Analysis of Factors Influencing Farmer and Herdsman's Operating Behavior in Crop Production--A Case Study of the Typical Tibetan Counties(Cities)

We select 204 panel data samples from fixed observation spots in China's rural areas(Nagqu County,Duilongdeqing County and Xigaze City in Tibet),and conduct systematic analysis of factors influencing farmer and herdsman's operating behavior in crop production,using regression estimation method of the linear model,mixed OLS model and the random effects model.The research shows that "the number of migrant workers","the amount of household labor forces","original value of fixed assets for production purpose at the end of year","whether having agricultural machinery or not" and other household endowment factors,have a positive impact on total planting area of households,and theoretically,the endowment effect of internal factors predicted is valid;the product of "average food price" and "whether selling or not" has conspicuous impact,and the empirical results confirm that in external factors,the substitution effect of price is greater than the income effect.

Behavior recognition and fuel consumption prediction of tractor sowing operations using smartphone

In order to qualitatively recognize the behaviors and investigate the relationship between fuel consumption and machinery driving modes of the tractor in a low-cost approach,this study proposed a method for behavior recognition and fuel consumption prediction of tractor sowing operations using a smartphone.First,three driving modes were developed for maize sowing scenarios:manual driving assisted driving and unmanned driving.While sowing,smartphone software and CAN(Controller Area Network)storage devices collected both positional data and engine operating conditions.Second,the tractor trajectory points were divided into kinematic sequences,with six driving cycle indicators built in each series based on the time window.Based on the semantic information of the kinematic sequences,the three operations of sowing,seeds filling,and turning round were well recognized.Last,a model for maize sowing fuel consumption forecast was advanced using the principal component analyses and random forest algorithm,regarding three factors:driving cycles,operating behaviors,and driving patterns.When compared to the traditional K-means algorithm,the results demonstrated that the harmonic mean of the precision and recall(F1 score)of sowing behavior recognition,seeds filling behavior recognition,and turning behavior recognition were enhanced by 2.06%,8.99%,and 21.79%,respectively.In terms of the impacts of driving modes and operating behaviors on fuel consumption,assisted driving mode had the lowest fuel usage for both sowing and turning behavior.Therefore,assisted driving is the most fuel-efficient mode for maize sowing.Combining the three driving modes,the relative error of the fuel consumption prediction model was 0.11 L/h,with the manual driving mode having the lowest relative error at 0.09 L/h.This research method lays the foundation for the optimization of tractor operation behavior,the selection of tractor driving mode,and the fine management of tractor fuel consumption.

Production quality and pricing strategy for substitutable products under comparison effects

Comparison effects have been studied extensively in many fields.In particular,existing operations management articles have discussed the impact of comparison effects on enterprises'production and pricing decisions.Research has also shown that consumers'purchasing decisions are primarily determined by three factors:product quality,selling price,and comparison effects.The current study introduces the concepts of social and temporal comparison effects to examine how comparison effects influence a monopolist's production quality and pricing strategy for substitutable products.Results reveal the following:(1)Setting different prices for even two types of substitutable products with negligible quality differences can divide customers into three groups under the influence of social comparison effects in a single-stage model.(2)The monopolist should avoid using a price discrimination strategy in which products with a short market life cycle have the same quality but different prices.(3)When the market life cycle of products is sufficiently long in the single-product market and the market with two substitutable products,the monopolist's optimal choice in the second stage is to keep production quality constant and increase the selling price.Consequently,the number of buyers does not decrease because of temporal comparison effects.Therefore,the firm increases its revenue.(4)For the market with two substitutable products with quality differences,one approximate optimal strategy for the enterprise in the second stage is to keep the selling price constant with the assumption that product quality cannot be adjusted after the first period.At this point,the consumption situation in the market is the same as that in the first stage.Therefore,when no external constraints exist,the monopolist firm can obtain more benefits in the second stage than in the first stage by exploiting the temporal comparison effects of consumers in the second stage.(5)When consumer identity information can be confirmed in the market,social comparison effects,similar to temporal comparison effects,could help the enterprise increase its price and profit while maintaining product quality.These social and temporal comparison effects constrain consumers.Thus,the number of people who continueto buyproducts does not decrease.

