Evaluating E-Commerce Website of an Organization of Choice - Research Proposal Example

Evaluating E-Commerce Website of an Organization of Choice ID: Details: Module Module Module leader’s Deadline Word Count: Table Of contents Evaluating E-Commerce Website of an Organization of Choice………………..1 Table Of contents…………………………………………………………………2 Introduction……………………………………………………………………….3 Website Evaluation Criteria……………………………………………………….3 Website Design Metrics………….………………………………………………..5 Decision Method and Model……...……………………………………………….5 Website Design Metrics…………….……………………………………………..9 Conclusion…………………………………………………………………………9 Introduction Relative literature defines commerce as the mutual exchange of value such as goods and services on a large scale. The exchange may be between people, businesses or entities and is regulated by legal, political, socio-cultural, technological and economic factors. Commerce can be carried out on various scopes which are from local to international levels (Flavian, Gurrea and Orus, 2009). As a result of the increment in present years innovation and technological advancements has led to the invention and growth of e-commerce. E-commerce can be defined as the transfer of goods and services, data or funds through an electronic network (Tarafdar and Zhang 2008). E-commerce primarily uses the internet as the medium of transfer. The internet has provided this kind of network that is aimed at linking business users and businesses through the information system on a global basis. As a result of the growth of e-commerce, several e-commerce websites such as Volusion, Shopify and Wix (Barnes andVidgen, 2002). The primary goal of this academic research paper is to write a report using a supermarket as the chosen business organization of choice. Through e-commerce analysis and evaluation of effectiveness and efficiency, we can identify its alignment with strategic objectives. This paper further analyses the contribution of e-commerce to the entire business cycle as well as the importance of e-commerce concepts to an organization’s future development. Website Evaluation Criteria Since the e-commerce industry has relatively low-entry barrier costs, this has led to the present increase in e-shopping sites. Since the potential benefits of e-commerce are enormous, the relative risks are also similarly huge but rather hidden. Examples of these risks include unwarranted product quality, fraudulence in transaction payment and offering of after sales services (Petre, Minocha, and Roberts, 2006). Consumers look at these virtual online companies like a large maze of different functions and information integrated into various web appearances which could be deceiving at times (Smith, 2001). The evaluation of e-shopping sites such as supermarkets involves several factors and metrics that make it very challenging. A previously done literature by another scholar Kim et al. (2003), categorizes e-commerce website evaluation criteria into six categories (Ahn, Ryu and Han, 2007). These are business functionality, corporate credibility, content reliability, website attractiveness and systematic structure plus navigation. Recently other scholars have come up with two basic categories for evaluating e-commerce websites. Au Yeung and Law (2004) focused on usability, reliability and functionality in their study on the heuristic evaluation techniques to compute the efficiency of hotel websites in Hong Kong. Concerning the above they recommended the use of efficiency, reliability and functionality in evaluating e-commerce websites. Au Yeung and Law aimed at constructing a hybrid approach that combines the fuzzy analytic network process and FVIKOR for evaluating website quality. This research study shall integrate other disciplines in an effort to evaluate e-commerce websites. Through the process of identifying and ranking their main quality characteristics through a survey of various developers and the other users’ points of interaction within the system. The different strategic performance characteristics are organized based on the Fuzzy Model for software evaluation that has previously produced excellent results in various application domains. The Fuzzy model categorizes websites based on its quality characteristics. These characteristics can further be subdivided into subcategories (Nefti, Meziane and Kasirani, 2005). User friendliness is a quality characteristic that promotes the ease of the e-commerce site use during its operation, as well as maintenance. Conceptual user friendliness is related to the e-commerce website’s ability to meet and exceed its primary purpose since this was what it was designed to do. Additionally, the website’s reliability refers to its ability to be well understood and manipulated along its life cycle (Kong and Liu, 2005). Website Design Metrics From the above discussion, it is evident evaluating of e-commerce websites requires analytical consideration of the various web measurements in E-commerce. The different tools used in measuring web metrics are website performance and traffic (Lee and Kozar, 2006). The most significant web metrics for our study are design and usability. Design and usability by websites decide the levels of a website’s productivity and revenue generation. This attaches more significance to the design of informational websites. Among the design components that can be fine-tuned and refined include, information flow, navigation, and graphic and user experience. On the other hand, website performance can be measured through response time. Response time is referred to the difference between the period a request is issued and the feedback of the requested data (Palmer, 2002). During