Journal of Strategic Marketing ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/rjsm20 Rollover service contracts: the influences of perceived value, convenience, confusion and switching costs on consumer satisfaction and service loyalty Muhammad Mohsin Butt, Stephen Wilkins, Joe Hazzam & Ben Marder To cite this article: Muhammad Mohsin Butt, Stephen Wilkins, Joe Hazzam & Ben Marder (2024) Rollover service contracts: the influences of perceived value, convenience, confusion and switching costs on consumer satisfaction and service loyalty, Journal of Strategic Marketing, 32:8, 1336-1356, DOI: 10.1080/0965254X.2024.2319831 To link to this article: https://doi.org/10.1080/0965254X.2024.2319831 View supplementary material Published online: 13 Mar 2024. Submit your article to this journal Article views: 298 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=rjsm20 JOURNAL OF STRATEGIC MARKETING 2024, VOL. 32, NO. 8, 1336–1356 https://doi.org/10.1080/0965254X.2024.2319831 Rollover service contracts: the influences of perceived value, convenience, confusion and switching costs on consumer satisfaction and service loyalty Muhammad Mohsin Butt a , Stephen Wilkins b , Joe Hazzam c and Ben Marder d a Department of Marketing, Faculty of Business Administration, Institute of Business Administration Karachi, Karachi, Pakistan; bFaculty of Business and Law, The British University in Dubai, Dubai, United Arab Emirates; c Staffordshire Business School, Staffordshire University, Stoke-on-Trent, UK; dUniversity of Edinburgh Business School, The University of Edinburgh, Edinburgh, UK ABSTRACT ARTICLE HISTORY Rollover contracts are agreements that automatically renew, or ‘roll over’, when the contracted term is completed, unless the customer has previously given notice to terminate the agreement. Although ubiquitous, academic examination of this contract model is scarce, and it is not known the extent to which rollover contracts influence consumer satisfaction and individuals’ subsequent behaviors. A conceptual model was developed and tested using structural equation modeling. The data were obtained from a survey of 994 service consumers in the United States. Perceived value emerged as the strongest enabler of consumer satisfaction with rollover con­ tracts, followed by convenience, while consumer confusion – e.g. caused by lengthy and complex contracts – has the strongest negative effect on consumer satisfaction. The strongest relation­ ships in our model are between satisfaction and staying intentions, word of mouth, and future rollover acceptance with other firms and products. The paper presents important theoretical contributions and managerial implications. Received 1 February 2022 Accepted 12 February 2024 KEYWORDS Rollover contracts; service loyalty; trust; competitor homogeneity; consumer inertia Introduction Service agreements that automatically roll over from one period to another are common in service markets. Such contracts can be found for cell phone services; broadband; software licenses; insurance; gym and sports club memberships; home security; and home maintenance services. Unless a customer has given notice to terminate their agreement, upon completion of the contracted term, the contract automatically renews or ‘rolls over’ for a further fixed term (typically 12 months). Previous research on service contracts has been undertaken predomi­ nantly in the domains of law and consumer economics, but the psychological dimension of buyer decision making has received surprisingly little attention from marketers. In addition to filling a gap in the marketing literature, this paper addresses recent calls from practitioners and journal editors for more research that is relevant, important and useful in informing business practice (Jaakkola & Vargo, 2021; Jedidi et al., 2021). CONTACT Stephen Wilkins stephen.wilkins@buid.ac.ae Supplemental data for this article can be accessed online at https://doi.org/10.1080/0965254X.2024.2319831 © 2024 Informa UK Limited, trading as Taylor & Francis Group JOURNAL OF STRATEGIC MARKETING 1337 Contract renewals generate continued revenues for service providers, and due to the costs of advertising, vetting applicants, setting up new accounts and initiating new customers, it is far more profitable to retain existing customers, avoiding churn, than acquire new customers (Wangenheim et al., 2017). Nonetheless, exist­ ing literature provides little understanding about what factors determine customer satisfaction with their existing rollover contracts and its attitudinal and behavioral outcomes. Therefore, it is critical for firms to understand the reasons why con­ sumers choose to rollover their contract, or to instead terminate their service agreement. Consumer satisfaction is generally assumed to be an essential antecedent of behavioral loyalty in service contexts, yet it is known that satisfied consumers sometimes switch provider, while dissatisfied consumers may continue making repeat purchases, perhaps due to switching costs or consumer inertia (Curasi & Kennedy, 2002). Thus, this research seeks to better understand the antecedents of consumer satisfaction with their existing rollover contracts, and the extent to which these antecedents and consumer satisfaction influence consumers’ post consumption attitudes and behaviors. Our conceptual model is broadly anchored on social exchange theory (J. J. Lee et al., 2014), while the theory of planned behavior (Ajzen, 1985) and nudge theory (Thaler & Sunstein, 2008) is used to support specific relationships. Our contribution is manyfold. First, from a theoretical perspective, we provide a deeper understanding of the influences affecting consumers’ satisfaction with roll­ over contracts and subsequent repurchase behavior, recognizing that these may comprise a range of pull factors, some of which may be based on the principle of reciprocity, and push factors, which may be associated with low perceived behavioral control. Secondly, we also contribute to identifying boundary conditions by comparing two types of services, and several potential moderating variables like trust, firm’s reputation, demographics and customer relationship duration with the service provi­ der. Thirdly, by offering a conceptual model for analyzing the antecedents and con­ sequences of contract-based consumer satisfaction with service providers, we encourage a future research agenda in services marketing that pays greater attention to the terms and presentation of contracts between providers and consumers. From a practical point of view, our study informs marketers that by implementing appro­ priate strategies, service firms may be able to reduce the number of customers terminating their agreements and switching to competitors, or who might engage in negative word of mouth. The remainder of this paper is organized as follows. First, we review the limited literature on automatic renewal contracts, mainly in the domains of law and consumer economics, and then we present the study’s theoretical framework. Following this, we turn to other relevant literature on services marketing, service loyalty, consumer decision making, and consumer inertia, to support the development of our hypotheses. Then, we describe and explain our methodology, before presenting the results of our data analysis, undertaken using covariance-based structured equation modelling (SEM). We conclude by summarizing and explaining our theoretical contributions and managerial implica­ tions, in particular considering the implications of our findings for services marketing researchers and service firms. 