E Commerce A Storage Environment - 1025 Words

We use database in our everyday life and some of the common uses of databases are given below: †¢ Personal Cloud Storage: When in our any type of storage device like a phone or a tablet we are saving documents like a photo or an audio file we are saving it in a cloud. Now the cloud here is a storage environment presented to us by syncing data through a powerful database, we not only store data but can call the data anytime and retrieve it. †¢ Social Media: User information is required by every social media platform which is stored by databases to provide the end user with recommendation of friends, topics, businesses and products of preference. †¢ E-commerce: Database is used by any type of online organization to orient and organize their†¦show more content†¦Databases of extreme power are needed to track information regarding day to day basis transactions and even to predict future of the finance world using financial models. †¢ Weather: Prediction of weather is a complex process and depends on numerous factors. These factors are gathered by databases and stored to be analyzed and the resultant report is sent to a weather channel or an in your smartphone. Data taken in by a weather company per day can be of size 20 terabytes. For supporting such data the company uses databases like MySQL, Cassandra and many more. †¢ Government Organizations: For various purposes such as research, legislation, defense and many more, information is collected frequently by government organizations .Very powerful and advanced database systems are used to collect, store and analyze such information. †¢ Online Television Streaming: Netflix is an example of online television streaming service which uses database to generate a list of TV shows and movies to its user, keep track of preference and also to provide a list of shows for recommendation. Highly advanced database management system is required for analyzing such huge amount of data, for example Cassandra. Importance of Non-relational databases †¢ In comparison to relational databases, NoSQL databases are better at providing superb performance while handling data of large scale and variable structures

E Commerce A Storage Environment - 1025 Words

We use database in our everyday life and some of the common uses of databases are given below: †¢ Personal Cloud Storage: When in our any type of storage device like a phone or a tablet we are saving documents like a photo or an audio file we are saving it in a cloud. Now the cloud here is a storage environment presented to us by syncing data through a powerful database, we not only store data but can call the data anytime and retrieve it. †¢ Social Media: User information is required by every social media platform which is stored by databases to provide the end user with recommendation of friends, topics, businesses and products of preference. †¢ E-commerce: Database is used by any type of online organization to orient and organize their†¦show more content†¦Databases of extreme power are needed to track information regarding day to day basis transactions and even to predict future of the finance world using financial models. †¢ Weather: Prediction of weather is a complex process and depends on numerous factors. These factors are gathered by databases and stored to be analyzed and the resultant report is sent to a weather channel or an in your smartphone. Data taken in by a weather company per day can be of size 20 terabytes. For supporting such data the company uses databases like MySQL, Cassandra and many more. †¢ Government Organizations: For various purposes such as research, legislation, defense and many more, information is collected frequently by government organizations .Very powerful and advanced database systems are used to collect, store and analyze such information. †¢ Online Television Streaming: Netflix is an example of online television streaming service which uses database to generate a list of TV shows and movies to its user, keep track of preference and also to provide a list of shows for recommendation. Highly advanced database management system is required for analyzing such huge amount of data, for example Cassandra. Importance of Non-relational databases †¢ In comparison to relational databases, NoSQL databases are better at providing superb performance while handling data of large scale and variable structures

Animal Rights Should Be Afforded On The Basis Of Morality

Animal Rights Although there may be many arguments regarding the proper treatment of animals, rights are a major concern. Humans have domain over animals and therefore act in a responsible way towards them. Affording animals certain rights would improve their living conditions as well as human’s conditions, and increase the awareness of the consequences humans may face due to their maltreatment. Animal rights should be afforded on the basis of morality. As a society of moral and just people, it would be wrong to mistreat animals. The treatment of these animals must be protected by some form of rights. Different animals are consumed by humans in different countries. The animals which are socially acceptable for human consumption vary among†¦show more content†¦Yet animals are affected in many other ways. Animals are being raised solely for human consumption. The animals are raised in overcrowded conditions, kept on dirty conditions, and bred unnaturally. Most Americans would not stand for this treatment of their pets, such as dogs and cats, there should be no difference for other animals. Furthermore, many of the conditions in which animals for human consumption are being raised in would be illegal if imposed on a dog or cat. In the spirit of thanksgiving, the conditions of turkeys shall be highlighted. Wild turkeys live, on average, twelve years and weigh about eighteen pounds. Sadly, farm-raised turkeys live approximately four and a half months and weigh thirty-five pounds. In the wild, turkeys value their family. In fact, turkey brothers stay together for the entirety of their lives. In contrast, turkeys raised on a farm for human consumption are mixed up and treated as a product on a conveyor belt, literally. Animals are being removed from their natural habitats; they are being reproduced and raised on farms for mass production. During this process, the conditions may be poor, chemicals and genetic mutations often take place. All for the benefit of humans, or what is seems. There are many studies and reports outlining the negative impacts of these farms. With stricter rights imposed on animals, society’s health may actually see improvements and

Social Learning Theory and Its Application to Aggression...