the course of processing, should the server process large amounts of data alongside a high number of requests. Feedbacks may take longer to be completed which would result in increased response time for clients. Since humans are naturally impatient and nervy, they tend to develop a poor experience from the website thus this makes a page’s interface very relevant in the evaluation of e-commerce (World best enterprises, 2004). Website traffic is also considered another important aspect in the evaluation of e-commerce websites. While analysing web traffic, the different factors to be considered are the number of unique visitors, the mean page hits, and the total amount of time spent by visitors. Other significant factors include user loyalty and all time page hits (Parasuraman, Zeithaml, andMalhotra, 2005). Decision Method and Model The different stages used in the evaluation through the use of the fuzzy model are as illustrated below. The primary stage entails establishment of the evaluation criteria alongside the items to be evaluated. From the two quality sub factors, eighty quality sub-factors for e-commerce were established and appraised. On the other hand, e-commerce users had 51 sub-factors which constituted the specialists’ sub-factors that contained five quality factors. The evaluators graded the sub-factors using grades which ranged from 0-4 for each sub-factor. These grades were then subjected to fuzzification which transformed the grades into triangular fuzzy numbers as shown in the table below (Van der Merwe andBekker, 2003). A triangular fuzzy number is represented as N (m, b, a). The values “a” and “b” respectively identify the inferior and superior limits of the base’s triangle. “M” represents the triangle’s height. In the second stage, the evaluator needs to obtain the profiles of the users and specialists managing the website. The relative experts and users’ profiles are obtained from the completion of the specialists’ and users’ identification questionnaires respectively. These questionnaires generate a weighting measure by each evaluator which finally influences the final result (Cao, Zhang andSeydel, 2005). The third stage involves attaching different levels of importance to the users and specialists identified in the first stage. The field research can provide opinions from thirty different users and specialists in the four major U.S cities. The different cities used in the study are Los Angeles, Chicago, and Las Vegas. The evaluators were required to evaluate each of the quality sub-factors surveyed with reference to its attached importance to the e-commerce website domain application. Since the study was on a supermarket kind of business, the questionnaire used amazon.com as a representative (Cao, Zhang andSeydel, 2005). The fourth stage involves subjection of fuzzy treatment of users, specialists and the data collected. In the process of evaluating user and specialists, the collected data was subjected to fuzzy treatment. This was through the use of a similar matrix considering that each specialist’s and user’s weight was obtained in the second stage as directed by the fuzzy model (Cao, Zhang andSeydel, 2005). The fifth and final stage entails aggregation of the website’s quality attributes in the different models of the hierarchical level. In this ultimate stage, the results got from the sub-factors are added to calculate the objective results. The final results obtained reveal the quality of the e-commerce websites. The table below displays the final set of the different quality attributes. The sub-factors have been arranged inside the factors with respect to decreasing order of importance as per the developers and users of e-commerce sites Albuquerque and Belchior, 2002). Interpretation of outcomes In the decision-making process, concerning the choice of the shopping sites, a consumer is faced with different alternatives. The research experiment above focused on only four shopping websites alongside their two core functions. The evaluation of the websites’ core functionality resulted in the multiple scheme indexes as seen above. These indexes can are used in guiding the specialists on where to improve as well as the users on the expected outcome levels of the different shopping sites (Kong and Liu, 2005). Conclusion This study found out that the different literature sources have different standards or techniques for evaluating websites albeit with significant all-round similarities. Through the use of Fuzzy’s framework of grading the various sub-factors on a multi-index basis, users can evaluate e-commerce sites. The outcome of the result indicates that the most significant factor considered by e-commerce users is security. This is linked to the increase in the use of electronic cash transfer and payment of e-commerce which has been lately subjected to fraud among other attacks (Ngai andWat, 2005). The integrity factor is rated the second with reference to the evaluation process. This implies that an e-commerce website has the responsibility of managing and controlling its database correctly and efficiently (Herrera-Viedma et. al, 2006). The decision model aids shoppers and other users to get a good view of the website quality sub-factors hence facilitating the choice of e-commerce website. Reference List Ahn, T., Ryu, S. and Han, I. (2007).The Impact of Web Quality and Playfulness on User Acceptance of Online Retailing. Information & Management, 44(3), 263-275. Albuquerque, A. B., andBelchior, A. D. (2002).E-commerce website quality evaluation. In Euro micro Conference, 2002.Proceedings. 28th (pp. 294-300). IEEE. Barnes, S. and Vidgen, R. 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