Research On The Incentive Mechanism Of Employee Value Creation Based On ESM

In recent years,enterprise social media(ESM)have been widely used in enterprises,because this tool could create important value for the company's organizational knowledge accumulation,R&D and operation management.This value comes not only from the knowledge created by employees on ESM,but also from the social networks that employees build through ESM.Continued use of ESM is a prerequisite for achieving and gaining employee value creation.To attract and encourage employees to continue to use ESM,companies often introduce incentives to drive employees to participate in ESM communication and interaction.Because the impact of incentives on employees' social media behavior is a complex process,the effects of incentives are still controversial in previous studies.Many studies believe that companies always expect employees to complete the tasks set by the company to obtain rewards,so the incentive mechanism can increase employees' enthusiasm for participating in ESM.However,some studies have suggested that improper incentives may stimulate external motivation and weaken the impact of internal motivation,and the short-term incentives that work in the short term may cause negative effects if the incentive mechanism fails in the long run.Summing up the previous research,the incentive mechanism of incentive policies on employee behavior on ESM is still unclear,and few studies have explored the continuous use behavior after the implementation of incentive policies from the perspective of a long-term time process.To clarify the incentive mechanism of incentives to employee value creation on ESM,this study focuses on the incentive mechanism to employee value creation on ESM from two dimensions:one is the value category dimension,which focuses on the employee value creation in ESM,and this employee value creation process can be divided into two categories:employee knowledge creation and social network construction;the second is the time process dimension,that is,not only focuses on short-term incentives for employees,but also considers the renewal impact of long-term incentives on employee value creation.Therefore,this research examines the corporate blog and its incentives by utilizing econometrics,static and dynamic social network analysis,machine learning modeling and interpretation algorithms and other research methods,testing the effects and incentive mechanism of incentives for employee knowledge creation and social network construction value creation from short-term to long-term dimension,and predict the failure of the incentive mechanism based on understanding the overall mechanism.The main conclusions of this study are as follows:First,in the short term,incentives have a positive driving effect on employee knowledge creation based on ESM,and mechanism of the above driving effect is the theoretical relationship between external motivation and employee knowledge creation which intermediated by intrinsic motivation,that is,"extrinsic motivation-internal motivation-employee knowledge creation" process.This research first builds a research framework based on the stimuli-organism-response theory framework,self-determination theory,and social tie theory;then uses machine learning algorithms for text analysis to classify high-quality work-related knowledge,low-quality work-related knowledge,high-quality non-work-related knowledge and low-quality non-work-related knowledge based on subject and quality;then through the difference-in-difference method,coarsened exact matching,intermediary effect test,and several robustness check techniques,examine the theoretical relationship between external incentives inspired by the incentive policies and different types of employee knowledge by introducing self-efficacy and altruism in intrinsic motivation to empirically test the intermediary effect of intrinsic motivation in the aforementioned theoretical relationship between external motivation and employee knowledge creation.Findings have shown that:(1)incentive policies have a significant positive impact on low-quality work-related blog posts;(2)incentive policies have a significant negative impact on high-quality and low-quality non-work-related blog posts,thus more energy will be used to create work-related knowledge and also bring value to enterprise knowledge management;(3)the internal motivation of self-efficacy and altruism completely intermediate the relationship between external motivation inspired by incentives and low-quality work-related blog posts;(4)the internal motivation of self-efficacy and altruism partially intermediate the relationship between external motivation inspired by incentives and high-quality and low-quality non-work-related blog posts.Secondly,in the short term,incentives have a positive driving effect on employees' social network construction based on ESM,but the construction of social networks under the role of incentives is limited by the clear hierarchical structure in the enterprise,which more reflects the hierarchy organization fragmentation,not communication across departments and levels.In this study,the static social network analysis method is first used to analyze the structural characteristics of the network,such as the number of nodes,the number of consecutive edges,the degree of nodes,the average path length,the network diameter,and the clustering coefficient,etc.of the enterprise social network based on ESM,and compare the changes in the network structure before and after the implementation of the incentive policies from a relatively macro perspective to understand the incentive effect of the incentive policies on employee social network construction value creation.Based on the network closure theory,this study separately considers the reciprocal effect and the transfer effect from the network structure effect,and also the similarity effect,ago effect,and popular effect from the characteristics effect,and uses a dynamic stochastic actor-oriented model based on the time-series network snapshot,describing underlline evolution characteristics of social network structure,thus analyze the incentive mechanism of incentive policies for social network construction from a more individual perspective.The research conclusions demonstrate that:(1)after the implementation of the incentive policies,the number of nodes and connections in the social network has increased significantly,and the evolution of the social network has accelerated significantly,indicating that the incentive policies have a positive impact on encouraging employees to participate in ESM and engage in interactions;(2)the difference in average path length,network diameter and clustering coefficient of social networks before and after the incentive is relatively small,indicating that the interconnection between nodes in the network may not become closer due to the implementation of incentive policies;(3)the reciprocal effect in the network structure effect has a positive driving effect on the evolution of social networks,but the