1338 M. M. BUTT ET AL. Literature review and hypotheses A main objective of this study is to assess the extent to which repeat purchases achieved as automatic renewals or extensions to service contracts, and positive word of mouth, are influenced by consumer satisfaction with their existing rollover agree­ ment. Service providers typically review and reset prices and service terms every 12 months, and therefore most service contracts may be conceptualized as fixed term contracts of 12 months duration, where customers have the option to automatically renew/continue. There are, of course, exceptions; for example, utility companies usually do not issue new agreements annually. Given the dearth of literature on automatic renewal contracts in the marketing domain, we turned initially to research published in the fields of law and consumer economics. Some of the research that guided this study is presented in Table 1. A preliminary study by Wilkins et al. (2023) considered consumers’ general attitudes and disposition toward rollover contracts, which influence their purchase decisions. They found that the desire for convenience had the strongest influence on consumer accep­ tance of rollover contracts, along with trust in the firm and perceived value. This study further expands their work in several ways. First, this research is focuses on measuring existing/experienced customers’ satisfaction with the rollover contract, and its potential antecedents and multiple outcomes in a holistic model. One of the novel contributions of this research is that it is likely to be one of the first studies to investigate consumers’ decision making on whether or not to renew (i.e. roll over) their service agreement at the end of a contracted service term. Consumers’ attitudes and decision making may be quite different before and after the consumer has experienced the service delivery, and at the end of a service term, switching costs and consumer inertia may act as barriers to switching provider (Gray et al., 2017). Thus, this research explores possible influences on consumers’ contract renewal decisions, which have not previously been considered in the literature. Theoretical background In this study, we use staying/repurchase intentions, word of mouth, and rollover accep­ tance as dimensions of customer service loyalty to a provider. In order to achieve customer service loyalty, providers must develop enduring customer relationships that are formed on the basis of reciprocity (Pervan & Johnson, 2003; Wilkins et al., 2023). Individuals typically feel psychologically obligated to return favors or benefits given to them (Kim & Lee, 2013). Social exchange theory has been useful in explaining the consumer loyalty towards a service provider that results from valued exchanges between firms and customers (J. J. Lee et al., 2014). Social exchange theory recognizes that in each exchange or transaction, there is a cost and a reward for each party. For example, a timepoor consumer who values convenience may consent to signing an automatically renew­ ing contract if the firm provides quicker and less demanding requirements to set up the new account. Similarly, if a firm provides a customer with a free service upgrade, the customer may perceive that they are receiving better value for money, and the resulting gratitude may translate into future behavioral loyalty intentions towards the service provider. JOURNAL OF STRATEGIC MARKETING 1339 Table 1. Key research on consumer contracts and automatic renewal clauses. Source Bisping and Dodsworth (2019). Paper type Review Key constructs or concepts ● Mobile phone contracts ● Pricing structures ● Technology ● Renewing and termi­ nating contracts Crawford et al. (2011). Case study ● Switching costs ● Customer retention DellaVigna and Malmendier (2006). Survey ● Consumer inertia ● Consumer overconfi­ Johnen (2017). Review Johnen (2019). Conceptual dence in predicting future benefits ● Consumer inertia ● Consumer procrastination ● Firm exploitation of consumer inertia ● Contractual terms ● Consumer inertia ● Teaser rates and back-loaded pricing ● Present-biased consumers Kock (2015). Lunn (2013). Review Review Wilkins, S., Hazzam, Survey J., & Megicks, P. (2023). ● Economic impacts of Key findings Contract duration, renewal of the agreement, and unilateral modification are three elements of automatically renewing long-term contracts that define consumer protection. Regulatory intervention varies across countries, and is influenced by technological development, geography, business considerations, and cultural considerations. Consumers with rollover contracts switch to competitors less than consumers on standard or fixed-term contracts. Based on their actual visits, gym members who choose a rolling monthly contract forgo savings by not selecting an alternative tariff, and they are more likely to stay enrolled beyond one year. Competitive firms rely more frequently on backloaded pricing, such as teaser rates/discounts. Consumers are overconfident about their future probability to cancel after the teaser period. Firms can then exploit consumer inertia by charging higher prices. Firms may use automatic renewal contracts to exploit consumer inertia. Competitive firms frequently offer less efficient contracts. The more a firm designs contracts to exploit consumer inertia, the higher are the benefits to more sophisticated consumers who take advantage of these offers by not procrastinating. Argues that firms’ use of automatic renewal clauses should be regulated because they may reduce consumer choices; increase switching/termination costs; hinder efficient termination; and increase average prices. automatic renewal clauses ● Legislative impacts of automatic renewal clauses ● Decision making Telecommunications markets present the consumer with a decision-making environment that is biases ● Switching costs particularly likely to be prone to established biases ● Endowment effect in consumer decision-making. Consumers’ ● Status quo bias inaccurate expectations of usage, or time ● Ambiguity aversion inconsistent preferences, may contribute to ● Procrastination consumers’ failure to select optimum contracts or ● Overconfidence bias switch providers. ● Consumer attitudes The desire for convenience was found to have the ● Perceived value strongest influence on consumer acceptance of ● Convenience rollover contracts, but trust and perceived value ● Firm reputation also influence consumers’ attitudes and behaviors. ● Trust To maximize revenues, service firms should ensure that agreements have an element of reciprocity. The theory of planned behavior explains that sometimes individuals may have a goal or desire, but for reasons beyond their control – such as the lack of information, ability, skills, or time – they are unable to take the action that achieves the goal or desire (Ajzen, 1985). In the theory of planned behavior, the factors that determine the individual’s perception of how easy or difficult it is to perform a particular behavior are referred to as ‘perceived behavioral control’. We use the logic of the theory of planned behavior to explain why consumers may not always act in the rational way that we would expect. A consumer may have a desire to switch provider – perhaps because they are not fully satisfied with the 1340 M. M. BUTT ET AL. service quality received – but other factors encourage this individual to undertake behavior that does not achieve their desire (Ajzen, 1985). For example, Gray et al. (2017) identified competitor similarity, consumer confusion, and switching costs as factors that may influence consumers when they are deciding whether or not to stay loyal to a firm. Finally, nudge theory may be used to explain consumers’ behavior. Thaler and Sunstein (2008, p. 6) define a nudge as, ‘any aspect of the choice architecture that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives’. Thus, nudges may take the form of defaults, where pre-set courses of action take effect if nothing is specified by the decision-maker. For example, if a gym reminds a customer about their health and fitness goals, the customer may be nudged to