional linear model was the commonly used method to study the relationship between ATIs and ACEs, whereas the impact of ATIs on ACEs in different areas might be complex and nonlinear due to the differences in trade openness causing different development levels of agricultural technologies. Therefore, this study aims to investigate the effect of trade openness on the relationship between ATIs and ACEs using a panel threshold model and put forward policy implications for the low-carbon agriculture development. The analysis was based on data from a panel of 31 provinces of China during 2003-2018. The results show that ATIs and ACEs increased from 2003 to 2018 and the spatial distribution of ATIs was similar to that of ACEs. The ATIs had a positive effect on ACEs with a significant single-threshold effect from trade openness. When the trade openness was below the threshold (0.1425), the positive effect of ATIs on ACEs was significant (coefficient, 0.117), whereas, when the trade openness was above the threshold (0.1425), the positive effect of ATIs on ACEs significantly decreased (coefficient, 0.062). Furthermore, industrial structure and agricultural economic development were the positive drivers of ACEs, while trade openness, education level of rural workers, R&D funding, and natural disasters had negative relationships with ACEs. The results provide valuable references for understanding ACE drivers and developing low-carbon agriculture with the consideration of ATIs and trade openness.

Evaluation and diagnosis of obstacles to land-based ecological security in resource-based cities: A case study of Xingtai city.

To provide a theoretical basis for sustainable land resource utilization and a reference for areas with similar natural conditions, an evaluation index for land-based ecological security was constructed based on the Driving force-Pressure-State-Impact-Response (DPSIR) model and the improved analytic hierarchy process (IAHP) and entropy methods, and the land-based ecological security status of Xingtai city from 2006 to 2017 was evaluated. Then, the obstacles to land-based ecological security were diagnosed. The results show that the values of the comprehensive evaluation index of land-based ecological security were 0.28–0.66 in the period from 2006 to 2017. The value of the index of land-based ecological security was low in the first seven years and gradually improved in the last five years of the study period. However, the overall situation was grave, and the ecological security conditions were poor. The main obstacles to land-based ecological security were the usage of pesticides, investment in environmental pollution treatments, the degree of machine cultivation, the rate of cultivation and the usage of fertilizer in Xingtai city. Based on the results of the land-based ecological security evaluation and the main obstacles identified in Xingtai city, this paper proposes management strategies and suggestions for improving land-based ecological security in Xingtai city. The specific proposals are as follows: vigorously develop green agriculture, increase investment in environmental pollution control, increase input in science and technology, and strengthen supervision and management of land use.

The influencing factors of China's green building development: An analysis using RBF-WINGS method

Energy efficiency and emission reduction in construction industry has been concerned in the world. Green building become the focus of academic research in recent years. To fundamentally realize the green development of construction industry, it is necessary to systematically analyze the influencing factors of green building development. On the basis of science and technology investment, industrial size, industry potentiality, and policy incentives, this paper introduced the green financial supportive factor and established a multi-layer green building influencing factors index system. Radial basis function neural network is adopted to improve the Weighted Influence Non-linear Gauge System (WINGS) model, namely RBF-WINGS model, and direct strength-influence matrix is determined. This method objectively analyzed the weights of the green building development influencing factors. The result indicates that science and technology input is the fundamental influencing factor, while industrial size and green financial support are the main influencing factors for the development of green building. This study provides theoretical evidence for the development of green buildings in China and offers decision-making reference for government departments.

Life cycle effects of technology on revenue in the music recording industry 1973–2017

Revenue in the recording music industry is driven by exogenous technology inputs and revisions to the Copyright Act. Each new technology and regulatory change had a financial impact that altered the life cycle patterns in the industry, that in turn led to innovative marketing applications that transformed the production, sale, and distribution of music. The premise that technological change follows exactly the theoretical S-curve in all cases may be misleading and this paper provides an alternative measure. We analyze the life cycle effects of technology on revenue in the music industry using an unbalanced panel instead of a logistic growth model when life cycle curves may be ‘irregular’ and the mathematical approximation is often difficult. When the error terms are corrected for heteroscedasticity and serial correlation, the model measures the increased marginal effects of digital technologies (physical, downloads, digital subscriptions, streaming, and synchronization) on music industry revenue for the years 1973–2017. This paper adds to the growing literature of advanced econometric modeling, machine learning, and artificial intelligence analysis in the music and creative industries.