transfer effect and the triangle effect respectively have positive and negative effects,indicating that the evolution of social networks is hierarchical and not completely equal;(4)employee attributes such as gender,age,rank,education level,marital status,and contract status could be used to calculate similar effects,ago effects,and popular effects,and have been found different degrees of driving effect on the evolution of social networks,but generally show that employees are more limited to establish new connections with employees who they are familiar with,or among employees who are in the similar levels.Cross-level,cross-department,and diversified social network construction trends did not appear.Instead,they showed a "huddle" between similar groups and a"split" phenomenon between different groups.Third,in the long run,the incentives for employees to create value based on ESM will gradually fail over time.The historical abnormal blog post publishing behavior can be used as a leading indicator for predicting the degree of failure of incentive mechanisms in the future,and the machine learning prediction model which based on extreme gradient boosting decision tree algorithm has a good performance on predicting the abnormal behavior of ESM users.This research first defines the abnormal behavior of ESM users in the research context after the incentive mechanism fails,i.e.publish abnormal blog posts in corporate blogs;then this study uses extreme gradient boosting decision tree model,deep neural network model and support vector machine to finish predicting abnormal blog posts,and compares the accuracy of three kinds of models,thus abstaining the optimal prediction model for identifying abnormal blog posts.Finally,the SHAP value decomposition and interpretation method are used to analyze the prediction results and find the historical abnormal blog post publishing behavior can be used as a leading indicator for predicting the failure degree of the future incentive mechanism,to facilitate decision-makers to identify and predict the failure phenomenon of the incentive mechanism more reasonably.The findings have shown that:(1)the frequency of abnormal behaviors rises significantly six months after the implementation of incentive policies,and continues to increase gradually over time.This observation shows that after the implementation of the incentive policies,it will gradually fail over time;(2)based on the extreme gradient boosting decision tree algorithm,the machine learning prediction model has a good prediction performance on the abnormal behavior of ESM users;(3)the number of abnormal blog posts in the past six months and the past three months of before the current blog post,and the normal blog posts in the past six months and the past three months are the four most important features,so that can be used to identify and predict the abnormal behavior of ESM users in the future.Through in-depth research on the incentive mechanism of employee value creation based on ESM,the innovation of this research is reflected in the following aspects:First,based on stimuli-organism-response theory framework,this research finds that the incentives can have an unequal effect on how incentives influence knowledge creation:incentives can significantly increase low-quality work-related knowledge creation,but significantly reduce non-work-related content generated on ESM.Based on the classic work-related and non-work-related content classification in previous studies,this research innovatively introduces the knowledge content classification of the quality dimension into content generated on ESM,and the empirical research reveals the driving role of incentive policies mainly reflected in the creation of low-quality work-related knowledge,and reduce the creation of high-quality and low-quality non-work-related knowledge.During this process,the positive emotions brought by the results of knowledge creation stimulated the intrinsic motivation of self-efficacy and altruism,which in turn motivated employees to create knowledge.Because the creation of work-related knowledge that requires highly autonomous and complex skills has to more dependent on the level of intrinsic motivation than non-work-related knowledge,intrinsic motivation completely mediates the creation of extrinsic motivation and low-quality work-related knowledge,and partially mediates extrinsic motivation and non-work-related knowledge with high and low quality.Second,according to social analysis theory and network closure theory,this study demonstrates the unequal effect of employee social network evolution:incentives encourage employees to participate in ESM,but the relationships between nodes cannot become closer after adopting incentives.This research innovatively adopts a research paradigm that combines static social network structural characteristics analysis with dynamic social network evolution modeling.This research first calculates the structural indicators such as the number of nodes,the number of connected edges,the degree of nodes,the average path length,the network diameter,and the clustering coefficient in the social network of the enterprise,and have found that the number of interacting nodes and connected edges in the social network has increased significantly.Based on the stochastic actor-oriented model,this study then estimates the parameters of employees'decision-making behavior and direction of establishing social relationships,and finds that the role of incentives has a positive impact on the evolution of social networks,but it shows more hierarchical trends when establishing new connection relationships.These findings reveal the real impact of incentive policies in the construction of social networks,and helps companies to form reasonable expectations of the effects and make timely interventions when designing incentive policies.Third,this research applies econometrics,machine learning modeling and interpretation algorithms,and finds that the impact of incentives will gradually fail over time,and the historical abnormal blog post publishing behavior can be used as a leading indicator for predicting the degree of failure of incentive mechanisms in the future.This study innovatively studies the impact of incentive policies on driving employee value creation in the long run.The abnormal behavior of employees who post abnormal blog posts is used as a sign of the failure of the incentive mechanism.The study found that the failure of incentive mechanism occurs the after the incentive policies have been adopted six months,but machine learning models can be used to identify and predict the failure of the incentive mechanism of the incentive policies,and the historical abnormal blog post publishing behavior can be used as a leading indicator for the prediction and recognition of the failure degree of the incentive mechanism in the future.The above conclusions can help companies consider introducing machine learning prediction modules in ESM,thereby helping companies more efficiently incent employee value creation through the use of ESM.