accept the new agreement without giving much attention to any changes in price or terms. Perceived value Consumers determine perceived value by assessing the trade-off between the price paid and the benefits received, which in turn influences their satisfaction and behavioral loyalty, i.e. repurchasing the service (Boksberger & Melsen, 2011; M. Lee & Cunningham, 2001). In effect, consumer satisfaction results when an individual considers the price paid as ‘fair’ for the benefits they received. Some individuals are prepared to pay a premium price for a product they perceive as higher quality, or one that will deliver higher levels of satisfaction (Nguyen et al., 2021). Consumers’ purchase decisions are typically influenced by price and quality more than any other factors (Wilkins & Ireland, 2022). Indeed, Bisping and Dodsworth (2019) claim that price is one of the most important aspects in consumers’ decision making when choosing a cell phone service. Umashankar et al. (2017) found that in service industries as customers’ behavioral loyalty increases, so too does the emphasis they place on price, so that price becomes a stronger determinant of perceived value than rewards or convenience. Thus, we conceptualize perceived value as value for money. H1: Perceived value is positively related to a consumer’s satisfaction with their auto­ matically renewing service agreement. Convenience Many consumers are interested in conserving time and effort, and therefore convenience may be a key consideration to these individuals when purchasing services (Berry et al., 2002). Consumers may require time to obtain information on different firms and products, evaluate alternatives, and undertake the purchase transaction. Although consumers may associate time usage with effort, effort actually comprises physical, cognitive and emo­ tional dimensions. For example, consumers may need to undertake calculations and exert considerable mental effort to effectively compare and evaluate different cell phone tariffs. A convenience-oriented consumer, who seeks to accomplish tasks in the shortest time possible using the minimal amount of energy, may be attracted to automatic renewal agreements. Not only do such agreements eliminate the need to obtain and evaluate JOURNAL OF STRATEGIC MARKETING 1341 information on alternative providers and products (decision convenience), the payment for repeat purchases usually occur automatically (transaction convenience). Various stu­ dies have found that convenience may influence consumers’ evaluations and behavioral loyalty towards a service provider (Martínez & Del Bosque, 2013; Umashankar et al., 2017; Wilkins et al., 2023). H2: Convenience is positively related to a consumer’s satisfaction with their automati­ cally renewing service agreement. Consumer inertia Consumer inertia may be recognized as a psychological phenomenon, where the indivi­ dual holds a set of assumptions and beliefs that justify a disposition toward maintaining the status quo by eliminating the need to consider other options or form new intentions (Henderson et al., 2021). Nudge theory explains that consumer inertia may result from the existence of default settings. Consumers with inertia continue purchasing the same brand passively and without much thought (Gray et al., 2017). Inert consumers typically prefer to avoid making new purchase decisions and transactions, and they may dislike having to learn new service routines and practices, thus encouraging contract rollover. Some consumers may be satisfied with their current provider because they perceive staying with their current provider the safer option, rather than risking a worse service from a new provider (R. Lee & Neale, 2012). When consumers have received a service that fulfils their expectations and desires, they are less likely to spend time evaluating either their existing provider or alternative providers, and more likely to renew their agreement without much further thought. H3: Consumer inertia is positively related to a consumer’s satisfaction with their auto­ matically renewing service agreement. Confusion Many service providers create contracts that are complex and difficult for consu­ mers to understand (Wilkins et al., 2023). Such agreements are often overly-long and use considerable amounts of technical and legal language. For example, Paypal’s terms of service agreement is approximately 50,000 words in length, while Apple iTunes’ agreement is 14,500 words (Hudson, 2013). As a result, the vast majority of service consumers do not read contracts in full before signing or agreeing to their terms (Hillman, 2006), and some individuals may agree to auto­ matic contract renewal without realizing they have done so (Johnen, 2018). The terms related to contract termination are often unclear or excessively demanding, in terms of the required notice period and method of communication, which is generally written. Some service providers make it difficult for customers to find the 1342 M. M. BUTT ET AL. address, telephone number or email address needed to communicate with the firm, so that individuals need to invest considerable time and effort to terminate their agreement (Kovač & Vandenberghe, 2015). H4: Consumer confusion is negatively related to a consumer’s satisfaction with their automatically renewing service agreement. Competitor similarity Competitor homogeneity may exist in markets where product differentiation is difficult or virtually impossible. Consumers will likely switch provider only if they perceive the alternative provider as more attractive (Gray et al., 2017). A competitor may, for example, offer a cheaper or higher quality product. A consumer who perceives that competitors are similar, and that other firms are unlikely to provide a superior service, may feel, on the basis of comparison with possible alternatives, more content and satisfied with their existing provider, thus providing them with a rationale for renewing their agreement (Patterson & Smith, 2003). H5: Perceived competitor similarity is positively related to a consumer’s satisfaction with their automatically renewing service agreement. Switching costs Most consumers consider switching costs in terms of the time, effort and economic costs of changing provider. In service contexts, Jones et al. (2002) identified six dimensions of switching costs: (1) time and effort needed to evaluate alternative providers; (2) time and effort required to commence service delivery; (3) benefits and privileges lost by switching; (4) loss of investments already made in the existing service relationship; (5) time and effort needed to learn a new service routine; and (6) losses arising from low performance with the new provider. A considerable body of research indicates that switching costs are positively related to repurchase intentions (e.g. Burnham et al., 2003; Gray et al., 2017; Jones et al., 2002; Kaur et al., 2012). Consumers who prefer to avoid the effort and economic costs associated with switching supplier may seek to identify reasons that support their decision to stay with the existing provider, and in focusing on the positive aspects of their customer experience they will likely feel more satisfied. H6: Switching costs are positively related to a consumer’s satisfaction with their auto­ matically renewing service agreement. JOURNAL OF STRATEGIC MARKETING 1343 Consequences of consumer satisfaction Previous research has indicated that service quality, reliability and dependability may be key determinants of consumer satisfaction with service providers (Saroha & Diwan, 2020), but the existing studies have not considered the effects of the service agreement on consumer satisfaction. For example, some consumers may place a higher value on convenience (offered by the rollover agreement) than service quality, and may be influenced differently by switching costs and the