Establishing a Stable Prediction Model of Loyal Customers for Repurchase Behavior

In this changing time of network technology, online shopping has become an indispensable of trading platform for many people. Previous study also found out good forecasting result from consumption behaviors of the general and the individual (including consumers of re-purchased rate and purchase amount), which established through activity probability. However the same data in different time points often caused instability of forecast accurate probability. This reason can be attributed by general parameters’ non-optimization, which leads to managers’ trouble in decision-making. Based on this, our study through the improved activity probability calculated, as well as normal distribution’s value simulated as the actual value by bootstrap method, to identify the most representative parameter to predict consumption behavior that represents the dataset for achieving the highest accuracy of forecast results for the use by enterprises. From simple examples, results tend to be stable and accurate, which is the best and also contributed to management decisions

Do Private Labels Generate Loyalty? Empirical Evidence for German Frozen Pizza

food retailing, private labels, brand loyalty, panel data, hazard analysis, Consumer/Household Economics, Demand and Price Analysis, Institutional and Behavioral Economics, Marketing,

The Role of Logistics Service Quality in Creating Customer Loyalty

The purpose of this dissertation is to examine the loyalty phenomenon and to understand the role of logistics service in creating customer loyalty. The main objective is to help companies assess the impact of logistics service in creating loyalty. Logistics service quality is purported to consist of two separate constructs – relational LSQ and operational LSQ. These elements of LSQ drive satisfaction. This research also explores the loyalty phenomenon, which is conceptualized as a causal relationship between affective commitment and purchasing behavior. The strength of this relationship is proposed to be moderated by calculative commitment, which involves the calculation of costs and benefits and the assessment of the investments made in the relationship, along with the availability of alternatives. Further, satisfaction influences the loyalty relationship differently. This research contends that satisfaction has a linear relationship to affective commitment, but its relationship to purchase behavior is nonlinear, being more significant at the extremes. These constructs are defined and operationalized, and by testing its components, along with calculative commitment and satisfaction, different loyalty types should be identified. Understanding that firms have a portfolio of different customer relationships, the research should ascertain what conditions drive various types of customer relationships. This nomological model should also provide managerial insight to the proposition that there are different loyalty types that would have different strategic implications. Top firms recognize the differences in the needs and desires of major customers and design offerings according to those needs (Zhao, Droge and Stank 1996). Because an important goal for firms is to grow a larger share of the profitable revenue available (Bowersox, Closs and Stank 2000), managers must realize that not all customers are the same. This research should help distinguish different customer segments based on their loyalty profiles. If the loyalty relationship can be better understood, then managers will have more clarity about how to determine what level of logistics service (as well as other services) to provide to different customer groups

Exploring Factors That Influence Consumer Loyalty to Automobile Dealerships in New York

Customer attrition has severe effects on profitability and organizations incur high costs acquiring new customers while existing ones generates more profits. However, when an organization reduces customer quitting by 5%, it raises profits by 2-8% (Khan & Rizwan, 2014). Previous studies gave much attention to factors of customer loyalty such as product quality and customer satisfaction but none have qualitatively explored the factors relative to automobile dealerships businesses in New York City. The aim with this study was to fill the research gap. Based on Theory of Reasoned Action, the purpose of this qualitative multiple-case study was to explore some factors that influence customer loyalty towards automobile dealerships after initial purchases. Data were collected from 50 participants who have purchased, leased, or serviced automobiles from same dealership for over 60 months. Data analysis involved thematic and content analysis. The 3 emergent themes in final report related to Customer Satisfaction, Product Quality and Service Quality influences on consumers loyalty towards dealerships. Findings could result in retention programs and strategies for automobile business managers to inhibit attrition rate while alleviating the damaging effects to sales and profitability. This study is beneficial to automobile business managers, policy makers, and academics

Service Delivery Management: A Process for Proactively Ensuring Customer Satisfaction.

SDM is a process model, based on service marketing components, to position a service while concurrently being a service delivery management tool improving serviceen counter processes. Added to a service script, SDM can increase customer satisfaction, quality perception, voice levels and repurchase intentions in a general service encounter scenario as well as during episodes which include a failure. Addressing mishaps requires particular attention, since Consumer Complaint Behaviour research shows that most customers prefer to switch suppliers, rather than offer constructive feedback. This means that many service failures go unnoticed, with a large proportion of customers defecting. Since most services are performed in real time by service personnel, consistent quality output is a challenge. Therefore, occasional service failures are inevitable. Present research recognises this by offering suggestions, but does not present an integrated framework like SDM, using the presence of a customer during a service encounter as an unique opportunity to resolve issues on the spot. An elicitation process is used as a first step, attempting to improve voice and minimising lost feedback. Step two is a specific service recovery process, adapted to the failure type. SDM processes can also lead to a general increase of satisfaction and quality perception, regardless of whether or not there was a service failure. With satisfaction generally being regarded as an actual repurchase behaviour indicator, this may lead to increased sales turnover, while a higher quality perception may lead to a larger price premium tolerance and therefore higher profits. Higher service quality perceptions can also be used as a marketing positioning tool to differentiate a service from competitors. Data collected supported all hypotheses put forward in this thesis, showing statistically significant improvements on all key variables, including a satisfaction rating increase of 24percent when SDM was applied. In academic terms, the process model tested did not only link separate literature streams, but offered an integrated, proactive tool which is capable of operating in real time. Traditionally, academic models and their processes analyse results after an episode concludes, while SDM allows a provider to positively influence or manage satisfaction levels during the service delivery

Service Delivery Management: A Process for Proactively Ensuring Customer Satisfaction.

