Simulation Research On Organizational Behavior And Operation Of Crowdsourced Logistics Enterprises And Employees Under Smart Environment

In recent years,with the steady development of social economy in our country,and with the rise of the concept of "Internet +",sharing of economy and big data,as well as the increasingly smart mobile and intelligent equipment tools,impacting on people's living and consumption habits,the leap-forward development of express delivery industry is already Become an irresistible trend.With the rapid development of e-commerce,o2 o industry and the increasing demand of diversified users,the orders of the last 3 kilometers of logistics are increasing rapidly.The traditional logistics is hard to deal with such a huge volume of business.However,self-built logistics Faced with the problem of high costs.In the era of intelligent logistics,the role of optimal allocation of market resources has been magnified.The business operation mode of enterprises has also been transformed from vertical integration to partial outsourcing at the beginning.Among them,crowdsourcing logistics mode has had an important influence on improving the express delivery market.Therefore,crowdsourcing logistics Unwittingly become the best way to solve the city distribution.Crowdsourcing logistics entry threshold is very low,the average person as long as there is a mobile phone can participate in,the time is also very free,so crowdsourcing logistics model also bear a huge risk,facing many instabilities,but these illnesses have been capital infused passion Cover up.For the crowdsourcing logistics enterprises,for example,whether the delivery staff will directly influence the normal operation of the company will make the non-linear change of their psychology and behavior more obvious to those who are members of the public in an intelligent environment,Has aroused widespread concern,while the current on crowdsourcing logistics.Catastrophe theory,opinion dynamics and computational experiments have been utilized in theis paper to study the behavior of service providers,customers and crowdsourced logistics company.Firstly,The instant online behavior of individual easily leads to polarization and reversal of collective behavior in the smart environment.To capture the underlying mechanism of this phenomenon,modeling method for catastrophe dynamics in collective opinion is designed.The virtual community of DaDa logistics company is taken as an example.The messages(i.e.,text data)sent online by couriers in the virtual community are the data for modeling.Thus the cusp catastrophe model,i.e.,pure mathematical model,is combined with qualitative simulation method and converted into the semi-quantitative model.Fuzzy set joins the fitting of model's parameters due to the vague and incomplete text data.The modeling method is verified and validated by through a case of DaDa couriers talking about the topic on work pressure and condition,in which the catastrophe model is embedded into the relative agreement model(i.e.,RA model in the field of opinion dynamics)for validation.Meanwhile,it provides a new validation approach for the field of social computing,and shows the catastrophe-embedded RA model is more suitable for explaining the dynamics of collective behavior in the smart environment than the original RA model.An optimization framework of applying the catastrophe-embedded RA model to identify the structure of DaDa virtual community is design to explore fractions of sensitive,neutral and indifferent individuals of DaDa courier group.Secondly,Crowdsourced logistics is one of the business models for the issue "The Last One Kilometer" in China.However,the organization of crowdsourced logistics remains unstable in the smart-device environment(i.e.,mobile phones in communication,digital platforms in employee communication).With a small change in environmental factors—e.g.,the delivery charge minimally decreased by managers—the carriers' opinion may briefly show polarization or reversal and lead to employee turnover.To explore the nature of opinion dynamics and employee turnover,we introduce a new model that embeds catastrophe theory in the relative agreement(RA)model of opinion dynamics.Experimental results demonstrate the suitability of the proposed model in capturing the evolutionary trajectory of employee group opinion.We analyze the reasons for the bifurcation behavior of employees.We draw conclusions on the relationship between delivery price and employee turnover.The catastrophe-embedded RA model extends the application of the RA model in the field of opinion dynamics to the smart environment.Thirdly,We propose a model to explore employee's turnover behavior in crowdsourced logistics through two kind of interaction.The first is employee and employee interaction,which is under internet environment,their network belongs to social network,we set it as a scale-free network;the second is employee and customer interaction,which is under IoT enviroment,that means the interaction between employee and customer is partial,dynamic,and based on their location,so we set is as location-based network.Through agent-based simulation experiments,we find that the employee and customer interaction leads the employee's turnover rate exhibits two-stage down trend which is different from the interaction under internet environment;in order to decrease the employee's turnover rate,choosing seeding targets based on their number of social ties is more promising than choosingthem randomly.Marketing managers can use our results to evaluate whether identifying and targeting social hubs is worth the cost and effort.Fourthly,With the increasingly wide use of sensor-embedded smartphones,we envision that there will be many crowdsourcers to acquire logistics service from a large population of service providers.They form a bilateral competition market,where crowdsourcers compete for the limited logistics service and service providers compete for the limited budget from crowdsourcers.Each crowdsourcers has to select an “optimal” budget that can attract enough service providers.Each service provider has to decide the crowdsourcers to join in,while a congested crowdsourcer may resulte in a low reward.In this paper,we present a game theoretic study of such a bilateral competition market.To be more practical,we consider the bounded rationality of service providers.We formulate the dynamics behavior of service providers as an evolutionary game,and take two key factors(crowdsourcer's analytics ablity and service providers' evaluation)under smart enviroment in our model,and then present a simulation model for the implementation of evolution process.Through this paper,we can understand the dynamic evolution of the crowd logistics market under smart environment and crowdsourcers can adjust their strategy to optimal their profit.Lastly,Nowadays crowdsourcing develops rapidly in our country.Even though many crowdsourced logistics enterprises spring up,a large part of the enterprises withdraws from the market due to capital chain rupture.This thesis in the perspective of crowdsourced logistics enterprise studies promotional methods' and stocking strategies' influence on internal index like cash flow and external index like loyalty,investor trust.Then it analyzes how those indexes affect enterprises' capital chain rupture and find the intrinsic mechanism of promotional methods and stocking strategy.In order to observe the dynamic effect of these factors and the interaction between users and enterprises,this research uses a multi-agent system and system dynamics to simulate internal and external indexes' influence on capital chain.Through simulation experiment,sensitivity analysis method and catastrophe theory are used to analyze the mechanism of capital chain rupture.The result is to provide some suggestions about ordering maker's psychological quality and price reduction strategy to protect crowdsourced logistics enterprise against capital chain rupture.