Social learning theory proposes that social learning occurs when the individual views a modeled behavior that they value, observes an act if the model has a role model or admired status, and when a person imitates a learned behavior (Bandura, Ribes-Inesta, 1976). The basic foundations of the theory are applied to education policies, understanding psychological disorders, training courses, behavioral modeling, in the media and has a plethora of further applications in today’s society. Another application of the theory is for criminals, violence and aggression. Whether referring to violence in the media, domestic violence, community violence, bullying and others, aggression and violent behaviors can by dissected and expounded using social†¦show more content†¦This experiment was very controversial as Bandura sought to prove that aggression was learned through imitation of others. Children between the ages of three and six were brought in to a room with an adult in one corner and the child in the other. The child’s side contained fun activities while the adult’s side contained a toy set, a mallet and a Bobo doll. The child was told that the toys in the adult corner were only for the adults. In three different groups, children were either subjected to an aggressive adult that would punch and kick the Bobo doll, a non-aggressive adult that would play with the small toys and ignored the Bobo doll and another group where no adult was present. After the ten minute session the child was brought into another room with many toys and after only two minutes, the child is told that they are no longer allowed to play with those toys. The frustrated children were then brought back into the first room, where the experiment sought to measure the physical and verbal aggression, the amount of times the mallet was used as other forms of aggression and other forms of aggression that did not show imitation of the original adult. The experiment found th at children exposed to the aggressive adult were more likely to act more aggressively than the others. The study also found that boys were much more likely to be aggressive and that imitation increased when the model was of the same sex (Bandura, Ross, Ross, 1961).Show MoreRelatedAn Explanation Of An Instinct Theory1547 Words   |  7 PagesAggression is defined as the intention to cause physical or psychological harm to oneself, an object, or another, in a form that is not socially sanctioned. 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Understanding the Effect of Customer Relationship Management Efforts on Customer Retention and Customer Share Development free essay sample

The results show that affective commitment and loyalty programs that provide economic incentives positively affect both customer retention and customer share development, whereas direct mailings influence customer share development. However, the effect of these variables is rather small. The results also indicate that firms can use the same strategies to affect both customer retention and customer share development. ustomer relationships have been increasingly studied in the academic marketing literature (Berry 1995; Dwyer, Schurr, and Oh 1987; Morgan and Hunt 1994; Sheth and Parvatiyar 1995). An intense interest in customer relationships is also apparent in marketing practice and is most evident in firms’ significant investments in customer relationship management (CRM) systems (Kerstetter 2001; Reinartz and Kumar 2002; Winer 2001). Customer retention rates and customer share are important metrics in CRM (Hoekstra, Leeflang, and Wittink 1999; Reichheld 1996). Customer share is defined as the ratio of a customer’s purchases of a particular category of products or services from supplier X to the customer’s total purchases of that category of products or services from all suppliers (Peppers and Rogers 1999). To maximize these metrics, firms use relationship marketing instruments (RMIs), such as loyalty programs and direct mailings (Hart et al. 1999; Roberts and Berger 1999). Firms also aim to build close relationships with customers to enhance customers’ relationship perceptions (CRPs). Although the impact of these tactics on customer retention has been reported (e. g. , Bolton 1998; Bolton, Kannan, and Bramlett 2000), there is skepticism about whether such tac- C Peter C. Verhoef is Assistant Professor of Marketing, Department of Marketing and Organization, Rotterdam School of Economics, Erasmus University, Rotterdam. The author gratefully acknowledges the financial and data support of a Dutch financial services company. The author thanks Bas Donkers, Fred Langerak, Peter Leeflang, Loren Lemon, Peeter Verlegh, Dick Wittink, and the four anonymous JM reviewers for their helpful suggestions. The author also acknowledges the comments of research seminar participants at the University of Groningen, Yale School of Management, Tilburg University, and the University of Maryland. Finally, he acknowledges his two dissertation advisers, Philip Hans Franses and Janny Hoekstra, for their enduring support. tics can succeed in developing customer share in consumer markets (Dowling 2002; Dowling and Uncles 1997). Several studies have considered the impact of CRP on either customer retention or customer share, but not on both (e. g. , Anderson and Sullivan 1993; Bolton 1998; Bowman and Narayandas 2001; De Wulf, Odekerken-Schroder, and Iacobucci 2001). A few studies have considered the effect of RMIs on customer retention (e. . , Bolton, Kannan, and Bramlett 2000). In contrast, the effect of RMIs on customer share has been overlooked. Furthermore, most studies focus on customer share in a particular product category (e. g. , Bowman and Narayandas 2001). Higher sales of more of the same product or brand can increase this share; however, firms that sell multiple products or services achieve share increases by cross-selling other products. Moreover, no study has consider ed the effect of CRPs and RMIs on both customer retention and customer share. It is often assumed in the literature that the same strategies used for maximizing customer share can be used to retain customers; however, recent studies indicate that increasing customer share might require different strategies than retaining customers (Blattberg, Getz, and Thomas 2001; Bolton, Lemon, and Verhoef 2002; Reinartz and Kumar 2003). Prior studies have used self-reported, cross-sectional data that describe both CRPs and customer share (e. g. , De Wulf, Odekerken-Schroder, and Iacobucci 2001). The use of such data may have led to overestimation of the considered associations because of