Forecasting of industrial structure evolution and CO2 emissions in Liaoning Province

A framework for predicting environment should focus on the sources of economic growth, behavioral issues of market participants and the changing structure of the regional economy over time. This paper constructed a multi-agent intertemporal optimization model (MIOM) that include consumer preference, technology input and knowledge accumulation to forecast CO2 emission trends of 13 industrial sectors in Liaoning Province from 2018 to 2030. With the premise of maximizing consumer benefit, the model realizes intertemporal optimization in sector output and investment and obtains the optimal path of economic growth driven by capital. The results show that: (1) Liaoning Province’s economy will maintain the abidance growth driven by investment. Before 2030, the economic growth rate of Liaoning Province is on the rise. (2) Departments with higher consumption preferences will account for a higher proportion of total economic output. And the bigger the gap of consumption preference is, the more obvious the change of industrial structure will be. (3) In the current level of R&D investment and economic growth, the energy consumption structure of most energy-intensive industries in Liaoning will continue to decline in the future except oil industry. (4) Under the influence of R&D investment and knowledge accumulation, the emission intensity of most industrial sectors will continue to decline during the simulation period, and the annual growth rate of CO2 emissions is gradually decreasing.

Influencing factors of spatial variation of national marine ranching in China

The construction of modern marine ranching is an important way to protect coastal ecological environment and efficiently produce marine fishery resources in China. This study analyzed the scale, nature and function of national marine ranching in 11 coastal areas from 2015 to 2019, and identified the problems of quantity and area mismatch and regional development imbalance in the current layout. Then the standard deviation ellipse was used to explore the spatial variation characteristics of marine ranching in China. Geographic detector were then used to detect factors affecting spatial distribution. The results show that the spatial variation presents an obvious flattening trend through time. From 2015 to 2018, the overall center of gravity of marine ranching moved to the southwest. The X-axis first decreased and then increased, while the Y-axis showed an increasing trend from northeast to southwest. Marine ranching construction in Liaoning, Guangdong, Guangxi showed an obvious increase on the long axis. In 2019, the average center moved to the northeast due to the fact that no new national marine ranchings were added in Guangxi, Fujian and other places, while the construction momentum was strong in Shandong and Liaoning. In terms of influencing factors, resource difference, scientific and technological input and economic development levels have a significant influence on the spatial variation of marine ranching, and social factors and policy factors need to interact with other factors to play the role. The conclusions of this study can inform China Government decision making for marine ranching construction in coastal areas.

The state of wearable health technologies: a transdisciplinary literature review

This review evaluated transdisciplinary empirical research on wearable health technologies using the input-mechanism-output model and addressed a major concern relating to the invasiveness of wearables. The dataset consisted of 250 published papers that investigated wearables for health-related purposes. Papers focused on technological inputs and health output factors, de-emphasizing theoretical mechanisms that could effectively translate the former into the latter. The lack of transdisciplinary research in the field is limiting both identification of effectiveness and evidence of beneficial health outcomes, with a considerable divide between technologists and public health researchers. Privacy concerns relate to increasing trends in collecting data for mental health and physical health, with the latter escalating exponentially. Invasiveness of wearables has increased over time in terms of collected signals and the derived health information, monitoring both users and their social and physical environments. We conclude with reflections for conceptual development, commercial application and policy regulation.

The State Kindergarten Entry Assessment Digital Technology Landscape

Over the past 8 years, U.S. kindergarten classrooms have been impacted by policies mandating or recommending the administration of a specific kindergarten entry assessment (KEA) in the initial months of school as well as the increasing reliance on digital technology in the form of mobile apps, touchscreen devices, and online data platforms. Using a sample of KEAs used in 29 states in Fall 2019, in this report I examine the KEA digital technology landscape. Of particular interest was the extent to which states with similar KEA item types incorporated such technology as well as the potential impact of these technology inputs on the role of the kindergarten teacher in the KEA administration, scoring, and report‐generating processes. Analyses of the study's data demonstrated that all 29 states incorporate digital technology into their KEAs. However, differences among states' technological inputs suggested four different models of KEAs along a continuum of supplanting versus retaining teachers' active roles in the administration, scoring, and report‐generating processes. These findings have implications for short‐term research agendas aimed at supporting KEA validity, reliability, and utility.

Application of Biometric Technology in Financial Shared Service Center

With the development of the times, financial shared service center has become more and more diversified and complex and the traditional financial system cannot meet the needs of enterprises. Only by providing services anytime and anywhere can we be invincible. In order to reduce costs and improve efficiency, financial institutions deploy biometric technology in various service channels to ensure user authentication and improve the security and timeliness of business processing. Therefore, this article puts forward the application of biometrics in financial shared service center. In order to verify the advantages of biometric technology, this paper analyzes the efficiency and management cost of biometric technology after it is put into use, and tests the cost change of an enterprise for four consecutive years and the change of personnel age for three consecutive years. Through this analysis, it is concluded that the input of biometric technology is conducive to the control of enterprise cost and the adjustment of personnel structure. In order to further the feasibility of biometric technology, this paper compares the data before and after the reform of enterprise financial system. The results show that the efficiency of financial business processing has increased from 5.8 days to 0.41 days, and the efficiency has increased by 14.15 times, which is in the international high level, and the financial shared service center is more intelligent and efficient. Through the analysis, the research in this paper has achieved ideal results and made a contribution to the application of biometric technology in financial shared service center.

