Eye Wear Industry Case Study

5.3 Implications of the Study

5.3.1 Managerial Implications

From the perspectives of theoretical contributions, this research provide useful information to eye wear industry and also useful for the future researchers especially for those who are doing research on the m-commerce and customer satisfaction. On the other hand, employers are able to know how to avoid unnecessary problems and satisfy their customers. Other than that, the increased customer satisfaction can increase sales and build customers loyalty as well. Thus, the organization should emphasize on these practices to maximize customer satisfaction. It can help to indicator of how likely a customer will make a purchase in the future and reduce customer churn.

Employees often provide customers with their initial impressions of the products the company offers. Though the workers who deal directly with customers may not be the people who select or develop products, they are the ones who give customers information about them, selling the products and proving to the customers that the products in question are ones they need. To ensure that workers can represent the products they sell effectively, managers must educate their workers on these products and ensure that they possess the knowledge necessary to tell workers about them in an informed and engaging manner.

Furthermore, survey helps organization to determine customer perception and behaviour and support the organizations to change the idea and set their target goals in order to enhancing the customer satisfaction.

Moreover, in this research study, we proposed the independent variable will have connections to the customer satisfaction. Therefore, management should take the each of the variables are important and take them into consideration in order to meet the expectation of customer needs and wants and gain customer satisfaction as well.

5.4 Limitation of Study

5.4.1 Size and Scope of Research

This research, however, has some limitations. First, despite the fact that the age range of respondents covered the main portion of the whole set of m-commerce users, the sample size was too small to obtain a more accurate classification or prediction rate. Some data mining techniques such as Bagging can be employed to address this limitation, but increasing the number of respondents is a fundamental solution to this problem.

1. Falsification of Respondents and Difficult in Finding

The reliability of survey data may depend on the factors of respondents. Some of the respondent is  respondents may not feel encouraged to provide accurate, honest answers due to some sensitive question such as age, and purchasing power. Next, respondents may not be fully aware of their reasons for any given answer because of lack of memory on the subject, or even boredom. Survey question answer options could lead to unclear data because certain answer options may be interpreted differently by respondents. For example, the answer option “somewhat agree” may represent different things to different subjects, and have its own meaning to each individual respondent.  ‘Yes’ or ‘no’ answer options can also be problematic. Respondents may answer “no” if the option “only once” is not available.

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