methodological problems such as carryover and backfire effects and common method variance (Bickart 1993). Such data cannot establish a causal relationship; indeed, the argument could be made that causality works the other way (i. e. , I am loyal, therefore I like the company) (Ehrenberg 1997). Longitudinal data rather than cross-sectional data should be used to establish the causal relationship between customer share and its antecedents. Journal of Marketing Vol. 7 (October 2003), 30–45 30 / Journal of Marketing, October 2003 I have the following research objectives: First, I aim to understand the effect of CRPs and RMIs on customer retention and customer share development over time. Second, I examine whether the effect of CRPs and RMIs on customer retention and customer share development is different. My study analyzes questionnaire data on CRPs, operational data on the applied RMIs, and longitudinal data on customer retention and customer share of a (multiservice) financial service provider. Literature Review CRPs and Customer Behavior Table 1 provides an overview of studies that report the effect of CRPs on customer behavior, and it describes the dependent variables, the design and context of the study, the CRPs studied, and the effect of CRPs on behavioral customer loyalty measures (which can be self-reported or actual observed loyalty measures). Table 1 shows that the results of studies that relate CRPs to actual customer behavior are mixed. RMIs and Customer Behavior Table 2 provides an overview of the limited number of academic studies that consider the effect of RMIs. The majority of the studies have focused on loyalty or preferential treatment programs, and the results show mixed effects of these programs on customer loyalty. Despite the intensive use of direct mailings in practice, their effect on customer loyalty has almost been ignored. More important, the effect of RMIs on customer share development over time has not been investigated. tomer relationship largely depends on the applied RMIs (Bhattacharya and Bolton 2000; Christy, Oliver, and Penn 1996; De Wulf, Odekerken-Schroder, and Iacobucci 2001). Moreover, because of the increasing popularity of CRM among businesses, an increasing number of firms are using RMIs. In the model, I also include customers’ past behavior in the relationship as control variables, which might capture inertia effects that are considered important determinants of customer loyalty in business-to-consumer markets (Dowling and Uncles 1997; Rust, Zeithaml, and Lemon 2000). Past customer behavioral variables (e. g. , relationship age, prior customer share) can also be indicators of past behavioral loyalty, which often translates into future loyalty. Prior research suggests that the type of product purchased in the past is an indicator of future cross-selling potential (e. g. , Kamakura, Ramaswami, and Srivastava 1991). Hypotheses CRPs Relationship marketing theory and customer equity theory posit that customers’ perceptions of the intrinsic quality of the relationship (i. e. , strength of the relationship) and customers’ evaluations of a supplier’s offerings shape customers’ behavior in the relationship (Garbarino and Johnson 1999; Rust, Zeithaml, and Lemon 2000; Woodruff 1997). The most prominent perception representing the strength of the relationship is (affective) commitment (Moorman, Zaltman, and Desphande 1992; Morgan and Hunt 1994). Because satisfaction and payment equity are important constructs with respect to the evaluation of a supplier’s offerings (Bolton and Lemon 1999), I included these three constructs in the model. The two categories of constructs differ in terms of both content and time orientation: Affective commitment is forward looking, whereas satisfaction and payment equity are retrospective evaluations. In the customer equity and relationship marketing literature, other CRPs that are not included in my model are often studied. Trust and brand perceptions are the most prominent of these variables (Morgan and Hunt 1994; Rust, Zeithaml, and Lemon 2000). I did not include brand perceptions because the focus is on current customers. My contention is that the brand is especially significant in attracting new customers. During the relationship, the brand probably influences affective commitment (Bolton, Lemon, and Verhoef 2002). I did not include trust, because trust should be considered merely an antecedent of satisfaction and commitment (Geyskens, Steenkamp, and Kumar 1998). No direct effect on customer behavior should be expected. Affective Commitment Commitment is usually defined as the extent to which an exchange partner desires to continue a valued relationship (Moorman, Zaltman, and Desphande 1992). I focus on the affective component of commitment, that is, the psychological attachment, based on loyalty and affiliation, of one exchange partner to the other (Bhattacharya, Rao, and Glynn 1995; Gundlach, Achrol, and Mentzer 1995). Customer Relationship Management Efforts / 31 Conceptual Model Figure 1 shows the conceptual model. In this model, I consider customer retention and customer share development between two periods (T1 and T0) as the dependent variables, which are affected by CRPs and RMIs. Because I consider customer retention and customer share development as two separate processes, relationship maintenance and relationship development, the underlying hypotheses of the model explicitly predict that different constructs of CRPs, and different RMIs influence customer retention and customer share development. The rationale for this distinction is that a customer’s decision to stay in a relationship with a firm may be different from his or her incremental decision to add or drop existing products. Consistent with this notion, Blattberg, Getz, and Thomas (2001) argue that customer retention is not the same as customer share, because two firms could retain the same customer. Reinartz and Kumar (2003) suggest that relationship duration and customer share should be considered as two separate dimensions of the customer relationship. Bolton, Lemon, and Verhoef (2002) propose that the antecedents of customer retention might be different from the antecedents of cross-buying behavior. I explicitly address these differences in the hypotheses. The inclusion of CRPs as antecedents of retention and customer share development is based on relationship marketing theory, which suggests that CRPs affect behavioral customer loyalty. I included RMIs because a successful cus- TABLE 1 Overview of Studies on Effect of CRPs on Behavioral Loyalty Examples of Studies Study Design Study Context Included