Efficiency of advanced sprayers for nutrient and pesticide application under precision cultivation of spring rapeseed (Brassica napus)

Precision agriculture, which consist of using farming inputs has become the third wave of the modern agriculture revolution in the globe. Evaluation of newly developed technology is necessary before dissemination. Therefore, a study was conducted during 2017-18 in the conditions of the Central Chernozem of the Russian Federation, Voronezh region to study the effectiveness of the new generation sprayer Amazone UX 11200 Isobus in comparison with Amazone UX 5200 Amaspray for using complex tank mixtures that include, the level of intensity of farming inputs such as pesticides and mineral fertilizers. The highest increase in productivity and oil collection per unit area were observed for intensive farming input of Amazone UX Isobus application technology with the value of 2.91 t/ha and 1272 kg/ha, with an enhancement of 89.0 and 86.2% compared to the control, respectively. The effect of precision spraying on reducing the level of intra-field variability of the segmental component of agro-phytocenosis with intensive cultivation technology (from 22.5 to 8.9%) revealed allowing an increase in the efficiency of using these tank mixtures to the tune of 91-97%. The manifestation of the stabilizing effect, on an average, according to the experience was 210%. The economic efficiency of intensive technology in comparison with the basic technology allowed us to reduce the consumption of plant protection products by 5-7%.

External funding and emergent technology inputs

The research and development (R&amp;D) process is critical to a firm’s competitive advantage and often requires external funding. Yet, we know little about how different types of investors respond to the cash needs of established R&amp;D intensive firms nor about how external financial analysts influence those decisions. We address these gaps by examining how a firm’s patenting activity affects its ability to raise cash. We distinguish the motivations of two investor groups: open-market and alliance partners. We focus on how patents based on emergent technologies impact two types of investors and their willingness to fund the R&amp;D process. We develop theory and test our hypotheses using data from publicly traded biopharmaceutical firms by drawing upon knowledge-based view, alliance, and investment theories. We find evidence that patents built upon emergent technologies are viewed differently by the two types of investors. We find open market investors were less likely to invest in emergent technologies and invested less when they did. Conversely, alliance partner investors would be more appreciative of the opportunities new technology inputs present, thus, more likely to invest in firms using emergent technologies and invest more.

Design and evaluation of large area strip sensor prototypes for the ATLAS Inner Tracker detector

The ATLAS community is facing the last stages prior to the production of the upgraded silicon strip Inner Tracker for the High-Luminosity Large Hadron Collider. An extensive Market Survey was carried out in order to evaluate the capability of different foundries to fabricate large area silicon strip sensors, satisfying the ATLAS specifications. The semiconductor manufacturing company, Infineon Technologies AG, was one of the two foundries, along with Hamamatsu Photonics K.K., that reached the last stage of the evaluation for the production of the new devices. The full prototype wafer layout for the participation of Infineon, called ATLAS17LS-IFX, was designed using a newly developed Python-based Automatic Layout Generation Tool, able to rapidly design sensors with different characteristics and dimensions based on a few geometrical and technological input parameters. This work presents the layout design process and the results obtained from the evaluation of the new Infineon large area sensors before and after proton and neutron irradiations, up to fluences expected in the inner layers of the future ATLAS detector.

Agile supply chain management: where did it come from and where will it go in the era of digital transformation?

In today's dynamic business environment, agile supply chain (ASC) has become a key strategic move to cope with market instability, handle competitive pressures and strengthen operational and organizational performance. Meanwhile ASC is a good example of a strategy drawing heavily on digitization since as a demand chain management it was information-centric and technology-centric from its inception. Yet, despite this relationship, a lack of coherence and clarity around the input of technology for ASC has impeded to portray accurately the relative importance of digitization in ASC strategies. This study provides a comprehensive and integrative review of 90 articles on ASC. By so doing, we contribute to the discussion about digitization in the supply chain in several ways. First, the paper reports descriptively and analytically how technology was addressed within the ASC literature. Second, it maps a nomological network of ASC research. Third, it finds that technology appears as a necessary but not-sufficient enabling factor for ASC deployment. Finally, a research agenda is proposed to suggest future research avenues to improve contributions to ASC performance.

