A dynamic model of customer loyalty an empirical

A dynamic model of customer loyalty: an empirical evidence M.Costabile *, M.A.Raimondo**, G.Miceli** Affiliation: * SDA BOCCONI, Milano; Università degli Studi della Calabria – Campus di Arcavacata ** Università degli Studi della Calabria – Campus di Arcavacata (Track indication: Relationship Marketing) * Università degli Studi della Calabria – Campus di Arcavacata, Rende (CS) – 87036 – Italy Phone and Fax: +0984/492269; E-mail: mcostabile@unical.it A dynamic model of customer loyalty: an empirical evidence Abstract Many studies have focused the attention on defining, operationalizing and measuring the market relationship construct According to these studies there are cognitive, affective and behavioral constructs (satisfaction, trust, commitment, loyalty, etc.) that qualify several types of relationship during different stages of the life cycle, starting from customer satisfaction and all the way through to customer loyalty and partnership in the ideal-typical path This paper aims to demonstrate that a dynamic model of customer loyalty can be conceptually defined and empirically tested In applying a structural equation model, the authors show evidence of the multidimensionality of customer loyalty, obtaining some findings about the effect of time on the loyalty construct dimensions Search Keywords: relationship, loyalty, trust, LISREL Introduction Marketing scholars have extensively analyzed the post-purchase consumer behavior (or customer behavior) and the customer relationship development, both in the business to business and in the business to consumer field Nevertheless a conceptual model widely accepted and empirically tested on how a relationship evolves from transaction up to loyalty is not available, yet On the ground of the customer satisfaction and relationship marketing literature, this paper describes a model on the customer loyalty development Loyalty is considered a multidimensional construct that emerges dynamically as the optimal stage evolution of the relationship between a customer and a firm or a brand The model is empirically tested, and some interesting evidences are given, thanks to a structural equation models application, even if a longitudinal analysis, appropriate to measure the dynamic of the construct, is not still available (a panel research is running) The findings confirm that customer loyalty is a multidimensional construct, and each of its dimensions have a different role over the time The literature on the customer buying behaviour and loyalty Customer satisfaction theories are based on the social and experimental psychology studies that discovered the foundation of the ‘confirmation/disconfirmation’ paradigm useful to explain the perception of satisfaction and the link between satisfaction and trust (Bitner, 1995; Costabile, 1998) This connection is allowed for the interpretation of the dynamics of market relationships, and thus for the origin of trust and loyalty, both grounded on the experience of satisfaction accumulated over time Since then many scholars analyzed the determinants of satisfaction, also attempting to understand the variables that intervene between the perception of satisfaction and the choice of repurchasing a brand, or a set of brands (Yi, 1990, Oliver, 1997) To sum up, it is possible to claim that there are clear casual connections between trust and repurchase decisions, and under some conditions, loyalty (Oliver, 1999) Grounding on the psychology of interpersonal relationships and on the social network theory, relationship marketing scholars have investigated exchange processes in dyadic and network contexts, showing the central role of trust The fundamental contribution of Dwyer, Schurr and Oh (1987) identified trust as the critical factor for moving from discrete market transactions towards exchange relationships Other specific researches have given evidence of the great importance of “relational constructs”; among others, commitment – defined by Morgan and Hunt (1994) as the “durable desire to maintain an important relationship” – and equity – defined as “the perception of reciprocity in the relationship with the seller” (Costabile, 2000) The dynamic perspective in the analysis of the customer-supplier relationship was proposed by Ford (1980) Other relevant contributions came from Dwyer, Schurr and Oh (1987), Wilson (1995) and Iacobucci and Zerrillo (1997) To sum up, customer behavior literature and relationship marketing literature supply a wide and solid background to analyze the relational continuum and the variables that play a role on the customer perceptions, attitudes, beliefs and behaviors The purpose of this paper is to propose and test a dynamic model of customer loyalty The model was developed thanks to the above mentioned literature background and was aimed to explain the customer growing involvement in the relationship The dynamic model of customer loyalty The dynamic model of customer loyalty (Costabile, 2000) proposed in this paper is shown by Figure LOYALTY tn DYADIC VALUE ANALYSIS REPURCHASE TRUST SATISFACTION t1 t0 t2, 3, … EXPECTED VALUE MENTAL LOYALTY PURCHASE PERCEIVED VALUE tm BEHAVIOURAL LOYALTY MONADIC VALUE ANALYSIS Figure The dynamic model of customer loyalty The model concerns the following stages: the “satisfaction to trust” stage: in exchange processes, when perceived value, in the buyer’s perspective, meets or exceeds the expected value satisfaction is generated; the flows of satisfaction enhance the perception of seller’s reliability, increasing the stock of positive attitude defined as trust and allowing the development of relationship towards loyalty (Morgan e Hunt, 1994); • the “trust to behavioral loyalty” stage: the growth in the stock of trust has a positive influence on the customer intention to