Perceptions (Effect) Additional Results/Comments Behavioral Loyalty Measurement Self-Reported Purchase intentions Anderson and Sullivan (1993) Morgan and Hunt (1994) Cross-sectional Cross-sectional Cross-sectional Longitudinal Cross-sectional Cross-sectional Retailing Retailing Car market Theater visitors Satisfaction (+), commitment (–) Satisfaction (+) Commitment (+) Relationship quality (+) Satisfaction (+) Various industries Channels Benefits (+), commitment (+) Service quality (+) Experiment Various industries Satisfaction (+) 32 / Journal of Marketing, October 2003 Zeithaml, Berry, and Parasuraman (1996) Garbarino and Johnson (1999) Mittal, Kumar, and Tsiros (1999) Macintosch and Lockshin (1997) De Wulf, OdekerkenSchroder, and Iacobucci (2001) Bowman and Narayandas (2001) Cross-sectional Grocery brands Gruen, Summers, and Acito (2000) Bolton (1998) Longitudinal Longitudinal Longitudinal Cross-sectional Professional association Telecommunications Credit card Car market Commitment (0) Satisfaction (+) Satisfaction (+), payment equity (+) Satisfaction (+) Bolton, Kannan, and Bramlett (2000) Mittal and Kamakura (2001) Lemon, White, and Winer (2002) Longitudinal Entertainment Satisfaction (0) Longitudinal Longitudinal Longitudinal Telecommunications, entertainment Credit card Financial services Satisfaction (+) Bolton and Lemon (1999) Bolton, Kannan, and Bramlett (2000) Verhoef, Franses, and Hoekstra (2001) Satisfaction (+), payment equity (+) Satisfaction (0), payment equity (0) Effect depends on relationship orientation of customer Customer share Quadratic effect of satisfaction Observed Customer retention and/or relationship duration Service usage Cross-buying Effect of satisfaction enhanced by relationship age Performance differences with other firms are important Effect of satisfaction moderated by consumer characteristics Effect of satisfaction mediated by future expected service usage Payment equity positively affects satisfaction Performance differences with other firms are important Effect of satisfaction and payment equity enhanced by relationship age Effect on customer retention. Given the previous definition of affective commitment, it might be expected that this type of commitment affects customer retention positively. In line with this, researchers who relate commitment to selfreported behavior, such as purchase intentions, usually find that commitment positively affects customer loyalty (e. g. , Garbarino and Johnson 1999; Morgan and Hunt 1994). However, the appearance of such an effect has recently been questioned (Gruen, Summers, and Acito 2000; MacKenzie, Podsakoff, and Ahearne 1998). Despite this, I hypothesize the following: H1: Affective commitment positively affects customer retention. from a particular supplier (Oliver and Winer 1987). This depends on, among other things, the customer’s satisfaction level. As a consequence, customers who are more satisfied are more likely to remain customers. Thus: H3: Satisfaction positively affects customer retention. Effect on customer share development. Relationship marketing theory posits that because affectively committed customers believe they are connected to the firm, they display positive behavior toward the firm. As a consequence, affectively committed customers are less likely to patronize other firms (Dick and Basu 1994; Morgan and Hunt 1994; Sheth and Parvatiyar 1995). In other words, committed customers are more (less) likely to increase (decrease) their customer share for the focal supplier over a period of time. H2: Affective commitment positively affects customer share development over time. Effect on customer share development. Although a positive relationship between satisfaction and customer share has been demonstrated in a single product category (Bowman and Narayandas 2001), this does not necessarily imply that satisfaction also positively affects customer share development for a multiservice provider. A theoretical explanation for the absence of such an effect could be that positive evaluations of currently consumed products or services do not necessarily transfer to other offered products or services. In other words, satisfied customers are not necessarily more likely to purchase additional products or services (Verhoef, Franses, and Hoekstra 2001). Another explanation is that though customer retention relates to the focal supplier alone, customer share development also involves competing suppliers. As a result, development of a customer’s share might be affected more by the actions of competing suppliers than by the focal firm’s prior performance. Thus, I do not expect satisfaction to have a positive effect on customer share development. Payment Equity Payment equity is defined as a customer’s perceived fairness of the price paid for the firm’s products or services (Bolton and Lemon 1999, p. 73) and is closely related to the customer’s price perceptions. Payment equity is mainly affected by the firm’s pricing policy. As a result of its grounding in fairness, a firm’s payment equity also depends on competitors’ pricing polici es and the relative quality of the offered services or products. Effect on customer retention. Higher payment equity (i. e. , price perceptions) leads to greater perceived utility of the purchased products or services (Bolton and Lemon 1999). As a result of this greater perceived utility, customers should be more likely to remain with the firm. Consequently, payment equity should have a positive effect on customer retention. This is consistent with empirical studies that show that payment equity positively affects customer retention (Bolton, Kannan, and Bramlett 2000; Varuki and Colgate 2001). Thus: H4: Payment equity positively affects customer retention. Satisfaction I define satisfaction in this study as the emotional state that occurs as a result of a customer’s interactions with the firm over time (Anderson, Fornell, and Lehmann 1994; Crosby, Evans, and Cowles 1990). Szymanski and Henard’s (2001) meta-analysis shows that satisfaction has a positive impact on self-reported customer loyalty. Despite such positive results in the literature, the link between satisfaction and actual customer loyalty has been questioned (e. . , Jones and Sasser 1995). Researchers have searched for a better understanding of this link and have proposed a nonlinear relationship between satisfaction and customer behavior (e. g. , Anderson and Mittal 2000; Bowman and Narayandas 2001). Other studies have shown tha t relationship age, product usage, variety seeking, switching costs, consumer knowledge, and sociodemographics (e. g. , age, income, gender) moderate