Author: Franziska M. Bongers
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Tim Louis Meyer
Publisher:
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Category :
Languages : en
Pages :

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Author: Erdem Dogukan Yilmaz
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Category :
Languages : en
Pages :

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Author: Mingwen Yang
Publisher:
ISBN:
Category : Consumer complaints
Languages : en
Pages :

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My dissertation provides prescriptive solutions and managerial implications for three novel operational and strategic challenges faced by firms or platforms in online business. The first problem arises from the need to manage online customer opinions. Online review platforms such as Expedia.com and Tripadvisor.com allow firms to respond to customer complaints. However firms need to carefully decide when to respond to negative reviews. To unravel the underlying mechanics of the problem, I develop a stochastic differential equation model (SDE) that describes the evolution of review ratings over time for a given response strategy employed by the firm. This model is validated using data on online customer reviews and firm responses from two of the world’s largest online travel agents. My approach is not just predictive, but more importantly one that can be used in a prescriptive sense, namely, to prescribe a response strategy that controls review ratings in a desired manner. I operationalize the theoretical response strategy in the stochastic model to an operational prescription that a firm can implement and show the applicability of the approach for different business objectives, such as Mean control, Mean-Variance control, and Service-Level control. Finally, I demonstrate the flexibility of the SDE model by extending it to encompass multiple state variables. The second problem extends the idea of online reputation management to competitive settings. I consider a market consisting of competing firms that participate in a platform such as Expedia or Yelp. Each firm exerts effort to improve its ratings, but in doing so, also influences the mean market rating. The sales of a firm are influenced by its own ratings and the mean rating of the firms in the market. An equilibrium analysis of the mean market rating reveals several insights. A more heterogeneous market (one where the parameters of the firms are very different) leads to a lower mean market rating and higher total profit of the firms in the market. The results can inform platforms to target certain firms to join: Growing the middle of the market (firms with average ratings) is the best option considering the goals of the platform (increase total profit of the firms) and the other stakeholders, namely, incumbents and consumers. For firms, I find that a firm’s profit can increase from an adverse event (such as, a reduction in sales margin, or an increase in the cost of control) depending on how other firms in the market are affected by the event. The findings are particularly significant for platform owners who could benefit from growing the platform in a strategic manner. The third problem addresses a novel Financial Technology (Fintech) phenomenon in social trading. In social trading, less experienced investors (followers) are allowed to copy the trades of experts (traders) in real-time after paying a following fee. This raises the transparency revenue tension: a dilemma between the need to release trading information transparently versus the risk of followers free riding on such information. I demonstrate the tension using data from a leading social trading platform operating in the Foreign Exchange market. An optimization model is developed to maximize information transparency while respecting a money-at-risk constraint. The performances of three information release policies are compared. Finally, I optimize platform revenue using an optimal release policy.

Author: Irfan Kanat
Publisher:
ISBN:
Category : Computer software
Languages : en
Pages : 95

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The recent changes in the software markets gave users an unprecedented numberof alternatives for any given task. In such a competitive environment, it is imperativeto understand what drives user behavior. To that end, the research presented inthis dissertation, tries to uncover the impact of business strategies often used in thesoftware markets.The dissertation is organized into three distinct studies into user choice and postchoice use of software. First using social judgment theory as foundation, zero pricestrategies effects on user choice is investigated, with respect to product features,consumer characteristics, and context effects. Second, role of social features inmoderating network effects on user choice is studied. And finally, the role of socialfeatures on the effectiveness of add-on content strategy on continued user engagementis investigated.The findings of this dissertation highlight the alignments between popular businessstrategies and broad software context. The dissertation contributes to the litera-ture by uncovering hitherto overlooked complementarities between business strategyand product features: (1) zero price strategy enhances utilitarian features but notnon-utilitarian features in software choice, (2) social features only enhance networkexternalities but not social influence in user choice, (3) social features enhance theeffect of add-on content strategy in extending software engagement.

Author: Janina Garbas
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Author: Jong-Woon Kim
Publisher:
ISBN:
Category :
Languages : en
Pages : 316

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Author: Berin Szoka
Publisher: TechFreedom
ISBN: 0983820600
Category : Computers
Languages : en
Pages : 578

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Author: John Stuart Mill
Publisher:
ISBN:
Category : God
Languages : en
Pages : 284

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Author: Michael S. Trusov
Publisher:
ISBN:
Category : Internet marketing
Languages : en
Pages : 346

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