In this dissertation, I study coordination or collaboration settings that are either within company or at inter-organizational levels in the form of three essays. In the first essay, I study the relationship between a client and a vendor in value co-creation environments such as knowledge intensive services. I consider that the client gets utility from the project throughout the development period. The output is contingent on the effort levels of each party and I allow these effort levels to be dynamic. Hence, the client needs to optimally decide the terms of the payment so as to maximize the project output and minimize its cost. In my second essay, I study another value co-creation environment. In this case, unlike the first essay, I assume that the effort levels are not observable but might be monitored. In both essays, I analyze the performance of different contracts and find the best one for the client in diverse settings. Among several other results, I derive the conditions under which the client chooses not to observe vendor’s effort level and operates in a double moral hazard environment. In addition, I show that the remaining time of the project and the client’s valuation of the project regulate the behavior of the effort levels and some other characteristics in the collaboration. In the third essay, I consider a subscription based rental organization, such as Netflix and Blockbuster. In these environments, the satisfaction of customers de- pends on the availability of requested products. Hence, it is important for these firms to satisfy as much demand as possible. Recommender systems, in a DVD- rental context, are typically used to help customers in finding the right movies for them. However, recommendations can be utilized to shift demand among movies considering the inventory level and future demand to increase the number of satisfied customers or profitability. I address this issue by considering inventory in the optimization of recommender systems. I present several results that could be utilized by managers in order to make important tactical and operational decisions. Results suggest that the proposed approach may improve profitability of the firms substantially.

<p>The aim of this study is to illustrate, adapt and develop methods of survival analysis in analysing and estimating customer survival time in subscription-based businesses. Two particular objectives are studied. The rst objective is to redene the existing survival analysis techniques in business terms and to discuss their uses in order to understand various issues related to the customer-rm relationship.</p>

Distributed directory services are an evolving paradigm in the distributed computing arena. They are a shift from the centralized directory that causes delay and does not scale well to widespread peer-to-peer networks. With networking becoming more pervasive, there is a need to integrate the heterogeneity of device, data and network with the applications that are built on them. SyD or System on Mobile Devices is a middleware that is being used to implement such a distributed directory service. To provide a persistent global view of data, we serialize and synchronize the distributed directories. The SyD APIs provide a high-level environment to rapidly develop collaborative applications for such networks in a systematic manner. An intervehicle communication application that notifies the driver of a vehicle of the available parking spots in the vicinity, allows us to see the practical working and benefits of the distributed directory paradigm.

<p>The aim of this study is to illustrate, adapt and develop methods of survival analysis in analysing and estimating customer survival time in subscription-based businesses. Two particular objectives are studied. The rst objective is to redene the existing survival analysis techniques in business terms and to discuss their uses in order to understand various issues related to the customer-rm relationship.</p>

Philosophiae Doctor - PhD / Subscription-based industries have seen a massive expansion in recent decades. In this type of industry the customer has to subscribe to be able to enjoy the service; there-fore, well-de ned start and end points of the customer relationship with the service provider are known. The length of this relationship, that is the time from subscription to service cancellation, is de ned as customer survival time. Unlike transaction-based businesses, where the emphasis is on the quality of a product and customer acquisition, subscription-based businesses focus on the customer and customer retention. A customer focus requires a new approach: managing according to customer equity (the value of a rm's customers) rather than brand equity (the value of a rm's brands). The concept of customer equity is attractive and straightforward, but the implementation and management of the customer equity approach do present some challenges. Amongst these challenges is that customer asset metric - customer lifetime value (the present value of all future pro ts generated from a customer) - depends upon assumptions about the expected survival time of the customer (Bell et al., 2002; Gupta and Lehmann, 2003). In addition, managing and valuing customers as an asset require extensive data and complex modelling. The aim of this study is to illustrate, adapt and develop methods of survival analysis in analysing and estimating customer survival time in subscription-based businesses. Two particular objectives are studied. The fi rst objective is to rede ne the existing survival analysis techniques in business terms and to discuss their uses in order to understand various issues related to the customer-fi rm relationship. The lesson to be learnt here is the ability of survival analysis techniques to extract important information on customers with regard to their loyalties, risk of cancellation of the service, and lifetime value. The ultimate outcome of this process of studying customer survival time will be to understand the dynamics and behaviour of customers with respect to their risk of cancellation, survival probability and lifetime value. The results of the estimates of customer mean survival time obtained from different nonparametric and parametric approaches; namely, the Kaplan-Meier method as well as exponential, Weibull and gamma regression models were found to vary greatly showing the importance of the assumption imposed on the distribution of the survival time. The second objective is to extrapolate the customer survival curve beyond the empirical distribution. The practical motivation for extrapolating the survival curve beyond the empirical distribution originates from two issues; that of calculating survival probabilities (retention rate) beyond the empirical data and of calculating the conditional survival probability and conditional mean survival time at a speci c point in time and for a speci c time window in the future. The survival probabilties are the main components needed to calculate customer lifetime value and thereafter customer equity. In this regard, we propose a survivor function that can be used to extrapolate the survival probabilities beyond the last observed failure time; the estimation of parameters of the newly proposed extrapolation function is based completely on the Kaplan-Meier estimate of the survival probabilities. The proposed function has shown a good mathematical accuracy. Furthermore, the standard error of the estimate of the extrapolation survival function has been derived. The function is ready to be used by business managers where the objective is to enhance customer retention and to emphasise a customer-centric approach. The extrapolation function can be applied and used beyond the customer survival time data to cover clinical trial applications. In general the survival analysis techniques were found to be valuable in understanding and managing a customer- rm relationship; yet, much still needs to be done in this area of research to make these techniques that are traditionally used in medical studies more useful and applicable in business settings. / South Africa