the link between satisfaction and customer loyalty (Bolton 1998; Bowman and Narayandas 2001; Capraro, Broniarczyck, and Srivastava 2003; Homburg and Giering 2001; Jones, Mothersbaugh, and Beatty 2001; Mittal and Kamakura 2001). Finally, dynamics during the relationship may also affect this link. Customers update their satisfaction levels using information gathered during new interaction experiences with the firm, and this new information may diminish the effect of prior satisfaction levels (Mazursky and Geva 1989; Mittal, Kumar, and Tsiros 1999). Effect on customer retention. Despite the apparent absence of an empirical link between satisfaction and behavioral customer loyalty, several studies show that satisfaction affects customer retention (Bolton 1998; Bolton, Kannan, and Bramlett 2000). The underlying rationale is that customers aim to maximize the subjective utility they obtain Effect on customer share development. Although I expect payment equity to have a positive effect on customer retention, I do not necessarily expect this to be true for customer share development. There are two reasons payment equity may have no effect on customer share development. First, literature on price perceptions suggests that customers with higher price perceptions are more likely to search for better prices (Lichtenstein, Ridgway, and Netemeyer 1993). Intuitively, the suggestion that such customers are less loyal makes sense. For example, customers of discounters (with high scores on price perceptions) are known to visit the greatest number of stores in their search for the best bargain. Customer Relationship Management Efforts / 33 TABLE 2 Studies on Effect of RMIs on Behavioral Loyalty Study Aggregated purchase shares Customer share Cross-sectional survey, perceptions on direct mail use — Aggregated panel data Panel design Loyalty Measure Study Design Study Context Grocery brands Retailing Results Short-term positive effect on purchase rates No effect 34 / Journal of Marketing, October 2003 No empirical data Aggregated penetration, average purchase frequency, customer share, sole buyers Purchase intentions — Retailing — Cross-sectional survey data, perceptions on loyalty program use Longitudinal Cross-sectional survey data, perceptions on preferential treatment programs Airlines Positive effect Customer retention, service usage Customer share Credit card Retailing No effect RMI Direct mail Bawa and Shoemaker (1987) De Wulf, Odekerken-Schroder, and Iacobucci (2001) Loyalty programs Dowling and Uncles (1997) Sharp and Sharp (1997) No convincing effect of loyalty programs Rust, Zeithaml, and Lemon (2000) Bolton, Kannan, and Bramlett (2000) Positive effect on retention and service usage De Wulf, Odekerken-Schroder, and Iacobucci (2001) FIGURE 1 Conceptual Model CRPs Satisfaction H3 H4 Payment equity H1 H2 Affective commitment ? Customer share T 1 T0 Customer retention T 1 T0 H6a H6b H5 Loyalty program RMIs Direct mailings Control Variables Customer share T0 Relationship age T0 Type of service purchased T0 According to this reasoning, customers with better price perceptions are more likely to decrease customer share over time. Second, as is satisfaction, a customer’s payment equity is based on the customer’s awareness of the prices of services or products purchased from the focal firm in the past (Bolton, Lemon, and Verhoef 2002). However, the prices of additional services or products from the focal supplier might be different from the currently purchased services or products. Therefore, a high payment equity score may not indicate that the customer will purchase other products or services from the same supplier. As a consequence, I do not expect payment equity to affect customer share development. RMIs Bhattacharya and Bolton (2000) suggest that RMIs are a subset of other marketing instruments that are specifically aimed at facilitating the relationship, and they distinguish between loyalty or reward programs and tailored promotions. In addition, RMIs can be classified according to Berry’s (1995) first two levels of relationship marketing. At the first level (Type I), firms use economic incentives, such as rewards and pricing discounts, to develop the relationship. At the second level (Type II), instruments include more social attributes. By using Type II instruments, firms attempt to give the customer relationship a personal touch. In this study, I focus on two specific Type I RMIs: direct mailings and loyalty programs. Direct mailings usually are personally customized offers on products or services that the customer currently does not purchase. In most cases, price discounts or other sales promotions (e. g. , gadgets) are used to entice the customer to buy. I focus on direct mailings that are a â€Å"call to action† rather than only a reinforcing mechanism for the relationship (e. g. , thank-you letters). The loyalty program I include in the study is a reward program that provides price discounts based on the number of products or services purchased and the length of the relationship. Direct Mailings Direct mailings have some unique characteristics: enablement of personalized offers, no direct competition for the attention of the customer from other advertisements, and a capacity to involve the respondent (Roberts and Berger 1999). Because direct mailings focus on creating additional sales, I do not expect them to influence customer retention. Moreover, the data do not enable me to relate direct mailings to customer retention. Effect on customer share development. There are several theoretical reasons direct mailings should positively influence customer share development. First, direct mailings can create interest in a (new) service and thereby lead to a final purchase (Roberts and Berger 1999). Second, the personalization afforded by direct mailings may increase perceived relationship quality, because customers are approached with individualized communications that appeal to their specific needs and desired manner of fulfilling them (De Wulf, Odekerken-Schroder, and Iacobucci 2001; Hoekstra, Leeflang, and Wittink 1999). Third, according to the sales promotions literature, the short-term rewards (i. e. , price discounts) offered by direct mailings may motivate customers to purchase additional services and thus increase customer share. In support of this claim, Bawa and Shoemaker (1987) report short-term gains in redemption rates of direct mail coupons. I hypothesize the following: H5: Direct mailings positively affect customer share development over time. Loyalty Programs Effect on customer retention and customer share development. There