availability of alternative providers (Woisetschläger et al., 2011). A large body of literature has confirmed the relationship between consumer satisfaction and desirable consequences, such as repeat purchases and positive word of mouth (Watson et al., 2015). In service contexts, consumer involve­ ment may increase emotional and brand attachment, and service offerings that are perceived by the consumer to save time, effort, and transaction costs, are more likely to result in satisfaction that leads to positive post-consumption behaviors (Ahmad & Akbar, 2023; Yang & Peterson, 2004). Consumers learn from their personal experiences, and an individual who has a positive experience with a provider with which they have an automatically renewing agreement, is more likely to accept such agreements from other firms in the future (Polo & Sesé, 2009). H7: Consumer satisfaction with their service agreement is positively related to intention to stay with their existing provider. H8: Consumer satisfaction with their service agreement is positively related to favorable word of mouth. H9: Consumer satisfaction with their service agreement is positively related to future rollover contract acceptance with other firms. Figure 1 presents the proposed conceptual model. Firm reputation and trust Firm reputation and trust are particularly important to service providers, as the intangibility of services makes it difficult for consumers to assess alternative pro­ viders and products (Wirtz & Lovelock, 2016). In particular, trust has been found to commonly mediate the relationship between satisfaction and loyalty (Schirmer et al., 2018). In their study examining consumers’ general attitudes and dispositions toward automatic renewal agreements, Wilkins et al. (2023) found that a consumer’s trust in a firm has a significant influence on their purchase intentions. Furthermore, they found that firm reputation has an indirect effect on consumers’ decision making when moderated by trust. Hence, as post-hoc analysis, we explored the possible role of firm reputation and trust as moderating influences on the relationships between consumer satisfaction and our six predictors of consumer satisfaction. 1344 M. M. BUTT ET AL. Reciprocity Perceived value H1 Reputaon Trust Demographics Duraon with provider Consumers’ service loyalty Convenience H2 Staying inten!on H7 Perceived behavioral control H3 Consumer sa!sfac!on H8 Word of mouth H9 Consumer iner!a H4 Future rollover acceptance Confusion H5 Compe!tor similarity H6 Switching costs Figure 1. Proposed conceptual model. H10a: Firm reputation moderates the relationships between consumer satisfaction and its antecedents. H10b: Trust moderates the relationships between consumer satisfaction and its antecedents. Demographic influences It is widely recognized that individuals’ demographic characteristics may influence their decision making and purchase decisions (Çakır & Balagtas, 2014; Polo & Sesé, 2009). Thus, as post-hoc analysis, we explored whether a consumer’s gender, age, education (Sharma et al., 2012; Walsh et al., 2008), and length of time with their current service provider, may act as moderating influences on the relationships between consumer satisfaction and our six proposed antecedents of satisfaction. The length of time that a consumer is with a service provider may have an influence on the reported levels of consumer satisfaction because dissatisfied customers are more likely to terminate their service agreement earlier (Chiao et al., 2008). Over time, repeated or continued use of a service may result in consumers forming consumption and repurchasing habits, and individuals may associate the feelings of comfort resulting from their habitual behavior with satisfaction (Huang et al., 2023; Woisetschläger et al., 2011). H10c: Consumer gender moderates the relationships between consumer satisfaction and its antecedents. JOURNAL OF STRATEGIC MARKETING 1345 H10d: Consumer age moderates the relationships between consumer satisfaction and its antecedents. H10e: Consumer education moderates the relationships between consumer satisfaction and its antecedents. H10f: Length of time with the service provider moderates the relationships between consumer satisfaction and its antecedents. Methodology Sample and data collection The study population is consumers who obtain a service from a provider with which they have already agreed automatic contract renewal. Data were collected using an online survey questionnaire. The participants’ responses related to either their cell phone service or gym/sports/leisure club membership (hereafter referred to only as ‘gym’). The cell phone service was selected as a lower cost essential use product, while the gym was considered as a higher cost discretionary spend product. Mechanical Turk (MTurk) was used to collect data from respondents residing in the United States (US). Participant quality control measures were employed through Turkprime (see Litman et al., 2017). A total of 994 usable responses were obtained. Males accounted for 50.5% of the sample, and females 49.3%, while seven individuals answered ‘Other or prefer not to say’. Approximately 50% of the participants were below the age of 35 years; 44% were between the ages of 35 and 60 years; and the remaining were above the age of 60. More than 70% of the sample possess either an undergraduate or graduate degree, while 23% of the participants completed only high school or technical education. Measures With the exception of rollover acceptance, all of the measures used in this study are validated, pre-existing scales adopted from the literature. The measurement scale for perceived value was adopted fromSweeney and Soutar’s (2001) four-item scale for measuring functional value, i.e. the utility derived from a product compared to the price paid. The seven-item scale for convenience was adopted from Wilkins et al. (2023). The scales for consumer inertia, consumer confusion, perceived competitor similarity, and switching costs, were derived from Gray et al. (2017). The five-item scale for consumer satisfaction was also obtained from Gray et al. (2017), but the items were rephrased to make them specific to a cell phone service or gym membership. The scale measures the consumer’s overall satisfaction with their service offering, in the context of satisfaction with their service agreement. The scales for intention to stay and word of mouth were adopted from R. Lee and Neale (2012) and Walsh and Beatty (2007) respectively. Finally, the scales for firm reputation and trust were adopted from Keh and Xie (2009) and Sichtmann (2007). The five-item scale for rollover acceptance was developed by the 1346 M. M. BUTT ET AL. authors and subjected to pretesting with 20 pilot study participants. All of our survey items are presented in Appendix 1, which is provided as an online supplementary file. All of the validated measurement scales used in this research had previously demon­ strated satisfactory internal reliability (Cronbach’s alpha > 0.70). Our respondents used a 7-point Likert scale for all items, where 1 = strongly disagree and 7 = strongly agree. The survey questionnaire was subjected to pretesting with 20 consumers. The participants completed the survey questionnaire and then provided feedback in one of two focus groups. The survey instrument appeared to perform satisfactorily and no modifications were made to the draft version, other than some minor rephrasing of the questionnaire’s rubric. The final questionnaire is presented in Appendix 2, provided as an online supple­ mentary file. Results Preliminary data analysis Skewness and kurtosis were examined to assess the normality of the data. For skewness and kurtosis, a value of less than 8 is considered acceptable for a large data set (Kline, 2011). All of the observed variables in our model had a value of less than 3 for skewness and