SDM is a process model, based on service marketing components, to position a service while concurrently being a service delivery management tool improving serviceen counter processes. Added to a service script, SDM can increase customer satisfaction, quality perception, voice levels and repurchase intentions in a general service encounter scenario as well as during episodes which include a failure. Addressing mishaps requires particular attention, since Consumer Complaint Behaviour research shows that most customers prefer to switch suppliers, rather than offer constructive feedback. This means that many service failures go unnoticed, with a large proportion of customers defecting. Since most services are performed in real time by service personnel, consistent quality output is a challenge. Therefore, occasional service failures are inevitable. Present research recognises this by offering suggestions, but does not present an integrated framework like SDM, using the presence of a customer during a service encounter as an unique opportunity to resolve issues on the spot. An elicitation process is used as a first step, attempting to improve voice and minimising lost feedback. Step two is a specific service recovery process, adapted to the failure type. SDM processes can also lead to a general increase of satisfaction and quality perception, regardless of whether or not there was a service failure. With satisfaction generally being regarded as an actual repurchase behaviour indicator, this may lead to increased sales turnover, while a higher quality perception may lead to a larger price premium tolerance and therefore higher profits. Higher service quality perceptions can also be used as a marketing positioning tool to differentiate a service from competitors. Data collected supported all hypotheses put forward in this thesis, showing statistically significant improvements on all key variables, including a satisfaction rating increase of 24percent when SDM was applied. In academic terms, the process model tested did not only link separate literature streams, but offered an integrated, proactive tool which is capable of operating in real time. Traditionally, academic models and their processes analyse results after an episode concludes, while SDM allows a provider to positively influence or manage satisfaction levels during the service delivery

An explanatory and predictive PLS-SEM approach to the relationship between organizational culture,organizational performance and customer loyalty: The case of health clubs

Purpose This study aims to analyze the impact and predictive capacity of organizational culture on both customer loyalty and organizational performance in health clubs using data from managers and customers of health clubs in Spain. Design/methodology/approach A total of 101 managers were asked to measure organizational culture and organizational performance and 2,931 customers were asked to indicate their customer loyalty. The proposed hypotheses were tested and their predictability assessed through PLS-SEM. A composite concept was adopted to analyze the relationships between the different constructs and their indicators. Findings The findings suggest that organizational culture has a positive relationship with both customer loyalty and organizational performance. The four main dimensions of organizational culture that influence this relationship are, in order of significance, organizational presence, formalization, atmosphere and service-equipment. The authors’ model has a very good predictive power for both dependent variables. Originality/value Customer loyalty is an aspect of health clubs that can be improved. This study highlights the importance of creating a strong organizational culture in health clubs, as it enhances and predicts customer loyalty and organizational performance. Its predictability has already been tested with samples of managers and customers, with the analysis being performed from the perspective of the organization’s management and customer perceptions. This study also contributes to the field of sport management, using a predictive PLS-SEM techniqu

Identifying the contribution of financial and non-financial measures in value creation: An exploratory empirical analysis of economic value added and customer satisfaction.

A primary question in the field of marketing strategy involves the role of marketing constructs in the strategic management of an enterprise. A key element of strategy is that firms can choose to follow either a cost or differentiation strategy to create a competitive advantage. Traditional theory suggests that a firm should choose Dose one approach because it is either too difficult to develop a dual cost and differentiation strategy or because the attention of top management is limited in enacting and monitoring a dual strategy. The choice of which performance measures to use to monitor and evaluate the effectiveness of the chosen strategy is an important decision for driving firm performance. Critics have suggested that the exclusive use of traditional financial measures fails to effectively capture the value created in the firm and that non-financial measures need to be added to increase the understanding of new sources of firm value. Research has provided evidence that non-financial measures such customer satisfaction can be linked to increased firm performance and firm value in conjunction with traditional financial measures. In this study, questions about the relationship between economic efficiency, customer satisfaction measures, and firm value metrics are investigated including the size and structure of these relationships. The goal is to relate the value gained by following either a cost strategy or a differentiation strategy or a combination of strategies to assist managers and investors in identifying the relationship between a firm's current condition and its capacity to produce future wealth. In order to explore these relationships, data were gathered from publicly available sources including the American Customer Satisfaction Index (ACSI) and the Stern Stewart Performance 1000. Key variables include the firm's ACSI score, Economic Value Added (EVA), and Market Value Added (MVA). A series of regression models are used to test the structure of how customer satisfaction and financial metrics are reflected in measures of market value added. In addition, a matrix evaluating firms based on their position relative to average EVA and ACSI is created to illustrate the relative effects of cost and differentiation strategies on the level of MVA created over time. The results suggest that the interaction of customer satisfaction measures (ACSI) with the financial metric of economic value added (EVA) is a significant positive predictor of market value added (MVA) and provides incremental value to the sole use of financial measures or non-financial measures in predicting firm value creation. In addition, firms that have both greater than average levels of customer satisfaction and cost efficiency have higher average levels of MVA compared with firms that are lower on either or both cost and differentiation measures. Implications are drawn for marketing practitioners and additional supplemental research topics for strategic marketing analyses are presented.Ph.D.ManagementMarketingSocial SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/132206/2/9959825.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/132206/4/license_rd