are several theoretical reasons the rewardbased loyalty program being studied should positively affect both customer retention and customer share development. First, psychological investigations show that rewards can be highly motivating (Latham and Locke 1991). Research also shows that people possess a strong drive to behave in whatCustomer Relationship Management Efforts / 35 ever manner necessary to achieve future rewards (Nicholls 1989). According to Roehm, Pullins, and Roehm (2002, p. 203), it is reasonable to assume that during participation in a loyalty program, a customer might be motivated by program incentives to purchase the program sponsor’s brand repeatedly. Second, because the program’s reward structure usually depends on prior customer behavior, loyalty programs can provide barriers to customers’ switching to another supplier. For example, when the reward structure depends on the length of the relationship, customers are less likely to switch (because of a time lag before the same level of rewards can be received from another supplier). It is well known that switching costs are an important antecedent of customer loyalty (Dick and Basu 1994; Klemperer 1995). Despite the theoretical arguments in favor of the positive effect of loyalty programs on customer retention and customer share development, several researchers have questioned this effect (e. g. , Dowling and Uncles 1997; Sharp and Sharp 1997). In contrast, Bolton, Kannan, and Bramlett (2000) and Rust, Zeithaml, and Lemon (2000) show that loyalty programs have a significant, positive effect on customer retention and/or service usage. In this study, I build on the theoretical argument in favor of the positive effect that loyalty programs have on customer retention and customer share development. H6: Loyalty program membership positively affects (a) customer retention and (b) customer share development. products, and customer characteristics. In the second (T1) survey, I collected data on customer ownership of various insurance products. Although the company whose data I used offers other products, such as loans, I limited the study to the category of insurance products. The rationale for this limitation is that customers usually buy each type of insurance product from a single insurance carrier (i. e. insurance type X [life insurance] from insurance carrier Y [i. e. , Allianz Life Company]), but this does not necessarily hold for other financial products or services. For example, it is well known that many customers have savings accounts at several financial institutions. Moreover, the insurance market is the most important market for this company in terms of the number of customers and customer turnover (approximately 90%). As a result of this choice, the sample is restricted to those customers who purchase insurance products only from the company. This resulted in a usable sample size of 1677 customers for the first measurement (T0) and 918 for the second measurement (T1). Contents of the Company Customer Database The company’s customer database provided data on the past behavior of individual customers and the company RMIs directed at individual customers. The past customer behavior data cover two periods. The first period starts at the beginning of a relationship between the company and the customer and ends at T0 (this period differs among customers). The data on past customer behavior included variables such as number of insurance policies purchased, type of insurance policies purchased, and relationship length. The second period covers the interval between T0 and T1. For this period, the database provided data about which customers left the company and the number of company insurance policies a customer owned at T1. The company’s customer database contains the following information on RMIs: loyalty program membership at T0 and the number of direct mailings sent between T0 and T1. Every customer who purchases one or more financial Research Methodology Research Design I combined survey data from customers of a Dutch financial services company with data from that company’s customer database. I used a panel design, displayed in Figure 2, to collect the data. I collected the survey data at two points in time: T0 and T1. I used the first (T0) survey to measure CRPs of the company, customer ownership of various insurance FIGURE 2 Panel Design Data from Customer Database Start of Relationship T 0 (Survey 1 Among Customers) T 1 (Survey 2 Among Customers Interviewed in Survey 1) 6 / Journal of Marketing, October 2003 services from the company can become a member of the loyalty program (an opt-in program). At the end of each year, the program gives customers a monetary reward based on the num ber of services purchased and the age of the relationship. Because the company uses regression-type models to select the customers with the highest probability of responding to direct mailings, the number of direct mailings sent differs among customers. Customer Survey Data Collection At T0, customer survey data were collected by telephone from a random sample of 6525 customers of the company. A quota sampling approach was used to obtain a representative sample. I received data from 2300 customers (35% response rate). After those responses with too many missing values were deleted, a sample size of 1986 customers remained. At T1, I again collected data from those customers, except for those who left the company between T0 and T1. In the second data collection effort, 1128 customers were willing to cooperate (65% response rate). To assess nonresponse bias at T1, I tested whether respondents and nonrespondents differed significantly with respect to customer share at T0. A ttest does not reveal a significant difference (p = . 36). Thus, I conclude that there is no nonresponse bias. Measurement of CRPs For the measurement of CRPs (i. e. affective commitment, satisfaction, and payment equity), I adapted existing scales to fit the context of financial services. For the affective commitment scale, I adapted items from the studies of Anderson and Weitz (1992), Garbarino and Johnson (1999), and Kumar, Scheer, and Steenkamp (1995). To measure satisfac tion, I adapted Singh’s (1990) scale and added four new items. Finally, I based the payment equity scale on items adapted from Bolton and Lemon’s (1999) and Singh’s (1990) studies. To assess construct validity and clarify wording, the original scales were tested by a group of 12 marketing academics and 3 marketing practitioners familiar with customer relationships. Subsequently, the scales were tested by a random sample of 200 customers of the company. On the basis of interitem correlations, item-to-total correlations, coefficient alpha, and exploratory and confirmatory factor analysis, I reduced the set of items in each scale. 