kurtosis. The variables in our model were then tested for possible multicollinearity. The results of multiple regression analysis indicated that the variance inflation factor (VIF) values for all independent variables were well below the cut criterion of < 4 (O’Brien, 2007). As we collect data for two types of services, Gym and Cell phone, we first conducted measurement invariance to test if we can compare the structural model across these groups. To achieve this, a multigroup confirmatory factor analysis was conducted. In the first step, we tested for the configural invariance. The results indicated that the data has a good fit with the model: χ2 = 3677.86 (df = 1936, p < 0.01); χ2/df = 1.90; RMSEA = 0.03; CFI = 0.95; GFI = 0.86; NFI = 0.90; and TLI = 0.94. Thus, configural invariance was achieved. We then tested for metric invariance by constraining all the factor loadings. The nested model comparison results suggest that the groups are not invariant (Δχ2 = 59.85, Δdf = 35, p < .001). We proceeded further by following a step-by-step process of constraining factor loadings, to identify the source of invariance across the groups. The results indicate that out of 12 latent factors, 10 were fully invariant, 1 (staying intention) was partially invariant, while rollover acceptance was not invariant across the groups. These results gave us a weak invariant model, but it is considered sufficient to test if the structural relationships in our model differ across groups (Byrne et al., 1989). It also allowed us to pool the data to establish the convergent and discriminant validity of our sample (Hanson et al., 2006). To establish convergent and discriminant validity, confirmatory factor analysis was conducted using the AMOS software version 26. The results indicated that the data has a good fit with the model: χ2 = 2143.10 (df = 968, p < 0.01); χ2/df = 2.21; RMSEA = .03; CFI = .96; GFI = .91; NFI = .96; and TLI = .95 (also see Appendix 3 in the supplementary online file). The common latent factor method was used to test for any bias in the data. In this method, an unmeasured first order common latent factor (CLF) is added in the measurement model. This new unmeasured latent factor is reflected by all the existing indicators in the measurement model (Podsakoff et al., 2003). The standar­ dized factor loadings of all the measurement indicators are compared when CLF is JOURNAL OF STRATEGIC MARKETING 1347 Table 2. Convergent and discriminant validity. Perceived value Convenience Consumer inertia Confusion Competitor similarity Switching costs Satisfaction Staying intention Word of mouth Future rollover acceptance Reputation Trust CR .92 .90 .91 .94 .87 .80 .91 .79 .94 .84 AVE VAL CONV INER CONF SIM SWIT SAT STAY WOM ACC REP TRUS .74 .85 .58 .24 .76 .78 .14 .13 .88 .82 −.15 −.30 .13 .90 .63 .07 .02 .22 .26 .79 .58 .19 .19 .43 .18 .14 .76 .67 .57 .35 .14 −.34 .09 .16 .84 .56 .46 .33 .25 −.36 .06 .26 .66 .75 .83 .50 .25 .13 −.31 .00 .18 .70 .69 .91 .58 .53 .25 .17 −.27 .09 .18 .73 .57 .53 .76 .88 .72 .91 .73 .29 .27 .56 .71 .21 .13 −.13 .03 −.26 −.03 .13 .14 .34 .34 .32 .35 .29 .28 .33 .22 .85 .55 .85 Notes: CR = composite reliability; AVE = average variance extracted; figures in italics on the diagonal are the square roots of the average variance extracted. present in the measurement model against the loadings without a CLF. The results suggest that the difference in the standard loadings was between 0.007 and .15, which are lower than the cut criterion of < .20 (Nystrand & Olsen, 2020). Results of the measurement model (Table 2) indicate that all of the constructs achieved values above the minimum cut criteria of > .70 for composite reliability (CR) and > 0.50 for average variance extracted (AVE), thus establishing convergent validity (Yap & Khong, 2006). Fornell and Larcker’s (1981) test was used to establish discriminant validity. All of the constructs have acceptable discriminant validity, as the value of the square root of AVE of each construct is higher than its highest correlation with any other construct in the model (Table 2). Thus, we conclude that all of the constructs in our measurement model are valid, reliable, and distinct from one another (Yap & Khong, 2006). Hypothesis testing The results from the full structural model indicate that the data has a good fit with the proposed model: χ2 (716) = 1916.20, p < 0.001; χ2/df = 2.26; RMSEA = 0.041; CFI = 0.95; GFI = 0.90; NFI = 0.93; and TLI = 0.95. All of the paths are significant at p < 0.05. The estimates of squared multiple correlations (R2) explain 49–55% of the variance of endogenous constructs in our model. Table 3 presents the standardized estimate, standard error and critical ratio related to each hypothesis tested. We also conducted a multi group analysis to test if the correlation between the latent constructs is different across two groups of customers (gym and cell phone users) (Table 4). The results suggest that the constrained model fit slightly worse (χ2 (1432) = 3026.58, p < 0.001; χ2/df = 2.11; RMSEA = 0.034; CFI = 0.94; GFI = 0.86; NFI = 0.90; and TLI = 0.94) than the unconstrained model (χ2 (1441) = 3062.18, p < 0.001; χ2/df = 2.12; RMSEA = 0.034; CFI = 0.94; GFI = 0.86; NFI = 0.89; and TLI = 0.94). The chi square difference test also suggests that the groups are different in terms of structural relationships (Δχ2 = 35.60, Δdf = 9, p < 0.001). To test which paths are different across groups, we compare two models by constraining and unconstraining each path individually. The results suggest that two paths were significantly different between the cell phone and gym users. They were between satisfaction with staying intention and satisfaction with word of mouth. 1348 M. M. BUTT ET AL. Table 3. Hypothesis test results. H1 H2 H3 H4 H5 H6 H7 H8 H9 Association Perceived value to satisfaction Convenience to satisfaction Consumer inertia to satisfaction Confusion to satisfaction Competitor similarity to satisfaction Switching costs to satisfaction Satisfaction to staying intention Satisfaction to word of mouth Satisfaction to future rollover acceptance Standard error .029 .038 .023 .020 .026 .037 .040 .043 .037 Standardized estimate .492 .117 .070 −.310 .113 .081 .707 .730 .739 Critical ratio 15.91 3.94 2.29 −10.04 3.90 2.42 15.02 25.02 23.13 Result Supported Supported Supported Supported Supported Supported Supported Supported Supported All paths are significant at p < 0.05. Table 4. Multigroup structural model path comparison. Cell Phone H1 H2 H3 H4 H5 H6 H7 H8 H9 Association Perceived value to satisfaction Convenience to satisfaction Consumer inertia to satisfaction Confusion to satisfaction Competitor similarity to satisfaction Switching costs to satisfaction Satisfaction to staying intention* Satisfaction to word of mouth* Satisfaction to future rollover acceptance S. Est. .50 .12 .12 −.34 .08 .01 .68 .75 .72 S. Error .036 .003 .003 .026 .033 .050 .059 .052 .050 Gym C.R. 12.003 3.018 2.932 −8.359 2.325 .299 11.714 19.394 15.464 S. Est .48 .10 .03 −.28 .12 .13 .72 .74 .75 S. Error .046 .058 .032 .032 .041 .055 .055 .043 .053 C.R. 10.562 2.357 .691 −6.141 2.866 2.784 9.340 17.116 17.047 *paths are significantly different at p < 0.05 using chi square test of difference. Moderation test results Product type, firm reputation, trust, and the consumer’s gender, age, education, and length of time with the current service provider were proposed as variables that may moderate the relationships between consumer satisfaction and its antecedents. Moderating effects were assessed using Hayes’ Process macro 3.5 model 1, with 5,000 bias corrected bootstrap samples and a 95% confidence interval. It was found that product type and firm reputation do not moderate the relationships between consumer satisfaction and its antecedents. Consumer trust in the service provider moderates the relationships between perceived competitor similarity