191 research outputs found

    THE INFLUENCE OF PRICE DISPERSION ON PURCHASE INTENTION IN CHINESE ONLINE C2C MARKET: A TRUST PERSPECTIVE

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    Chinese C2C market grows rapidly. However, it is plagued by serious trust fraud problems. The level of price dispersion in C2C platforms is relatively high. The mixed interaction between “lemons market” problem and high level of price dispersion makes it hard for buyers to identify trustworthy sellers with low price. We are interested in the generation of initial trust and purchase intention when the buyers search a product and receive a list of widely distributed prices, rather than a list of narrowly distributed prices. However, limited knowledge can be gained from previous studies regarding this issue. This study puts forward a theoretical model to explain how price dispersion interacts with other important factors in C2C purchase (e.g. initial trust, perceived risk, perceived value and purchase intention). Product type (high- touch/low-touch) is taken into consideration as well since the level of uncertainty faced by buyers is different. A proposal for experiment is described. This research-in-progress has the potential to lead to various theoretical and practical implications. For example, the results will enhance the literature on trust, help buyers do better purchase decision, assist sellers in designing pricing strategy, and be utilized by platforms to propose new mechanisms

    Review Manipulation: Literature Review, and Future Research Agenda

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    Background: The phenomenon of review manipulation and fake reviews has gained Information Systems (IS) scholars’ attention during recent years. Scholarly research in this domain has delved into the causes and consequences of review manipulation. However, we find that the findings are diverse, and the studies do not portray a systematic approach. This study synthesizes the findings from a multidisciplinary perspective and presents an integrated framework to understand the mechanism of review manipulation. Method: The study reviews 88 relevant articles on review manipulation spanning a decade and a half. We adopted an iterative coding approach to synthesizing the literature on concepts and categorized them independently into potential themes. Results: We present an integrated framework that shows the linkages between the different themes, namely, the prevalence of manipulation, impact of manipulation, conditions and choice for manipulation decision, characteristics of fake reviews, models for detecting spam reviews, and strategies to deal with manipulation. We also present the characteristics of review manipulation and cover both operational and conceptual issues associated with the research on this topic. Conclusions: Insights from the study will guide future research on review manipulation and fake reviews. The study presents a holistic view of the phenomenon of review manipulation. It informs various online platforms to address fake reviews towards building a healthy and sustainable environment

    SME-OPERATED CHOCOLATE EXPORT OPERATION TO THE CHINESE MARKET : Case “Fazer” chocolate

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    This thesis is focused on describing and analyzing SME (small and medium enterprise) operated export operation for Finnish famous chocolate brand “Fazer” to the Chinese market. It is based on a real case from international trade company CF Line, which is a totally new trade company located in Kalajoki, and which has started this operation summer 2012. The objective of the thesis essay is to research and analyze Chinese market by using marketing, supply chain and financial knowledge to evaluate the feasibility of case Fazer. It is an export plan of an existing product - Fazer chocolate, to enter a new market. From marketing view, I will use several marketing tools to analyze the product environment. Financial aspect is worked for financial statement and existing company position. And Supply chain is focused on real logistics perspective. From my thesis, it is possible to understand basic relationship between Fazer chocolate production and Chinese food market. I wish it will enlighten and guide more SMEs in which wish to implement export business between Finland and China

    Complexity or simplicity? Designing product pictures for advertising in online marketplaces

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    In online marketplaces, many sellers highlight product and service information directly within product pictures for advertising purposes. Such a strategy increases the visual complexity of the picture and provides more information to support buyers’ judgment. However, when other sellers adopt the same method, a given picture will not be conspicuous enough to be noticed. To address this issue, the concept of complexity contrast is introduced. No prior attention has been paid in literature to the interplay between visual complexity and complexity contrast. This research proposes a theoretical model to explain the influences of visual complexity and complexity contrast on buyers’ pleasantness in shopping, while perceptual and conceptual fluency act as mediators. Results from a lab experiment suggest an entangled effect of complexity contrast and visual complexity, indicating that buyers are influenced more by the conspicuousness of a product picture, rather than the information conveyed by a product picture when it is visually overwhelming