repurchase (Boulding, Kalra, Staelin and Zeithmal, 1993), in particular thanks to the opportunities of economies on cognitive, emotional, operational and structural costs (Costabile, 2000); considering this stage, in a dynamic perspective, these repurchase savings generate a behavioral loyalty, dependant on competitive and technological pressures that operate on customer involvement; • the “mental loyalty” stage: the behavioral loyalty is not a never ending type of loyalty During the life cycle some kind of “conflict” could emerge (Iacobucci and Zerrillo, 1997), in the shape of a new comparison between the value offered and experienced by the firm and the value proposition advanced by its competitors (Woodruff and Gardial, 1996) The positive resolution of the conflict based on monadic value analysis – regarding the ratio “customer benefits/customer sacrifices” compared with the same ratio offered by competitors – pushes customers towards mental loyalty, defined as a strong belief in the seller’s capability in offering always “the best value”, in order to satisfying the customer requirements over time The mentally loyal customer is a very strong committed one He will generate positive word-of-mouth and he will be unlikely to switch to another seller; • • the “customer loyalty” stage: a long time customer has enough information to compare the perceived value he has received from the relationship and the value that the longevity of the latter has created for the seller Both the common sense belief that loyalty over time creates extra-value for the firm, and the learning opportunities about the products, the firm and its economics that are given to the customer by a long relationship push the customer to check the perception of equity of the relationship At this advanced stage of the relationship, when the customer knows very well the firm’s behavior, a dyadic value analysis becomes the central focus of his evaluation: a second type of conflict arises with a focus on the evaluation of the supplier “fairness” (versus “opportunism”) The positive resolution of this second conflict – the belief that the supplier adopted a fair behavior over the time – is determinant to reach the optimal stage of the relational continuum: the customer loyalty A loyal customer is a collaborative one, and his behavior will be aimed to co-operate in building a long lasting relationship, also when contextual or competitive variables plays against the loyalty option (proactive loyalty - Oliver, 1997 and 1999) The research design To empirically test the model a structural equation model has been applied The different constructs defined by the model have been operationalized and measured realizing a survey with two distinct groups of Italian customers of mobile telephone services These two groups differ by the longevity of their relationship with the supplier The “elders” are customers that repurchase from their principal provider at least since three years; the “youngs” are customers that repurchase from their principal provider since less than three years The cut off in the duration of the relationship has been defined analyzing the data, having found a median value of three years in the time distribution concerning the relationship length The aggregate sample has been created adopting a criterion based on convenience Collection of data has been carried out in two towns, Milan – in Northern of Italy – and Cosenza – in Southern of Italy – The purpose of this research design was to test the main model hypotheses defined as follows: HP1 – confirmation or positive disconfirmation of expectations has a positive influence on satisfaction; HP2 - emotions have a positive influence on satisfaction; HP3 - satisfaction has a positive influence on trust; HP4 - trust has a positive influence on customer loyalty with a greater intensity in the early stages of relationship life cycle (therefore in the “youngs”); HP5 - trust has a positive influence on mental loyalty; HP6 - mental loyalty has a positive influence on customer loyalty with a greater intensity in the late stages (therefore in the “elders”); HP7 - the buyer’s perception of equity has a positive influence on customer loyalty with a greater intensity in the late stages (therefore in the “elders”); HP8 - customer’s sacrifices and seller’s sacrifices (both in the customer’s perceptions) have a negative influence on buyer’s perception of equity; HP9 - customer’s benefits and seller’s benefits (both in the customer’s perceptions) have a positive influence on buyer’s perception of equity; For some of the hypotheses (HP4, HP6 e HP7) a longitudinal study would be appropriate A cross sectional research does not give the opportunity to verify if the differential intensity of some connections was already high when the “elder” customers were “youngs”, and viceversa (“young” customers will show the same intensity of the hypothesized connections when they will become “elders”?) Nevertheless a longitudinal study require an early test of the model aiming to verify if the loyalty construct is a multidimensional one and if there are significant differences over the time Then it will be possible to design a longitudinal study to isolate the effect of time By the way, an exploratory factor analysis – explained variance = 55.46%; sig = 000 – has been run to purify measurement scales, built both on the ground of a literature review and on the accomplishment of some qualitative interviews to generate contextual items (i.e variables affecting satisfaction towards mobile phone services) Promax rotation criterion shows a factorial structure with no cross-loadings and with significant loadings on the hypothesized latent factors; in a comprehensive view, very good levels of discriminant and convergent validity are obtained Satisfaction has been measured with