and satisfaction, and switching costs and satisfaction. The condi­ tional effects are reported in Table 5. The results indicate that when perceived similarity is low, consumers high on trust are most satisfied, and consumers low on trust are least satisfied; however, when the perceived similarity is high, the interaction effect becomes non-significant. Similarly, when switching costs are low, consumers high on trust are most satisfied, and consumers low on trust are least satisfied; however, when the switching costs are high, the interaction effect again becomes non-significant. Education was found to moderate the relationships between satisfaction and value, convenience, confusion, and switching costs. Non-degree holders are less satisfied than degree holders when value and convenience are low, when confusion is high, or if there are high switching costs. When individuals seek value and convenience, when individuals feel less confused, or if switching costs are low, the non-degree holders are more satisfied than the degree holders. Gender and age moderate the relationship between confusion JOURNAL OF STRATEGIC MARKETING 1349 Table 5. Moderation analysis results. Moderator Trust Predictor Competitor similarity Switching costs Gender Confusion Age Confusion Level of education Perceived value Convenience Confusion Switching costs Duration with provider Perceived value Condition −1 SD At the mean +1 SD −1 SD At the mean +1 SD Female Male −1 SD At the mean +1 SD No degree Degree No degree Degree No degree Degree No degree Degree <2 years ≥2 years Effect .19 .12 .05 .27 .17 .08 −.19 −.29 −.18 −.23 −.29 .66 .53 .90 .63 −.35 −.21 .39 .17 .64 .53 SE .04 .02 .03 .06 .03 .04 .03 .03 .02 .01 .02 .04 .02 .11 .06 .04 .02 .07 .04 .03 .02 t 4.08 4.61 1.57 4.51 4.86 1.83 −7.16 −10.33 −6.78 −12.29 −10.96 14.42 20.32 8.17 10.10 −8.16 −9.98 5.07 4.13 16.42 18.69 p .001 .001 .110 .001 .001 .067 .000 .000 .001 .001 .001 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 95% CI .1034 .2943 .0729 .1808 −.0136 .1233 .1541 .3921 .1063 .2498 −.0058 .1728 −.2443 −.1394 −.3483 −.2371 −.2422 −.1335 −.2776 −.2012 −.3429 −.2388 .5744 .7553 .4971 .6034 .6861 1.119 .5123 .7592 −.4432 −.2714 −.2583 −.1734 .2393 .5410 .0920 .2579 .5677 .7218 .4828 .5961 and satisfaction. Females are more satisfied than males in high confusion situations, and vice versa. Similarly, younger people are less satisfied in high confusion situations. Finally, duration with the service provider moderates the relationship between value and satis­ faction. This finding is important because previous research has found that perceived value and the length of consumer-provider relationships influence consumers’ attitudes towards switching provider (Wang & Wu, 2012). Although the newer customers in our sample tend overall to be less satisfied than older customers, the longer the time with the provider, the weaker is the relationship between value and satisfaction. In summary, we found partial support for H10b, H10c, H10d, H10e, and H10f. Discussion Based on past literature, we identified and empirically tested six likely antecedents of rollover contract satisfaction, and three consequences of such satisfaction. Each of the nine hypotheses (H1–H9) associated with relationships between the constructs of our conceptual model are supported. The three relationships between consumers’ satisfac­ tion and service loyalty (H7, H8, H9) – measured by staying (repurchase) intentions, word of mouth, and rollover acceptance – are the strongest in our model. Although this result may be unsurprising given that there is much support in the literature for a link between satisfaction and service loyalty (e.g. Ahmad & Akbar, 2023; Watson et al., 2015; Yang & Peterson, 2004), it is an important finding in the context of service contract renewal since even customers who are satisfied with their service provider could switch to a competitor that develops a service innovation or offers a price discount. Thus, our results emphasize the importance of consumer satisfaction in achieving consumer service loyalty. Perceived value emerged as the strongest enabler of consumer satisfaction with roll­ over contracts, while consumer confusion – e.g. caused by lengthy and complex con­ tracts – has the strongest negative effect on consumer satisfaction. This was followed by 1350 M. M. BUTT ET AL. convenience, as an important predictor of consumer satisfaction. Our findings that perceived value and convenience are key drivers of consumer satisfaction with rollover contracts may be compared to the findings of Wilkins et al. (2023), which found that convenience and perceived value are key influences on consumers’ initial decision to enter into automatic renewal agreements. Service providers should focus on those constructs in our model that they have control over. For example, in some service categories, firms may have little or no influence over consumer inertia or perceived competitor similarity. As H1–H6 are each supported, this suggests that service providers should deliver value and convenience, and emphasize this to consumers in marketing communications. Further, providers should avoid using con­ tracts that are overly-long, complex, and difficult for consumers to understand as this will lead to lower levels of satisfaction. Likewise, particularly for consumers who value con­ venience, providers may use a certain level of switching costs, so that the consumer perceives they are saving time and effort by staying with their existing provider. However, switching costs should not be extreme, as consumers may then perceive them as unreasonable, resulting in lower levels of satisfaction. The results of H10b–10f offer support for the moderating influences of consumers’ gender, age, level of education, trust in the service provider, and length of time with the provider on some of the relationships in our model. The antecedent variables that are most affected by these moderating influences are perceived value, confusion, and switch­ ing costs. Service providers may use this knowledge when targeting specific categories of consumer. For example, a provider that sells its service to mainly young people will generate lower levels of satisfaction if the service contract is perceived as confusing, as young people are generally less willing to spend time and effort understanding long and complex agreements compared to older people. Theoretical contributions By considering how service agreements may influence the antecedents of consumer satisfaction, this research contributes to the academic literature by extending previous research on consumer repurchase decision making and behavioral loyalty in services. First, we offer a holistic model that includes key antecedents of consumer satisfaction with rollover contracts, and the subsequent effects on staying intentions, word of mouth, and future rollover acceptance with other firms and products. The results highlight that the structure, presentation and contractual terms of service contracts may have an impact on various antecedents of consumer satisfaction. Furthermore, the results suggest that consumers may perceive automatic renewal at the end of a contracted period as a contributor to value. When faced with the decision of whether to stay with the existing provider or switch to a competitor, ‘rolling over’ the contract may save consumers the time and effort needed for information searching and evaluation of alternative providers. Second, our research sheds new light on the relationship between consumer satisfac­ tion and behavioral loyalty. While the extant research has focused on consumer inertia and switching costs (Gray et al., 2017), no previous study has considered the impacts of automatic contract renewal and the contractual terms associated with this – e.g. notice periods, penalties and loss of benefits – on consumer