Subscription-based services are becoming more popular in today’s society. Therefore, any company that engages in the subscription-based business needs to understand the user behavior and minimize the number of users canceling their subscription, i.e. minimize churn. According to marketing metrics, the probability of selling to an existing user is markedly higher than selling to a brand new user. Nonetheless, it is of great importance that more focus is directed towards preventing users from leaving the service, in other words preventing user churn. To be able to prevent user churn the company needs to identify the users in the risk zone of churning. Therefore, this thesis project will treat this as a classification problem. The objective of the thesis project was to develop a statistical model to predict churn for a subscription-based service. Various statistical methods were used in order to identify patterns in user behavior using activity and engagement data including variables describing recency, frequency, and volume. The best performing statistical model for predicting churn was achieved by the Random Forest algorithm. The selected model is able to separate the two classes of churning users and the non-churning users with 73% probability and has a fairly low missclassification rate of 35%. The results show that it is possible to predict user churn using statistical models. Although, there are indications that it is difficult for the model to generalize a specific behavioral pattern for user churn. This is understandable since human behavior is hard to predict. The results show that variables describing how frequent the user is interacting with the service are explaining the most whether a user is likely to churn or not. / Prenumerationstjänster blir alltmer populära i dagens samhälle. Därför är det viktigt för ett företag med en prenumerationsbaserad verksamhet att ha en god förståelse för sina användares beteendemönster på tjänsten, samt att de minskar antalet användare som avslutar sin prenumeration. Enligt marknads-föringsstatistik är sannolikheten att sälja till en redan existerande användare betydligt högre än att sälja till en helt ny. Av den anledningen, är det viktigt att ett stort fokus riktas mot att förebygga att användare lämnar tjänsten. För att förebygga att användare lämnar tjänsten måste företaget identifiera vilka användare som är i riskzonen att lämna. Därför har detta examensarbete behandlats som ett klassifikations problem. Syftet med arbetet var att utveckla en statistisk modell för att förutspå vilka användare som sannolikt kommer att lämna prenumerationstjänsten inom nästa månad. Olika statistiska metoder har prövats för att identifiera användares beteendemönster i aktivitet- och engagemangsdata, data som inkluderar variabler som beskriver senaste interaktion, frekvens och volym. Bäst prestanda för att förutspå om en användare kommer att lämna tjänsten gavs av Random Forest algoritmen. Den valda modellen kan separera de två klasserna av användare som lämnar tjänsten och de användare som stannar med 73% sannolikhet och har en relativt låg missfrekvens på 35%. Resultatet av arbetet visar att det går att förutspå vilka användare som befinner sig i riskzonen för att lämna tjänsten med hjälp av statistiska modeller, även om det är svårt för modellen att generalisera ett specifikt beteendemönster för de olika grupperna. Detta är dock förståeligt då det är mänskligt beteende som modellen försöker att förutspå. Resultatet av arbetet pekar mot att variabler som beskriver frekvensen av användandet av tjänsten beskriver mer om en användare är påväg att lämna tjänsten än variabler som beskriver användarens aktivitet i volym.

The rapid growth of technological infrastructure has changed the way companies do business. Subscription based services are one of the outcomes of the ongoing digitalization, and with more and more products and services to choose from, customer churning has become a major problem and a threat to all firms. We propose a machine learning based churn prediction model for a subscription based service provider, within the domain of financial administration in the business-to-business (B2B) context. The aim of our study is to contribute knowledge within the field of churn prediction. For the proposed model, we compare two ensemble learners, XGBoost and Random Forest, with a single base learner, Naïve Bayes. The study follows the guidelines of the design science methodology, where we used the machine learning process to iteratively build and evaluate the generated model, using the metrics, accuracy, precision, recall, and F1- score. The data has been collected from a subscription-based service provider, within the financial administration sector. Since the used dataset is imbalanced with a majority of non- churners, we evaluated three different sampling methods, that is, SMOTE, SMOTEENN and RandomUnderSampler, in order to balance the dataset. From the results of our study, we conclude that machine learning is a useful approach for prediction of customer churning. In addition, our results show that ensemble learners perform better than single base learners and that a balanced training dataset is expected to improve the performance of the classifiers.