an overall single item because of the bad factorial performance of the scale proposed by Oliver (1993) The satisfaction item hasn’t any significant loading on the other constructs Cronbach alphas grater than 71 have given evidence of reliability in all measurement scales Grounding on Bagozzi and Heatherton (1994) and considering the complexity of the model it has been applied a partial aggregation approach on observed variables: eight of ten multiple-items measurement scales have been synthesized into two indicators - our Y and X in our structural equation model tested - by a process based on simple means on two, three or four observed variables Constructs have been operationalized on the following basis: • Customer Loyalty (CL): two indicators (Y8 and Y9) are the output of the aggregation process of the items regarding repurchase intention, word-of-mouth, spontaneous collaboration, positive answer to requested collaboration, and two brand identification items; this construction is based on a multidimensional definition of loyalty (Morgan and Hunt, 1994; Dwyer, Schurr and Oh, 1987; Wilson, 1995; Costabile, 2000) • Customer Satisfaction (SA): grounding on Oliver (1993) we have operationalized Customer Satisfaction – as a per-se construct – distinguishing it from its antecedents, from disconfirmation of expectations and from emotions; as above mentioned given the bad factorial performance of items used by Oliver, Customer Satisfaction has been measured with a single overall item (Y1) • Trust(TR): five items expressing reliability and trustworthiness of the supplier (Morgan and Hunt, 1994; Smith and Barclay, 1997) have been aggregated on two indicators (Y2 and Y3) • Mental Loyalty (ML): three items concerning the provider capability in offering good prices, promotions, and new value added services over time have been aggregated on two indicators (Y4 and Y5) • Perception of Equity (EP): eight items concerning reciprocity in benefits, revenues and sacrifices, in the customer perspective (Oliver e Swan, 1989), have been aggregated on two indicators (Y6 and Y7) • Disconfirmation (DI): three items regarding the provider capability in confirming expectations about good prices, promotions and new value added services (Oliver, 1980 and 1997) have been aggregated on two indicators (X1 and X2) • Emotions (EM): seven semantic-differential items concerning emotions that Oliver (1993 and 1997) found as good antecedents of satisfaction and that have been confirmed in qualitative interviews have been aggregated on two two indicators (X3 and X4) • Customer Sacrifices (CS): two items (X5 and X6) have been used to operationalize the information costs and the competitor evaluation costs • Customer Benefits (CB): six items regarding the level of perceived customer care, the completeness of information, the goodness of communication, the problem-solving capability, the readiness of innovations and the attention paid to the customer requirements have been aggregated on two indicators (X and X8) • Supplier Sacrifices (PS): three items concerning the provider’s investments in advertising, promotions and marketing research have been aggregated on two indicators (X9 and X10) • Supplier Benefits (PB): two items (X11 and X12) have been used to operationalize the greater quantity of purchased services, and the positive worth-of-mouth stemming from long- term relationships with the firm Research findings Results of running LISREL 8.50 syntax are shown in Table In both analyses, model fit was acceptable, with better values in the “elders” group This means that the model proposed is a good approximation to the data, even if some improvements are further possible Hypotheses are not completely confirmed Some structural parameters are not statistically significant, this is probably, the expression of a lack in the measurement process, more than in the specification of the model, given the necessary hard purification of measurement scales Nevertheless, the central hypotheses of the model are confirmed in direction, sign and strength; these are the hypotheses concerning the role of trust, monadic value and dyadic value in determining customer loyalty The findings support the stronger influence of trust on customer loyalty during the early stages of the relationship than in the late ones (Table 1: TR€CL); and the greater impact of monadic and dyadic value during the advanced stages of the relationship life cycle than in the initial one (Table 1: ML€CL and EP€CL) The causal path from mental loyalty and from equity perception to customer loyalty are not significant in “youngs” group - the null hypothesis that the relative parameters are equal to zero can not be rejected -: this could be explained considering that in the early stage of the relationship the customer is not self-confident in giving evaluations on monadic value and on dyadic value In spite of a good factorial performance, emotions have not been confirmed as a significant antecedent of customer satisfaction Table Results of LISREL application Paths DI € EM € SA € TR € TR € ML € EQ € CS € PS € CB € PB € SA SA TR CL ML CL CL EQ EQ EQ EQ “Elders” (N=246) “Youngs” (N=219) χ2 (158 df) = 249.85 χ2 (158 df) = 309.87 NFI = 92 NNFI = 96 CFI = 97 NFI = 88 NNFI = 91 CFI = 94 GFI=.91 AGFI= 87 RMR = 06 GFI=.88 AGFI= 82 RMR = 08 Structural parameters 93* 07 (ns) 94* 55* 59* 20* 28* -.12*** -.12 (ns) 62* 14 (ns) Hypotheses HP1 supported HP2 not supported HP3 supported HP4 supported HP5 supported HP6 supported HP7 supported HP8 partially supported Structural parameters 98* - 08 (ns) 94* 67* 62* 11 (ns) 12 (ns) -.05 (ns) 17 (ns) 30* 19** Hypotheses HP1 supported HP2 not supported HP3 supported HP4 supported HP5 supported HP6 supported HP7 supported HP8 not supported HP9 partially HP9 supported supported ns = not significant; * significant at p