1 1I follow Steenkamp and van Trijp’s (1991) proposed method, using exploratory factor analysis and then confirmatory factor analysis to validate marketing constructs. Validation of CRPs The final measures are reported in the Appendix. The scales for commitment and satisfaction have reasonable coefficient alphas. For payment equity, I report a correlation coefficient of . 49, which is not considerably high. 2 However, note that the reported composite reliabilities of all scales are sufficient (Bagozzi and Yi 1988). I applied confirmatory factor analysis in Lisrel 83 to further assess the quality of the measures (Joreskog and Sorbom 1993), and I achieved the following model fit: ? 2 = 217. 4 (degrees of freedom [d. f. ]) = 51, p . 10; ? = . 03, p gt; . 10; customer share development: ? = . 01, p gt; . 10; ? = –. 01, p gt; . 10). In addition, I reestimated both models, leaving out satisfaction and payment equity. The parameter estimates for commitment were significant in both models (customer retention: ? = . 17, p lt; . 05; customer share development: ? = . 02, p lt; . 01). Finally, I estimated a regression model in which I related satisfaction and payment equity to commitment. The parameters of both satisfaction and payment equity were positive and significant (? = . 61, p lt; . 01; ? = . 09, p

Business Research and Communication

Question: Discuss about theBusiness Research and Communication. Answer: Introduction Labels can be illusory, therefore the people requires to cautious about the labelling of the products (Action to reduce animal testing, 2006). No precise rules and legislationsexist on the subject of cruelty-free labelling of the goods; consequently organisations can obtain independence in their resting purpose. At the same time it is doubtful that a corporation would placedeliberatelyfake information concerning its animal-testing tradition on theirgoods, declarations on the labels can be deceptive and not completelyuseful and enlightening.To make a better product market and for develop effective research and development of their products most of the company utilizes the animal for their testing purpose. In most of the cases it can be observed that food product, drug product and chemical production companies mostly utilize the animals for their testing purposes(Abbott, 2009). Due to the lack of rule and regulation in the cruelty free labelling the organisation constantly enhances the ir research and development of their products depending on the animal testing procedure. Animal testing can be defined as an animal research or testing within vivo testing methods. To control over the different variables which may affect the biological and behaviour system under this research this vivo testing has been obtained for non human animals. Mostly it can be observed that the animal testing is took place in the medical schools, universities, pharmaceutical companies etc(Coster, 2011). To research on the matter of cosmetics, defence, breeding and toxicology the researcher often uses the animal testing process in their research. According to the market research it can be observed that almost 93% of research on this sector is used different species of animal in their research process in EU. In US there is no such relevant legislation and rules against this matter. Willingness to pay (WTP) is defined as the utmost quantity a person is eager to give up obtaining a good or keep away from somewhat unwanted. The value of any products deal will therefore be any point among a purchaser's eagerness to disburse and a vendor's eagerness to admit. Main Body Analysis Toxicity experiments to evaluate the security of items and chemicals were produced in the mid of twentieth century. To calculate and measure the toxic part within the product and to analyse the harsh chemical effects on the people the researcher most of the time incorporates their research on eyes or in the skin of rabbit or other animals (the scandalous Draize test), and lethal dose (LD50) tests that decide poisonous quality by the dose of a substance (Hajar, 2011). These primordial creature test techniques are, unfortunately, still being used these days. Numerous researchers keep on relying on creature tests, and administrative offices still command information gathered from creature tests, in substantial part since that is the thing that custom and ebb and flow laws direct. As an outcome, the lives of a huge number of our kindred animals keep on being relinquished, and our own particular security traded off. The poisonous quality testing for some writes of items still includes testing on animals. Items are tried on creatures for three reasons: security (this slot in right item identification), viability and obligation. Numerous things acquired and utilized by purchasers consistently, for example, family chemicals, beautifying agents, medications and pesticides, are subjected to government controls requiring that they "protected" for people, creatures and the earth(Hester and Harrison, 2006). Makers are in charge of submitting security test information to organizations, and this regularly includes directing harmfulness tests on the items and/or their fixings before they enter the commercial centre. Administrative offices figure out if the information is adequate for naming and showcasing the item. Numerous items are tried for security to meet lawful prerequisites to distinguish potential perils to people, creatures and nature. Indeed, even non-directed items, for example, Drugs proposed f or human or creature use are furthermore tried for adequacy (i.e., viability in treating a condition or illness). This testing ordinarily includes creature models also. Beauty care products are normally tested by the animals for wellbeing with the end goal of risk. Organizations would prefer not to showcase an item that could bring about lawful cases (Judson, 2006). For medications, office endorsement to lead human testing in clinical trials commonly requires an organization to present the outcomes according to the animal research study information and toxicity information. In US there are some regulatory agency those who purview the matter to protection measurement based on the toxicity tests. According to the Food and Drug Administration it can be assessed thatproducts like drugs, medical devices, food additives, vaccines are regulated(Maguire and Novik, 2010). On the other hand, according to the