The impact of artificial intelligence on customer loyalty and entrepreneurship

Nowadays, every company struggles to success, however there are few of them that actually do. Artificial intelligence is something that is revolutionize the market, as well as, the way that companies structure themselves. This work pretends to illuminate who is searching about the effects that the artificial intelligence can have on customer loyalty and on entrepreneurship. To do that, I created an online survey, answered by 103 people and I made eleven interviews to people that worked or are working in one of these three areas. With these, I pretend to have a better notion about the impact that AI is having or can have in a near future in these areas, the benefits and disadvantages that can create for the companies, or even the utility that can be for a worker launch his own business. After conducting the questionnaire and the interviews and comparing it with the literature review, I came to some conclusions right now that in a very near future the use of AI will be fundamental to the success of any company. You will inevitably have to use AI tools to optimize processes, save costs, but never mischaracterize the company. On the other hand, customer satisfaction is extremely important because it leads to a buyback from the clientes and the good publicity they will do with third parties, however this is only achieved when there is a good mix between the quality of the salesman and the product.Hoje em dia, todas as empresas lutam para serem bem-sucedidas, no entanto, poucas delas realmente o são. A inteligência artificial é algo que está a revolucionar o mercado, bem como a forma como as empresas se estruturam e por isso pode ter um papel fundamental. Com este trabalho pretendo iluminar quem está à procura de respostas sobre os efeitos que a inteligência artificial pode ter na fidelidade do cliente e no empreendedorismo. Para isso, realizei um inquérito "online", respondido por 103 pessoas e fiz 11 entrevistas a pessoas que trabalharam ou estão a trabalhar numa destas três áreas. Com isso, pretendo ter uma melhor noção sobre o impacto que a IA está a ter ou pode vir a ter num futuro próximo nestas áreas, os benefícios e desvantagens que podem criar para as empresas, ou mesmo a utilidade que pode ter para o lançamento de um negócio próprio. Após realizar o questionário e as entrevistas e comparando com a revisão de literatura cheguei a algumas conclusões desde já o facto de num futuro bastante próximo a IA ser fundamental para o sucesso de qualquer empresa. Terá inevitavelmente de usar ferramentas de AI para otimizar processos, poupar nos custos, mas nunca descaracterizando a empresa. Por outro lado, a satisfação do cliente é extremamente importante pois leva a uma recompra por parte dos mesmos e à boa publicidade que irão fazer junto de terceiros, porém isto só é conseguido quando existe um bom mix entre a qualidade do vendedor e do produto

Commitment, Loyalty And Customer Lifetime Value: Investigating The Relationships Among Key Determinants

Using the theoretical underpinnings of relationship marketing, this study examined the relationships among various constructs relating to the management of a firm’s customers. In particular, the study investigated the multidimensional constructs of commitment and loyalty and the effect of a loyalty program on these dimensions. The study explored the relative impacts of affective and continuance commitment on these two dimensions of loyalty in a business-to-business context for a pharmaceutical distribution company.Reseasrchers have argued that affective commitment, being predicated on free choice and emotional attachment, should result in more enduring relationships compared to continuance commitment, which is based on economic benefits and the lack of viable alternatives that raise the exit barriers. The value of continuance commitment remains unclear as it is argued that continuance commitment can both enhance, as well as undermine, marketing relationships. Researchers have also argued that loyalty programs are likely to be more successful if they include, in their design, a greater emphasis on building emotional ties than promoting economic benefits. A self-administered survey was employed among 151 customers of a pharmaceutical distribution company and the results analyzed using structural equation modeling (SEM) with Partial Least Square (PLS-Graph 3.0 Build 1130) for inferential analysis and SPSS version 16.0 for descriptive analyses. The results supported the theorized view that affective commitment has a greater impact on loyalty than does calculative commitment. The results, however, did not support the theorized positions of a significant impact of calculative commitment on loyalty, and there was also no empirical evidence that a loyalty program impacts commitment or customer lifetime value. The managerial and research implications of the study are also presented