The sharing economy enables sustainable consumption through efficient access to products, but transitioning from ownership to a subscription-based model faces barriers. The thesis author explored how the decoupling of product ownership impact on the variables; consumer's perceptions of - psychological value, monetary value, social value, brand image, brand attachment, brand loyalty, service quality, and product quality and performance in the context of white goods. Furthermore, the thesis authors added sustainability awareness as an important variable, while discussing the decoupling of product ownership. Although, there is a lot of literature on the above-mentioned variables the relationship between the decoupling of product ownership and the mentioned variables was theoretically and empirically unexplored. Using a quantitative and deductive research approach, an online survey consisting of 29 questions was conducted. The empirical data revealed that the decoupling of product ownership impact all the variables under study and have a significant relationship with them. The impact of decoupling of product ownership was found to be strongest on consumers' perception of - service quality, followed by brand loyalty, brand attachment, product quality and performance, and monetary value. By gaining a deeper understanding of the relationships between the variables companies can effectively develop marketing strategies, subscription plans, and pricing strategies.

Prenumerationsmodellen är inget nytt fenomen, men har på senare tid spridit sig till nya branscher. Modellen har populariserats till följd av bland annat digitaliseringen, den ökade konkurrensen och nya framväxande kundvärden. Prenumerationsmodellen har fått positiv kritik för sina återkommande och förutsägbara intäkter, men för att det ska bli verklighet krävs det att kunderna stannar kvar. Flertalet prenumerationsföretag har låga utträdesbarriärer, vilket resulterar i att de kontinuerligt behöver skapa ett högt uppfattat värde för att kunderna ska stanna kvar. För att prestera väl och uppnå mål såsom att skapa ett högt uppfattat värde kan företag använda sig av prestationsmätning.Studiens syfte är att bidra med ny kunskap som förklarar hur företag med en prenumerationsmodell använder prestationsmätning i syfte att förlänga kundernas varaktighet.Studien har genomförts genom kvalitativa intervjustudier på fyra prenumerationsföretag inom olika branscher. Genom att studera likheter hos studieobjekten har slutsatser kunnat dras som kan förklara prenumerationsföretag generellt.Studien kom fram till att prenumerationsföretag, i syfte att förlänga kundernas varaktighet, använder prestationsmätning för de attribut som identifierats som särskilt värdeskapande för värdeerbjudandet. På så sätt kan prestationsmätningen användas mer optimalt för att skapa kundvärde och därmed förlänga kundernas varaktighet. Därtill fann studien att mål och mått i stor utsträckning är specifika för enskilda prenumerationsföretag. Studien fann även att värdeerbjudandet tycks påverka hur prenumerationsföretag använder sin prestationsmätning. Genom att prenumerationsföretag använder information från prestationsmätningen i syfte att agera på avvikelser, ökar deras möjlighet att förlänga kundernas varaktighet. Däremot tycks marknadsandel vara ett olämpligt mått för att besvara huruvida prenumerationsföretag skapar kundvärde och bör således inte användas i syfte att förlänga kundernas varaktighet. Slutligen fann studien att prenumerationsföretag använder en kombination av diagnostisk och interaktiv uppföljning och att det ständigt föränderliga kundvärdet innebär att uppföljningen till stor del är interaktiv.

To increase the number of customers buying from a web application, theory states that the application needs to be easy to use. In this study, navigability and usability will be investigated and tested on a web-based book-subscription service. The purpose of this study is to come to new conclusions regarding what is important for navigability and usability for subscription services that target students. A web application was created for an online book club subscription service for students at Linköping University. It was created in two different iterations where each iteration was tested on 12 students, which according to theory is a sufficient number of testers. The first iteration was designed based on theory and the second was redesigned based on the input from the test users. Counting the number of clicks taken by the user was the main method used for evaluating navigability, while Concurrent Thinking Aloud, System Usability Scale and Retrospective Probing Procedure were the methods used to measure usability. The most considerable changes made between the two iterations were the updating of the filtering function on the find book club page and the implementation of a search function on the same page. This was also the page where the most improvement in the number of clicks was made. In line with the theory, the usability improved in the tests after changes had been made that test users had commented on. The number of clicks did mostly decrease in the second iteration but not in all categories. This result does not mean that the user experience was not improved since some requested functionality was implemented that required additional clicks.