environmental protection agency of US products like anti microbial cleanser, chemical and chemical ingredients in industry are regulated. Consumer Product Safety Commission of US also regulated chemical contains household and consumer products. Due to the use of excessive test on animals it may reduce the customers buying behaviour due to the cruelty issues. By maintain the cruelty free environment within their research and development process an organisation can attract more customersby sustainable way in their business process. The cruelty free test is considered as a test by which the animal did not get any kind of pain or harm at the time of research process. Due to the different research and development process it can be stated that millions of animals were killed by the researcher in every year. To promote the cruelty free campaign programme and attract more customers for buying products in the year 1991 European Centre for the Validation and alternative methods had been established. The Draize test intended to skin irritancy that was initially presented in the year 1944. It has been utilized to gauge the incendiary reaction delivered at that time, a test material is connected to the sheared and rubbed skin of a gathering of animals, and might bring about extraordinary agony, smouldering and tingling(Reinhardt, 1994). The uplifting news is that the utilization of this testing technique has been to a great extent supplanted with accepted option strategies. Skin is scraped by immovably squeezing sticky tape onto the creature's body and rapidly stripping it off, and is rehashed until a few layers of skin have been evacuated. The Environmental Protection Agency's Office of Pesticide Programs, for instance, depends on information from the Local Lymph Node Assay. An additional conventional animal poisonous quality test is named as LD50 test, which remains for the deadly measurements of a given test substance in half of the tests animal populace. The experiment, performed mostly on rats mice, is regularly used to assess the human wellbeing aims of intense oral systemic harmfulness where animal subjects are coercively fed oral dosages of the substance being tried(Russell, 2013). Numerous researchers declared that the oral LD50 experiment has little pertinence to assessing the human wellbeing of stuff, and a few offices and worldwide associations have pulled back their necessity for this kind of test information. This oral systemic test is utilized as a general marker of the general relative poisonous quality of a substance. There are several problems regarding the animal tests. Due to the several ethical concern and rising people conflicts regarding the animal testing the researcher has discover some fresh and new strategies in their research process by which they can easily obtained their desired outcomes in a proper and easier way. Experiments in animals body are not generally prescient of human wellbeing impacts. The best experiments for human poisonous quality would be directed utilizing people that are totally dishonest(Sepahban, n.d.). In any case, science has significantly progressed since the advancement of the animal tests that are still being used in the present day. Cell society, sub-atomic and computation strategies are at present very much created experimental instruments. Poisonous quality testing, in any case, has not had the criticalness and backing of government financing programs that ailment based exploration has appreciated, in spite of the fact that this appears to have enhanced in the course of recent years. Truth be told, it is assessed that there is a build-up of over than 80,000 chemicals for which possible toxicity is generally difficult to understand(Watson, 2009). Numerous chemicals utilized as a part of items today have not been tried, so their wellbeing is to great extent obscure and new chemicals and items are entering the commercial centre at a continually expanding pace(Welsh, 1990). The animal experiments are moderate and costly, and wellbeing testing utilizing existing strategies can't stay aware of the interest. Gap in Literature Apart from this literature section it can be said that, the researcher find some additional recommendation about this animal testing and its influence on the consumer behaviour. After analysis of this literature section the researcher identifies that there are some gaps in the research hypothesis by which the research cannot make a successful outcome in the study process. To maintain an effective outcome in the research the researcher recommended that, apart from the alternative use of animal testing the researcher or research and development team of every organisation could test their research on food animals. To the large number of production and breeding for consumption it cannot affect the ecological system of the world. By testing the whole research on the food animals could mitigate the problem regarding the animal testing issues and cruelty free legal policies. Conclusion According to the above study it can be depicted that consumer behaviour of the buyer is very much depends on the label against animal testing. Development toward displacing the LD50 assessment with option non-animal strategies has been continuous, yet the test includes poisonous quality to the entire living being, and is along these lines organically. By obtaining different tools and techniques in research development and testing purpose instead of animal testing would attract more customers for buying the product safely and securely. References Abbott, A. (2009). The lowdown on animal testing for cosmetics.Nature. Action to reduce animal testing.(2006). Veterinary Record, 159(2), pp.31-31. Coster, P. (2011).The debate about animal testing. New York, NY: Rosen Central. Hajar, R. (2011). Alternative to animal testing.Heart Views, 12(1), p.39. Hajar, R. (2011). Animal testing and medicine.Heart Views, 12(1), p.42. Hayhurst, C. (2000). Animal testing. New York: Rosen Pub. Group. Hester, R. and Harrison, R. (2006).Alternatives to animal testing. Cambridge: Royal Society of Chemistry. Judson, K. (2006). Animal testing. New York: Marshall Cavendish Benchmark. Maguire, T. and Novik, E. (2010).Methods in bioengineering. Boston, Mass.: Artech House. Reinhardt, C. (1994). Alternatives to animal testing.Weinheim: VCH. Russell, J. (2013). Animal testing. [Place of publication not identified]: Book On Demand Ltd. Sepahban, L. (n.d.). Animal testing. Watson, S. (2009). Animal testing. New York: Rosen Pub. Welsh, H. (1990). Animal testing and consumer products. Washington, DC: Investor Responsibility Research Center.