Price squeeze under fairness: the road to supply chain coordination with a powerful retailer

This research investigates the impacts of the manufacturer’s fairness concerns on the supply chain performance when the power retailer implements a price squeeze and market service investment together.Through game-theoretic modeling,we find that 1)in the absence of fairness,although the manufacturer may be worse off due to possessing imperfect information on the price squeeze rate,the channel may be coordinated through an ex-ante negotiation between the two parties.2)When the manufacturer has fairness concerns for price squeeze,both channel performance and brand goodwill are made worse by disadvantageous inequality and improved by advantageous inequality versus the case of no fairness concerns.Furthermore,channel members’ex-ante negotiations regarding a profit reallocation scheme under certain conditions may achieve the following three objectives:generating a channel profit of the coordination level,promoting brand goodwill to the level of the integrated channel,and creating an equitable channel relationship.

An action-based Markov chain modeling approach for predicting the window operating behavior in office spaces

Reliable energy and performance prediction for building design and planning is important for newly-designed or retrofitted buildings.Window operating behavior has an important influence on the ventilation and energy consumption of these buildings under different realistic scenarios.Therefore,quantitatively describing this behavior and constructing a prediction model are important.In this work,an action-based Markov chain modeling approach for predicting window operating behavior in office spaces was proposed.Two summer measurement data(2016 and 2018)were used to verify the accuracy and validity of the modeling approach.The opening rate,outdoor temperature,time distribution,and on-off curve were proposed as four inspection standards.This study also compared the prediction performance between the action-based Markov chain modeling approach with the state-based Markov chain modeling approach,which is the most popular modeling approach to model occupant window operating behavior.This study proved that the yearly variation of occupants’behavior performed a form of action that remained unchanged during a certain period.Meanwhile,the results also proved that the action-based Markov chain modeling approach can reflect the actual window operating behavior accurately within an open-plan office,which is a beneficial supplement for energy-consumption simulation software in a window-state prediction module.The state-based Markov chain modeling approach showed better stability and accuracy in terms of the opening rate,whereas the action-based Markov chain modeling approach showed good consistency with the measurement data in the on-off curves and in situations with little data.For the on-off curves,the accuracy of action-based modeling approach in the prediction of window open-state is 20%higher.

Comparative analysis of window operating behavior in three different open-plan offices in Nanjing

Research on the window operating behavior of offices is of great significance for reducing building energy con-sumption and improving indoor comfort.The open-plan office is a common office form that involves a large number of people and a complex staffcomposition.The window operating behaviors in open-plan offices are also random and various.This study took three open-plan offices with different situations(area,office type,staffcomposition,etc.)as an example,which provides a new perspective on how people behave differently when opening or closing windows.The window operating behaviors in two typical seasons(summer and transition seasons)were recorded and analyzed.The occupants’schedules and influencing factors of window operating behavior were investigated by questionnaire surveys.In addition,the indoor environmental parameters,occu-pancy situation,and on-offstatuses of windows and air conditioning were acquired through field measurements.Furthermore,the differences in window operating behaviors in the three open-plan offices were compared from the perspectives of influencing factors,duration of the window on-offstatuses,and cause of window control ac-tions,among others.In addition,Spearman Correlation Coefficient was used to analyze the ranks of the candidate motivations for window operating behaviors.The preliminary results show that influenced by the personnel com-position,type of air conditioner and adjustable degree of windows,the window operating behaviors of different office buildings have larger discrepancies than that in the same building.However,there were some common characteristics in the window regulation behaviors of the three open-plan offices:they were generally influenced by the coupling of environmental factors,schedule factors,and equipment factors.This study reveals that when expand the research object from a single building to multiple buildings,more difficulties and challenges would be involved into behavior research.