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Factors Affecting Customer Satisfaction

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Factos Affecting Customer Satisfaction Abstract Uber application allows commuters to place their services and to access their preferred services at a tap on their mobile phones. With quality measures, through interaction with customers in the social media, the application is gaining popularity despite concerns that some consumers have raised. Three models are proposed for significance of cost efficiency, use of credit and debit cards for payment, and value for social interactions in social media as factors to the growing popularity of the app. Using questionnaires to collect data on respondents’ factors to usage of the app, critical experiments are implemented, subjecting respondents to different environments at different times. Introduction and Method Uber application is a contemporary technology than aids transportation by allowing access to commuter service providers through mobile phones. Using an iPad and just a few taps on the screen of a mobile device, one is able to order for services, specify service preferences, and save money (Rosenzweig and Jones, 2014). The technology’s management ensures quality for its products though interaction with clients in social media. It avoids using drivers who attract negative feedback from customers (Williams, 2014). Even though the technology based service provider has been facing controversies with its users (Hildebrandt, 2014), its expansion continues (Green, 2014). Utility could therefore be a factor the growth of the technological application with factors such as innovation and cost (Rahman, 2014. McDam and William, 2013) as possible mediator factors to the growth. This study investigates the role of cost effectiveness, use of credit card and debit card for payment, and value for social media in facilitating growth of the uber app. Observation Uber is a new app that has become popular among many students. The observation is significant because of its economic impacts on the service provider and the economic and management scope of revenue and profit maximization. It also helps in understanding trend in growth of the application for monitoring success and for understanding its stage in product lifecycle, a factor that can inform the technology’s management towards innovation and product improvements. The observation is also important for informing consumers, who have not been using the application, on benefits that they could enjoy. Model one: People choose living at less cost One of the implications of this model is that people save on resources that they can use on other products or services. Another implication is that people prioritize their needs based on cost and benefit analysis.Model two: People prefer to use credit cards or debit cards than cash An implication for this model is that people enjoy the safety of their money. The other implication is that people enjoy the portability of a device on which they carry their money. Model three: People tend to make more friends Under this model, people expand their social networks. Additionally, people improve their social skills. Critical ExperimentsWith the use of umber application, that has cost, technology, and social implications, the following three models were proposed for empirical investigations based on the question of what drives people into using the application. People choose living at less costPeople prefer to use credit cards or debit cards than cashPeople tend to make more friendsCritical Experiment 1: Existence of Competitors that use Similar Technologies but with lower Service Cost. Description of the experiment A possible variable to the models is existence of competing companies that use android applications as uber app, but that offer cheaper charges. The critical experiment will investigate people’s rationale for using uber application with focus on cost, payment mode, and social interactions. Random sampling will be used to sample commuters from a city. Commuting with a frequency of at least four times per week will be the inclusion criterion while previous experience with uber application will be an exclusion criterion. This is because previous experience with the application is likely to induce bias towards it. Participants will then be asked on their attitudes towards using or commencing use of the application and factors to their choice and their possible knowledge of alternative products to the app. A structured questionnaire will then be offered to the participants seeking effects of cost, mode of payment, and social networks on the decisions and analysis will focus on responses of those who will be interested in using the uber application.Variables Cost, mode of payment, and social networks are the independent variables while use of the uber application is the dependent variable. Variable operationalizationUse of Uber app will be the dependent variable and will be measured directly from participants’ opinions and nominal scale will be used with yes and no as responses. Yes will define willingness to use uber application while no will define unwillingness. Cost, mode of payment and social networks will be the independent variable and will be bases for the decision on willingness to use the application. Cost will be measures on an ordinal scale, with average commuter cost as the baseline for classifying cheap and expensive costs. Mode of payment will be measured on a nominal scale with use of cash or either credit or debit cards as options. Value for social network as complementary accessible applications to the uber app will be measured on a nominal scale with yes and no as responses. Critical Experiment 2: Insecurity of Electronic Payments due to Cyber Crimes Description of the experiment The second critical experiment considers an environment in which electronic money transfer is insecure. Cyber crimes and internal breach that leads to access of users’ private information that can then be used to access their bank accounts for unauthorized funds transfers explain the situation. Random sample of commuters will be used in the study subject to condition that participants must have not experienced loss due to fraud from their use of credit or debit cards. Data on participants’ willingness to use the uber application will be collected using a questionnaire, and their possible knowledge of fraud involving credit and debit cards noted. VariablesWillingness to use the uber app will be the dependent variable while involved cost, payment mode, and value of social networks will be the independent variables. Variable operationalization Same variables are replicated in the critical experiment and operationalization remains the same.