There has been lots of research done on customer retention in electronic commerce by using different theories and Model. But there is very less or no work done based on MODE (Motivation and Opportunity as Determinants) model by Fazio 1990. This thesis used MODEL to predict the factors that determine customer in retention in EC. Motivation and opportunity are the most important determinants for consumers choosing an online store. To study motivation and opportunity mechanisms underlying consumer-e-retailer exchange relationship, this research takes a new perspective, a perspective directed toward customer intention to repurchase or customer retention. By integrating MODE model of Fazio 1990 with ¡V process feasibility, switching cost, and relational bond. This study develops an integrated model of consumer retention in an e-retailer. Data for the study was collected using an online survey distributed via email, posting link on the social networking sites linkedin, facebook, and discussion boards¡¦ bbs, NSYSU website. Hypotheses were tested using structural equation modeling of SmartPls. Findings of the study imply that consumer retention in an online store is the affect of consumer motivation towards same online store. Specifically, a consumer¡¦s attitudes toward the key components of his/her entire online purchase experience (i.e., financial bond, social bond, structural bond, time and money saving, and switching cost) constitute the key drivers of consumer retention. Findings also indicate that motivation is intrinsically beneficial. If a consumer motivated by an online store, consumer will come back in the future to repurchase from the same e-retailer. Further, findings suggest that though motivation has a direct effect on future intentions and repurchase. Additionally, findings of the study imply that the effects of motivation on repurchase intention, but the opportunities available from another online store doesn¡¦t affect consumer attitude towards repurchase intention. Moreover search and experience type product moderately affect consumer attitude towards repurchase intention.

How should a company best allocate its spending between acquisition and retention? Under what condition should a company devote resources and money to analytics? The above questions are just examples of more general issues concerning many companies when managing their customer acquisition and retention programs. To answer the above questions, I will conduct a study on the allocation of financial resources between incentives that target different types of customers, and the allocation of resources between incentives and analytics spending. This research first distinguishes between customers and acquisition, between incentive and price discount, and between acquisition and retention. It then proposes a new concept, “free rider”, in a customer acquisition and retention context. Building on the free-rider concept, two mathematical models are formulated to examine the optimal allocation between acquisition incentive, retention incentive, and analytics spending. Closed-form solutions are reached for both models and the results are interpreted in the context of marketing practice. The conditions leading to different patterns of optimal solutions of analytics spending, acquisition incentives, and retention incentives are discussed. Specifically, the detailed conditions under which the optimal acquisition incentives is zero or non-zero, the optimal retention incentives is zero or non-zero, and the optimal analytics spending is zero or non-zero, are provided. Factors determining the ceiling for acceptable level of cost of analytics are also examined.

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This paper analyzes the diffusion of internet-based distance education technology (NETDE) among the US associate colleges. The study finds that an institution with experience in using an earlier generation distance education technology is more likely to adopt NETDE than an institution without such an experience. The finding supports the view of Cohen and Levinthal (1990) that an organization's 'absorptive capability' plays a significant role in its innovative activities. Institution size also facilitates the adoption of NETDE. We relate this size effect to market power because the size effect is partly caused by customer switching costs present in the NETDE market. Finally, we find that, among public institutions, the presence of close competitors motivates an institution to adopt NETDE earlier.

The purpose of this study was to examine the effectiveness of the current relationship building Supply Chain Management (SCM) and Customer Relationship Management (CRM) practices which could build business partners’ loyalty in the SCM context. A proposed model was developed with variables including mutual benefits/fairness, trust, retention, loyalty, and switching cost. Previous research examined the partial relationships in the proposed model, and no research has included the switching cost with all the variables in the proposed model. The quantitative methodology involving a survey method was employed for this exploratory study. The hypothesised relationships were partially supported depending on the type of SCM. The most significant variable having an effect on the switching cost was also different depending on the type of SCM. The SCM practice applied from Human CRM (i.e. emotional connections) in a business-to-business environment was the least effective SCM for loyalty but had a significant impact on switching cost.

Generally, service industries require a rapid innovation of service portfolios to gain and maintain a competitive advantage. In this context, service elimination is a tool of portfolio renewal, where customer retention is a strategic priority for companies. This is especially so because service elimination usually causes higher churn rates than an average churn in telecommunications. Thus, customer retention is seen as a major aspect in enhancing service elimination success. The purpose of this paper is to investigate the factors that increase customer churn in the case of service elimination. We use one of the three Hungarian telecommunication Operator's databases containing usage data three months before and after Service elimination in the course of a major service package reform. Contract-related information and demographics of 10 065 customers are used to differentiate between high and low churn factors, taking care of a possible sample selection problem. The results show that in the course of service elimination there is a significant positive relationship between price decrease, tenure, interaction intensity on the one, and customer retention on the other side. Besides these, demographics (age and residence) also play an important role in explaining churn rates during service elimination. Furthermore, we find that a higher monthly fee after elimination increases the customer´s usage intensity. This research aims to contribute both to service elimination, as well as to customer retention literature, by hierarchical modeling of retention and usage during service elimination with practical implications for decision-makers in rapidly innovating telecommunication markets. / Series: Department of Economics Working Paper Series