repurchase/switching decision making. We demonstrate that consumer satisfaction with rollover contracts is influenced JOURNAL OF STRATEGIC MARKETING 1351 by both positive factors, such as value and convenience, and negative factors, such as switching costs and confusion caused by lengthy and complex contracts. Third, our findings reinforce the importance of reciprocity in service relationships. As explained by social exchange theory, when making purchase decisions, consumers gen­ erally consider the potential rewards against the costs (J. J. Lee et al., 2014). Perceived value, conceptualized as perceived value for money, was found to be the strongest enabler of customer satisfaction. Interestingly, our results indicate that consumers may perceive automatic contract renewal as either a reward (e.g. by providing convenience and saving the individual time and effort) or a cost (e.g. limiting or constraining future opportunities to switch provider). Finally, our study reveals the potential benefits that firms may derive from consumers having lower levels of perceived behavioral control. From a theoretical perspective, it should be noted that firms may have the ability to influence consumers’ perceived behavioral control in some areas, while in other areas they may not have the ability to shape the consumers’ perceptions. In markets where it is difficult for firms to commu­ nicate a unique selling proposition, such as insurance or home security, consumers may perceive that the time and effort needed to collect information and evaluate alternative providers is unlikely to be worthwhile. It is interesting to note that the existence of switching barriers may actually increase consumer satisfaction, as individuals may per­ ceive that automatic contract renewal has saved them time, effort and inconvenience. Managerial implications Our findings present a number of managerial implications. First, although it is universally accepted that consumer satisfaction does not always lead to positive consumer behaviors, the strongest relationships in our model are between satisfaction and staying intentions, word of mouth, and future rollover acceptance with other firms and products. This implies that firms will benefit from focusing on the achievement of consumer satisfaction. Firms should identify the antecedents of satisfaction, and then develop and implement appro­ priate strategies that lead to these antecedents having a positive effect on satisfaction. Our results show that perceived value for money has the strongest influence on consumer satisfaction. Firms will likely benefit from undertaking market research, to identify custo­ mer needs and wants, particularly as the price-quality trade-off varies across products and markets (Wilkins & Ireland, 2022). Second, firms need to be aware of the seemingly negative factors that may positively or negatively affect consumer satisfaction and consumers’ subsequent behaviors. Of particular relevance to marketers are those antecedents of satisfaction over which they have control, or which they may influence. Firms need to exercise considerable care when designing consumer agreements and making decisions relating to switching costs and barriers. Although confusion marketing that makes it very difficult for customers to terminate their agreement may be profitable in the short term (Kasabov, 2015), it may result in negative outcomes in the longer term, such as reputational damage. Lengthy and complex contracts are likely to have a negative effect on consumer satisfaction, and even if the consumer does not switch provider, their negative attitudes toward the firm may translate into negative word of mouth, which may make it harder for the firm to recruit new customers. 1352 M. M. BUTT ET AL. Third, the results of this study serve as a reminder to marketers of the importance of trust in services marketing. Even though a consumer has received satisfactory service in the past, they will likely consider the likelihood of receiving good service in the future as well. In particular, trust was found to moderate the relationship between switching costs and satisfaction. It may be unwise for firms to try imposing unfair or unreasonable switching costs on consumers, as this could lower the individual’s trust in the firm, and subsequently also lower satisfaction. As well as behaving ethically, firms may use their marketing communications with customers to remind them of the benefits and value they receive, to develop and maintain strong firm-customer relationships. Finally, our findings suggest that firms should consider various demographic features of their customers. For example, firms that sell their products primarily to women, may develop and implement different strategies to firms that sell predominantly to men. Although our results found that confusion is negatively related to satisfaction, such confusion has a lesser effect on female consumers. It was interesting to note that within more confused customer groups, female respondents were more satisfied, compared to male respondents. Similarly, age moderates the relationship between confusion and satisfaction. As firms often focus on achieving rollover agreements with more profitable mature consumers, the need for marketers to reduce ambiguity and confusion surround­ ing rollover contracts remains important. Less educated consumers are less satisfied than more highly educated consumers when value and convenience are low, when confusion is high, or if there are high switching costs. To maximize the satisfaction of less educated customers, firms should implement strategies that provide value and convenience, while also keeping agreements simple and fair. Although our results also suggest that higher levels of satisfaction can be achieved through having higher switching costs, such a strategy may be counterproduc­ tive, as we do not know if there is a linear relationship between high switching costs and consumer satisfaction. A firm may not only retain customers, but also gain new customers, and market share, by actively promoting simple and transparent contracts. This strategy may be regarded as ethical behavior toward customers, and it may help a firm to differentiate itself from competitors. Limitations and future research This study is the first of its kind, which developed and empirically tested a holistic model that incorporates both antecedents and consequences of consumer satisfaction with rollover contracts. Thus, this research has contributed to the literature in a meaningful way. The results emphasize the importance of improving consumers’ perceived value of such contracts, and challenge the existing conception that inertia and switching costs are the major factors considered in consumer repurchase decision making, which influence customer attitudes, satisfaction, and behaviors toward roll­ over contracts. In addition, the results indicate that consumer confusion is a very strong dissatisfier, suggesting that firms should focus on reducing confusion around rollover contracts. One of the limitations of our research is its cross-sectional design. Also, we only considered consumers’ attitudes and behaviors toward two products, and in only one country. Future studies may examine the effects of other factors that may have JOURNAL OF STRATEGIC MARKETING 1353 an effect on consumer attitudes and behaviors, and such studies may involve manipulations, to strengthen the findings. Researchers may also further explore how increasing or decreasing confusion around renewal can impact upon consumer perceptions and attitudes toward rollover contracts, as well as their subsequent behaviors. Our model focused primarily on the identification and testing of enablers of satisfaction, but future research could focus on identifying potential disablers or barriers toward rollover acceptance. Future studies could also explore the extent to which consumer decision making is influenced by personal values and circum­ stances. Finally, we acknowledge that multidimensional scales could have been used for perceived value and convenience to have a more in-depth understanding of the proposed relationships with customer satisfaction, and these may be used in future research. Disclosure statement No potential conflict of interest was reported by the author(s). ORCID Muhammad Mohsin Butt http://orcid.org/0000-0002-1894-243X Stephen Wilkins http://orcid.org/0000-0002-0238-1607 Joe Hazzam http://orcid.org/0000-0003-4631-9167 Ben Marder http://orcid.org/0000-0003-1641-2344 References Ahmad, B., & Akbar, M. I. U. D. (2023). Validating a multidimensional perspective of relationship marketing on brand attachment, customer loyalty and purchase intentions: A serial mediation model. Journal of Strategic Marketing, 31(3), 669–692. https://doi.org/10.1080/0965254X.2021. 