{ Use of Uber app will be the dependent variable and will be measured directly from participants’ opinions and nominal scale will be used with yes and no as responses. Yes will define willingness to use uber application while no will define unwillingness. Cost, mode of payment and social networks will be the independent variable and will be bases for the decision on willingness to use the application. Cost will be measures on an ordinal scale, with average commuter cost as the baseline for classifying cheap and expensive costs. Mode of payment will be measured on a nominal scale with use of cash or either credit or debit cards as options. Value for social network as complementary accessible applications to the uber app will be measured on a nominal scale with yes and no as responses.}Critical experiment 3: Conservative Society in which Physical Interactions are Valued Description of the experiment Other technology applications, such as social media, could be a factor to users attitude towards uber and critical experiment 3 assumes that the application is independent from other mobile phone applications. A survey design with a stratified random sampling approach is proposed for the study. Three strata that consist of the elderly (older than 75 years of age and presumed to be foreigners to technology), adults of between 50 and 60 year (considered digital immigrants), and youths and young adults (between 17 and 40 years) considered digital natives, will form the sample. Data will then be collected, using a questionnaire, on willingness to use the application. VariablesWillingness to use uber app will be the dependent variable and cost, payment mode, and value of technology-based social networks will be the independent variables. Variable operationalization Variable operationalization for the previous experiments will be retained. { Use of Uber app will be the dependent variable and will be measured directly from participants’ opinions and nominal scale will be used with yes and no as responses. Yes will define willingness to use uber application while no will define unwillingness. Cost, mode of payment and social networks will be the independent variable and will be bases for the decision on willingness to use the application. Cost will be measures on an ordinal scale, with average commuter cost as the baseline for classifying cheap and expensive costs. Mode of payment will be measured on a nominal scale with use of cash or either credit or debit cards as options. Value for social network as complementary accessible applications to the uber app will be measured on a nominal scale with yes and no as responses.}(Lave amp. March 58- 60)Findings and ResultsThe first model for the study proposes that people chose to live at low costs and this suggest that cost effectiveness drives the use of uber app. Higher frequency of responses that identify cost effectiveness as factors to use or willingness to use the app will support the model. Low frequency of responses that identify cost effectiveness as a factor to use or willingness to use the app will however lead to rejection of the hypothesis. If the number of those who identify cost effectiveness as a factor equals the number of those who do not identify cost effectiveness then focus shall be shifted to the other models. Model 2 proposes that the use of credit cards or debit cards, as opposed to cash, is the driving factor to use of the app. Higher frequency of response in support of use of the cards for payments, than against the use, as their reasons for using the app will approve the model. The converse will however inform rejection of the model and shifts focus to model 1 and model 3. The third model suggests that value of social media is the factor to people’s use of the technology that is embedded in devices that also access social media. The model will be accepted if for significance of social media as a factor to usage, higher percentage of users report significance than those who do not. Is higher percentage of respondents report non-significance then the model will be rejected and focus shifted to models one and two. ReferencesGreen, A. (2014). Uber’s here: Popular and controversial ride-share app launches in Chattanooga (With video). Times Free Press. Retrieved from: http://www.timesfreepress.com/news/2014/nov/14/ubers-here-Popular-and-controversial-ride-share-ap/. Hildebrandt, A. (2014). Uber takes heat for customer privacy settings. CBC News. Retrieved from: http://www.cbc.ca/news/technology/uber-takes-heat-for-customer-privacy-settings-1.2852907. Lave, Charles, amp. March, James. (1993). An introduction to models in the social sciences. New York, NY: University Press of America. McDam, P. and William, A. (2013). Technology, utilization, and inflation: What drives the new Keynesian Phillips Curve? Journal of Money, Credit amp. Banking, 45(8), 1548-1579. Rahman, H. (2014). Factos affecting customer satisfaction in mobile telecommunication industry in Bangladesh. Business, Management amp. Education, 12(1), 74-93.Rosenzweig, G. and Jones, G. (2014). My iPad for seniors. London, UK: Que Publishing. Williams, C. (2014). MGMT 7. Mason, OH: Cengage Learning.