Two-part fractional regression model with conditional FDH responses: an application to Brazilian agriculture

We extend the notion of a two-part fractional regression model with conditional free disposal hull efficiency responses to accommodate two-stage regression analysis. The two-part regression model includes the binomial model with a nonlinear specification for the expected response in (0,1] and is a more general formulation in the context of fractional regressions. We use nonlinear least squares to assess the effect of covariates in the conditional efficiency response. The approach is applied to Brazilian agricultural county data, as reported in the Brazilian agricultural census of 2006. The efficiency measure is output oriented and assumes variable returns to scale. Output is rural gross income and inputs are land expenses, labor expenses and expenses on other technological inputs. The covariates affecting production are credit, technical assistance, a rural development index, income concentration, measured by the Gini index, and regional dummies. Overall Brazilian rural production performance responds positively to all covariates.

The Relationship between Environmental Regulation and Green Total Factor Productivity in China: An Empirical Study Based on the Panel Data of 177 Cities.

Promoting the coordinated development of industrialization and the environment is a goal pursued by all of the countries of the world. Strengthening environmental regulation (ER) and improving green total factor productivity (GTFP) are important means to achieving this goal. However, the relationship between ER and GTFP has been debated in the academic circles, which reflects the complexity of this issue. This paper empirically tested the relationship between ER and GTFP in China by using panel data and a systematic Gaussian Mixed Model (GMM) of 177 cities at the prefecture level. The research shows that the relationship between ER and GTFP is complex, which is reflected in the differences and nonlinearity between cities with different monitoring levels and different economic development levels. (1) The relationship between ER and GTFP is linear and non-linear in different urban groups. A positive linear relationship was found in the urban group with high economic development level, while a U-shaped nonlinear relationship was found in other urban groups. (2) There are differences in the inflection point value and the variable mean of ER in different urban groups, which have different promoting effects on GTFP. In key monitoring cities and low economic development level cities, the mean value of ER had not passed the inflection point, and ER was negatively correlated with GTFP. The mean values of ER variables in the whole sample, the non-key monitoring and the middle economic development level cities had all passed the inflection point, which gradually promoted the improvement of GTFP. (3) Among the control variables of the different city groups, science and technology input and the financial development level mainly had positive effects on GTFP, while foreign direct investment (FDI) and fixed asset investment variables mainly had negative effects.

Efficiency Analysis of the Marine Economy in the Guangdong–Hong Kong–Macao Greater Bay Area Based on a DEA Model

Wen, M.; Liu, C.; Galina, P.; Tao, C.; Hou, X.; Bai, F., and Zhao, H., 2020. Efficiency analysis of the marine economy in the Guangdong–Hong Kong–Macao Greater Bay Area based on a DEA model. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 225–228. Coconut Creek (Florida), ISSN 0749-0208.This paper aims to study the marine economic efficiency based on a data envelopment analysis (DEA) model. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) was taken as the research object, and an input-output index system was established. The research results show that the GBA is developing rapidly, and the spatial layout of the marine economy continues to optimize. In the established input-output index system, the input indicators include the three aspects of marine resources, human resources, and scientific and technological inputs, while the output indicators include marine economic output and environmental output. The marine economic efficiency of the GBA was not high, and the average efficiency values of all regions were less than 1; the average value of Guangdong's marine economic efficiency was the highest, and that of Hong Kong's was the lowest, indicating that they are in an inefficient state. Finally, countermeasures and suggestions are put forward for improving the marine economic investment and enhancing the efficiency of marine economic development. The research findings provide useful reference for the sustainable development of the marine economy in the GBA and throughout the country.

China's energy consumption and green economy efficiency: an empirical research based on the threshold effect.

Using the panel data of China's provinces from 2005 to 2016, the paper adopts the ultra-efficiency model to measure the green economy efficiency of each province. Then, the paper used the panel threshold model to study the impact of science and technological input on the green economy efficiency with the energy consumption intensity as a threshold variable. The results show that the green economy efficiency in China's provinces is low and is in a downward trend. When the energy consumption intensity is the threshold variable, the single-threshold effect is significant. When the energy consumption intensity is lower than the threshold value, the impact of science and technological input on green economic efficiency is not significant, and the energy consumption intensity has a significant impact on green economic efficiency with science and technological input and energy consumption intensity as the core explanatory variables and with energy consumption intensity as the threshold variable. When the energy consumption intensity crosses the threshold value, the impact of science and technological input and energy consumption intensity on green economic efficiency becomes significant. According to the above empirical results, this paper proposes corresponding countermeasures and suggestions.