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The Development of Trust and Trustworthiness between Buyers and Sellers on Mobile App Market. Mengxue Zheng mzheng11@illinois.edu. Wei Yang weiyang3@illinois.edu. CS598-KGK: Social Spaces on the Internet Fall 2013 University of Illinois at Urbana Champaign. Motivation.
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The Development of Trustand Trustworthiness between Buyers and Sellers on Mobile App Market Mengxue Zheng mzheng11@illinois.edu Wei Yang weiyang3@illinois.edu CS598-KGK: Social Spaces on the Internet Fall 2013 University of Illinois at Urbana Champaign
Motivation • Trust is important to the online store in general. • Low degrees of online consumer trust prevent consumers from purchasing and even from just window-shopping; (Gefen,2000) • The less verifiable and less controllable business environment of the Web. (Reichheld & Schefter, 2000) • The buyers’ and sellers’ behaviors on mobile app market could be different from those on traditional online store. • The low cost for sellers to cheat. • The app market doesn't set high standard for buyers like traditional shopping website such as eBay or Amazon. Lack of filtering/punishing mechanism for app market. • The cost for buyers to buy is different • Buyers pay lower price to get the product. A large portion of apps on market are free. • Buyers could be more vulnerable to the apps for security perspective. Malicious app could endanger the security and privacy of buyers.
Research Objectives • Objective1: Study the main factors that buyers form the trust • Objective2: Study the approaches that sellers take to gain customer's trust.
Definitions • Trust is the product of a set of trustworthiness beliefs. (Jarvenpaa et al., 1998; Mayer & Davis, 1999) • The beliefs include: • Integrity • The belief that the trusted party adheres to accepted rules of conduct, such as honesty and keeping promises. • Ability • The beliefs about the skills and competence of the trusted party. • Benevolence • The belief that the trusted party, aside from wanting to make a legitimate profit, wants to do good to the customer
Definitions in the case of mobile app market • Integrity • The belief that the purchased apps’ functionalities will be consistent with the functionalities in the descriptions. • Ability • The belief that the developers will write apps with fine quality or performance. • Benevolence • The belief that the purchased apps are not malwares or potentially unwanted applications (PUAs, e.g., Spyware,Trackware, Adware).
Research Questions • RQ1: For each category of apps, what are the weight of integrity, ability, and benevolence for user to form the trust? Which are the buyers main focus? • RQ1.1 If the main focus is ability, or benevolence, which aspects of ability or benevolence that users will most concern? • RQ2: For each category of apps, what are the approaches that sellers have taken to gain trust from the users?
Metrics • RQ1: The percentages of comments related to integrity, ability, and benevolence respectively in all buyers’ comments. • RQ1.1 If the main focus is ability, or benevolence, the percentages of comments for each aspects of ability or benevolence among all comments related to ability or benevolence ? • RQ2: The actions that sellers have taken to make the buyers change their ratings.
Methodologies • Data Extraction • Comments from top apps of both free and nonfree in each category • We pick top 6 apps from both free and nonfree list for each category. • In total of 300 Apps from 25 categories • Comments from all hybrid mobile apps using phonegap • To compensate the potential bias in popular apps. • Crawling 881 AppID from phonegap website, 581 of them have user comments. • Data Preprocessing • Data Analysis
Methodologies • Data Extraction • Data Preprocessing • Reduce words amount using a list of stop words (i.e., delete words without any meaning, e.g., a, an, we). • http://www.ranks.nl/resources/stopwords.html • Data Analysis
Methodologies • Data Extraction • Data Preprocessing • Data Analysis • Count the frequency for each word from the comments. We get a list of words and their frequency after that. • Identify the words that representing integrity, ability, and benevolence respectively, and manually verify the accuracy, then calculate their percentages. • Searching the updated comments after sellers’ changes. Find out their concerns and incentives to update the comments.
Result • General Findings • A large portion of positive comments do not reflect any users’ preferences. (Simple Comments) • Generally User focus more on ability. But the weights of each beliefs vary across different categories. • In each aspects of ability, compatibility, usability and stability are common user concerns. • The benevolence belief have more weights in GAME category.
