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日期:2019-05-29 11:11

Analysis of Survey Data

Assignment #4

Download the data from the following link.

https://www.dropbox.com/sh/xos6aza7a0lr01f/AADSwvBxiATaPNlJRb5ULB7ea?dl=0

NOTE: Use all available resources to solve the problems. Search for the concepts in the paragraph below

with which you are not familiar (e.g., flow, addiction). You can find a solution to most of the coding

problems from the Internet. Google it, if you are stuck in the middle.

As more and more firms are using social media to provide information on their products or services and to

communicate with their customers, the role of social media is increasingly critical for the success of

business. However, with the proliferation of social media, many users are complaining of fatigue in their

daily usage of the service. The negative potential of fatigue provides a new challenge for social media

service providers and firms that try to capitalize on the service. In this project, the researchers propose a

new concept of social media fatigue and develop measures for the construct. Based on related nonscholarly

articles and literature, in-depth interviews, and group discussions, five dimensions of social media

fatigue—fatigue from social or relational obligation (SOR) (e.g., I feel tired because I am obliged to write

comments on friends’ social media postings), self-appearance (SPR) (e.g., I feel tired because I need to post

touched-up photos), quality of information (IQLR) (e.g., I feel tired because of the fragmented or poorly

organized information in social media), quantity of information (IQNR) (e.g., I feel tired because of so

many postings by my friends), and undesirable consequences (UER) (e.g., I feel tired due to contact

requests from individuals I am not interested in)—are identified as a preliminary result. Confirmatory

factor analysis is conducted to confirm the second-order five dimensional measurement model for the

social media fatigue. A structural equation model is developed to verify the role of the newly proposed

construct in explaining potential outcome variables such as “the intention to use the social media (FUTU)”

and “the intention to use a new social media service (OTHU)”. Potential control variables such as the flow

in using the social media (FLOW), the addiction in using the social media (ADD), and the privacy

concerns (PRI) are also measured with reflective indicators.

Q1. Load the data to your R system. How many constructs and manifest variables are in the data?

Q2. Conduct a confirmatory factor analysis to confirm the second-order five dimensional measurement

model for SM fatigue. Compare the model with a one-factor measurement model.

Q3. Develop a structural equation model. Make sure to include all control variables available. Draw a graph

to show your model with ovals and arrows.

Q4. Empirically validate your structural equation model. Is the result consistent with your conjecture?

Note for optional task: There is a variable measuring the present usage level of social media, named PREU.

Given that SM fatigue and PREU should have a negative association, you may use the variable for further

verification of the measurement model for SM fatigue (by confirming the negative association).


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