Abstract Recent times have witnessed increasing availability of mobile technology-based products/services in developing regions such as Africa. However, the extant literature has not traditionally focused on understanding the adoption and use of these technologies by consumers in these parts of the world. This gap cannot be ignored and the need to investigate consumer intention to use mobile based-technology in this region is becoming paramount to their successful implementation. One such mobile-based technology is the M-pesa financial service. The current study merged appropriate theories that could predict consumer intention to use this M-pesa service in two African countries, Kenya and South Africa. First, the two countries were compared in an attempt to provide an explanation of why the launch of the M-pesa service has been more successful in Kenya than in South Africa. It then examined the effects of the Technology Acceptance Model variables (perceived usefulness and perceived ease of use), subjective norm from the Theory of Reasoned Action, self efficacy from the Social Cognitive Theory, and six dimensions of Switching Costs, on consumers intention to use M-pesa. To measure the study’s variables, validated scales from the IS literature, social psychology literature, and economics literature were identified and adopted. Data were collected using paper based survey instruments from individuals residing in low-income communities in Kenya (N=265) and South Africa (N=150), thus a total of 415 responses. The results indicate there are correlations between all variables and intention to use, however, only perceived usefulness, perceived ease of use, and subjective norms have a direct influence on intention to use M-pesa. The model explained 33.1% of the variance in intention to use M-pesa. The results suggest that while switching costs do not have a direct influence on intention to use, some of their effects are mediated in predicting intention to use. Thus, this study has paved the way for future testing and enhancement of the study’s model. The study’s contribution to theory and practice are also presented.

Customer loyalty has been investigated in years, and its importance to corporate is understood by managers. The purpose of this paper is to find out what kinds of specific and concrete operational factors have an important impact on Chinese mobile telecom customer loyalty. Firstly, a model was established to represent the relationship between customer loyalty and its influencing factors (customer satisfaction, perceived quality, customer value, switching cost and corporate image). 11 specific and concrete operational factors were found according to Chinese mobile telecom industry which were never been studied by the pre-researchers. Secondly, a survey of questionnaire has been conducted which help to found out that the 9 factors (call quality, coverage of area, SMS quality, the convenience and reliability of Inquiring phone fee system, service quality of service center and hotline, rating price of given quality, customer’s worry of troubles after change cell phone number, social responsibility, advertisements about corporate image) have an important impact on customer loyalty on Chinese mobile telecom industry. Thirdly, separating these 9 factors into 3 groups through investigate the performance of customer loyalty in China Mobile. At last, some recommendations were given to China Mobile

Quality of a prescription drug is uncertain to patients, physicians and even the manufacturer of the drug. Because this uncertainty can deter physicians from prescribing the drug, it is important to investigate how various marketing communication activities help reveal the true quality of its product. In particular, this study investigates publicity and advertising under quality uncertainty. Chapter 1 studies the effect of publicity on consumer demand with a reduced form approach. Chapter 2 structurally investigates the roles of detailing and publicity when the information spill-over is present. Both chapters study the market of anti-cholesterol drugs (statins). Chapter 1 investigates the effects of publicity (media coverage) on consumer demand. The main obstacle to measuring the impact of publicity is that data on media coverage are difficult to interpret. To overcome this obstacle, we propose a new way to code information presented in news articles, mapping the information to a multi-dimensional attribute space. We combine our publicity data with data on sales, detailing, medical journal advertising, direct-to-consumer advertising (DTCA) and landmark clinical trial outcomes, and estimate a demand model. Our results suggest that not all forms of publicity are equal. In chapter 2, we study consumer learning about scientific evidence and its impact on demand for pharmaceutical products by using the Bayesian learning model. Unlike previous literature, our learning model allows consumer’s prior quality perceptions to be correlated across brands. This unique feature of the model allows us to investigate information spill-over effects across brands. The information spill-over allows late entrants to free-ride on first movers’ investment in clinical trials and marketing activities and to gain late mover advantage. In addition to using product level market share data, we supplement them with switching rates and discontinuing rates. The switching rate data are particularly useful for taking the presence of switching costs into consideration, which has been ignored in the literature using product-level data. Our estimated structural model has implications for managers in allocating resources to various types of marketing activities more efficiently and helps forecast returns of clinical trials that are sponsored by pharmaceutical firms.

Quality of a prescription drug is uncertain to patients, physicians and even the manufacturer of the drug. Because this uncertainty can deter physicians from prescribing the drug, it is important to investigate how various marketing communication activities help reveal the true quality of its product. In particular, this study investigates publicity and advertising under quality uncertainty. Chapter 1 studies the effect of publicity on consumer demand with a reduced form approach. Chapter 2 structurally investigates the roles of detailing and publicity when the information spill-over is present. Both chapters study the market of anti-cholesterol drugs (statins). Chapter 1 investigates the effects of publicity (media coverage) on consumer demand. The main obstacle to measuring the impact of publicity is that data on media coverage are difficult to interpret. To overcome this obstacle, we propose a new way to code information presented in news articles, mapping the information to a multi-dimensional attribute space. We combine our publicity data with data on sales, detailing, medical journal advertising, direct-to-consumer advertising (DTCA) and landmark clinical trial outcomes, and estimate a demand model. Our results suggest that not all forms of publicity are equal. In chapter 2, we study consumer learning about scientific evidence and its impact on demand for pharmaceutical products by using the Bayesian learning model. Unlike previous literature, our learning model allows consumer’s prior quality perceptions to be correlated across brands. This unique feature of the model allows us to investigate information spill-over effects across brands. The information spill-over allows late entrants to free-ride on first movers’ investment in clinical trials and marketing activities and to gain late mover advantage. In addition to using product level market share data, we supplement them with switching rates and discontinuing rates. The switching rate data are particularly useful for taking the presence of switching costs into consideration, which has been ignored in the literature using product-level data. Our estimated structural model has implications for managers in allocating resources to various types of marketing activities more efficiently and helps forecast returns of clinical trials that are sponsored by pharmaceutical firms.