    How buyers perceive the credibility of advisors in online marketplace: review balance, review amount and misattribution

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    In an online marketplace, buyers rely heavily on reviews posted by previous buyers (referred to as advisors). The advisor’s credibility determines the persuasiveness of reviews. Much work has addressed the evaluation of advisors’ credibility based on their static profile information, but little attention has been paid to the effect of the information about the history of advisors’ reviews. We conducted three sub-studies to evaluate how the advisors’ review balance (proportion of positive reviews) affects the buyer’s judgement of advisor’s credibility (e.g., trustworthiness, expertise). The result of study 1 shows that advisors with mixed positive and negative reviews are perceived to be more trustworthy, and those with extremely positive or negative review balance are perceived to be less trustworthy. Moreover, the perceived expertise of the advisor increases as the review balance turns from positive to negative; yet buyers perceive advisors with extremely negative review balance as low in expertise. Study 2 finds that buyers might be more inclined to misattribute low trustworthiness to low expertise when they are processing high number of reviews. Finally, study 3 explains the misattribution phenomenon and suggests that perceived expertise has close relationship with affective trust. Both theoretical and practical implications are discussed

    Trust in the Sharing Economy: A Behavioral Perspective on Peer-to-Peer Markets

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    Detecting Fraudsters in Online Auction Using Variations of Neighbor Diversity

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    Inflated reputation fraud is a serious problem in online auction. Recent work suggested that neighbor diversity is an effective feature for discerning fraudsters from normal users. However, there exist many different methods to quantify diversity in the literature. This raises the problem of finding the most suitable method to calculate neighbor diversity for detecting fraudsters. We collect four different methods to quantify diversity, and apply them to calculate neighbor diversity. We then use these various neighbor diversities for fraudster detection. Experimental results on a real-world dataset demonstrate that, although these diversities were calculated differently, their performances on fraudster detection are similar. This finding reflects the robustness of neighbor diversity, regardless of how the diversity is calculated

    Sentiment Analysis in Sales Estimation: An Econometric Analysis of Product Listings and Reviews in a Chinese Cross-Border E-Commerce Context

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    Since the advent of electronic word-of-mouth communication, particularly in the form of user-generated reviews on e-commerce platforms, research has been undertaken to quantify and draw insights from this growing wealth of data. Coinciding developments in machine learning and natural language processing have enabled the systemic analysis of these texts, heightening the role of user feedback from a simple information channel between users to an indispensable source of “big data” information regarding consumer sentiment and behaviour. While otherwise extensive, contemporary research into the role of consumer sentiment, and, in particular, its effect on sales outcomes, is largely built around data gathered from Western e-commerce platforms, most notably Amazon. This has potentially limited its generalizability to wider contexts. In addition, many studies simplify the role of feedback valence by interpreting the sentiment polarity of a written review as equivalent to its corresponding numerical rating – a conflation that seems to go against existing research into rating inflation and other biases. This study seeks to further this field of e-commerce research by accounting for these issues. Us-ing cross-sectional data gathered from an industry-leading Chinese cross-border e-commerce platform, this study analyses the relationships between user-generated review sentiments and order amounts in a new context. By applying three different sentiment analysis tools to a total of 451,375 product reviews, overall sentiment polarity and subjectivity metrics were calculated for 8,319 product listings. Using these values, alongside other control variables (including numerical ratings, separate from sentiment polarities) from the listings, econometric regression models de-scribing the relationships were estimated and interpreted. The findings of this study demonstrate that, on a broad level, the notion of review sentiment polarity being positively related to sales outcomes is generalizable beyond the Western context. The role of a more nuanced aspect of review sentiments, namely the subjectivity of reviews, is found to be seemingly different from existing research into Western platforms, albeit somewhat inconclusively. The findings also support the notion that review sentiment polarity is not directly represented by its corresponding numerical rating, and that future studies should continue to differentiate between these two metrics. This study leaves open the exact causal nature of these relationships, requiring future research using time series data over multiple years. In addition, a greater variety of product categories could be studied in order to confirm the overall generalizability of these findings
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