1969422 Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: From cognition to behavior (pp. 11–39). Springer-Verlag. Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of Marketing, 66(3), 1–17. https://doi.org/10.1509/jmkg.66.3.1.18505 Bisping, C., & Dodsworth, T. J. (2019). Consumer protection and the regulation of mobile phone contracts: A study of automatically renewable long-term contracts across jurisdictions. Journal of Consumer Policy, 42(3), 349–375. https://doi.org/10.1007/s10603-019-09417-0 Boksberger, P. E., & Melsen, L. (2011). Perceived value: A critical examination of definitions, concepts and measures for the service industry. Journal of Services Marketing, 25(3), 229–240. https://doi. org/10.1108/08876041111129209 Burnham, T. A., Frels, J. K., & Mahajan, V. (2003). Consumer switching costs: A typology, antecedents, and consequences. Journal of the Academy of Marketing Science, 31(2), 109–126. https://doi.org/ 10.1177/0092070302250897 Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105(3), 456–466. https://doi.org/10.1037/0033-2909.105.3.456 Çakır, M., & Balagtas, J. V. (2014). Consumer response to package downsizing: Evidence from the Chicago ice cream market. Journal of Retailing, 90(1), 1–12. https://doi.org/10.1016/j.jretai.2013. 06.002 1354 M. M. BUTT ET AL. Chiao, Y. C., Chiu, Y. K., & Guan, J. L. (2008). Does the length of a customer–provider relationship really matter? The Service Industries Journal, 28(5), 649–667. https://doi.org/10.1080/ 02642060801988191 Crawford, G. S., Tosini, N., & Waehrer, K. (2011). The impact of ‘rollover’ contracts on switching costs in the UK voice market: Evidence from disaggregate customer billing data. University of Warwick. Curasi, C. F., & Kennedy, K. N. (2002). From prisoners to apostles: A typology of repeat buyers and loyal customers in service businesses. Journal of Services Marketing, 16(4), 322–341. https://doi. org/10.1108/08876040210433220 DellaVigna, S., & Malmendier, U. (2006). Paying not to go to the gym. American Economic Review, 96 (3), 694–719. https://doi.org/10.1257/aer.96.3.694 Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. https:// doi.org/10.1177/002224378101800313 Gray, D. M., D’Alessandro, S., Johnson, L. W., & Carter, L. (2017). Inertia in services: Causes and consequences for switching. Journal of Services Marketing, 31(6), 485–498. https://doi.org/10. 1108/JSM-12-2014-0408 Hanson, G. C., Hammer, L. B., & Colton, C. L. (2006). Development and validation of a multidimensional scale of perceived work-family positive spillover. Journal of Occupational Health Psychology, 11(3), 249–265. https://doi.org/10.1037/1076-8998.11.3.249 Henderson, C. M., Steinhoff, L., Harmeling, C. M., & Palmatier, R. W. (2021). Customer inertia marketing. Journal of the Academy of Marketing Science, 49(2), 350–373. https://doi.org/10. 1007/s11747-020-00744-0 Hillman, R. A. (2006). Online consumer standard-form contracting practices: A survey and discussion of legal implication. In J. K. Winn (Ed.), Consumer protection in the age of the information economy (pp. 283–312). Ashgate Press. Huang, C. C., Tsay, C. Y., Fang, S. C., & Huang, S. M. (2023). A contingency model in establishing brand loyalty: Relationship age as a moderator. Corporate Reputation Review, 26(1), 19–32. https://doi. org/10.1057/s41299-021-00131-7 Hudson, A. (2013). Is small print in online contracts enforceable? BBC News, Retrieved June 6, 2013, from https://www.bbc.com/news/technology-22772321 Jaakkola, E., & Vargo, S. L. (2021). Assessing and enhancing the impact potential of marketing articles. AMS Review, 11(3–4), 407–415. https://doi.org/10.1007/s13162-021-00219-7 Jedidi, K., Schmitt, B. H., Sliman, M. B., & Li, Y. (2021). R2M Index 1.0: Assessing the practical relevance of academic marketing articles. Journal of Marketing, 85(5), 22–41. https://doi.org/10.1177/ 00222429211028145 Johnen, J. (2017). Screening procrastinators with automatic-renewal contracts. CORE, UCLouvain. Johnen, J. (2018). Dynamic competition in deceptive markets. CORE, UCLouvain. Johnen, J. (2019). Automatic‐renewal contracts with heterogeneous consumer inertia. Journal of Economics & Management Strategy, 28(4), 765–786. https://doi.org/10.1111/jems.12317 Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2002). Why customers stay: Measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes. Journal of Business Research, 55(6), 441–450. https://doi.org/10.1016/S0148-2963(00) 00168-5 Kasabov, E.(2015). What we know, don’t know, and should know about confusion marketing. European Journal of Marketing, 49(11–12), 1777–1808. https://doi.org/10.1108/EJM-03-2014-0166 Kaur, G., Sharma, R. D., Mahajan, N., & Roy, S. K. (2012). Exploring customer switching intentions through relationship marketing paradigm. International Journal of Bank Marketing, 30(4), 280–302. https://doi.org/10.1108/02652321211236914 Keh, H. T., & Xie, Y. (2009). Corporate reputation and consumer behavioral intentions: The roles of trust, identification and commitment. Industrial Marketing Management, 38(7), 732–742. https:// doi.org/10.1016/j.indmarman.2008.02.005 Kim, S., & Lee, J. S. (2013). Is satisfaction enough to ensure reciprocity with upscale restaurants? The role of gratitude relative to satisfaction. International Journal of Hospitality Management, 33 (June 2013), 118–128. https://doi.org/10.1016/j.ijhm.2012.06.009 JOURNAL OF STRATEGIC MARKETING 1355 Kline, R. B. (2011). Convergence of structural equation modeling and multilevel modeling. In M. Williams & W. P. Vogt (Eds.), The SAGE handbook of innovation in social research methods (pp. 562–589). Sage. Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of E-Collaboration, 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101 Kovač, M., & Vandenberghe, A. S. (2015). Regulation of automatic renewal clauses: A behavioural law and economics approach. Journal of Consumer Policy, 38(3), 287–313. https://doi.org/10.1007/ s10603-015-9286-4 Lee, J. J., Capella, M. L., Taylor, C. R., Luo, M., & Gabler, C. B. (2014). The financial impact of loyalty programs in the hotel industry: A social exchange theory perspective. Journal of Business Research, 67(10), 2139–2146. https://doi.org/10.1016/j.jbusres.2014.04.023 Lee, M., & Cunningham, L. F. (2001). A cost/benefit approach to understanding service loyalty. Journal of Services Marketing, 15(2), 113–130. https://doi.org/10.1108/08876040110387917 Lee, R., & Neale, L. (2012). Interactions and consequences of inertia and switching costs. Journal of Services Marketing, 26(5), 365–374. https://doi.org/10.1108/08876041211245281 Litman, L., Robinson, J., & Abberbock, T. (2017). TurkPrime. com: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior Research Methods, 49(2), 433–442. https://doi.org/10.3758/s13428-016-0727-z Lunn, P. D. (2013). Telecommunications consumers: A behavioral economic analysis. Journal of Consumer Affairs, 47(1), 167–189. https://doi.org/10.1111/j.1745-6606.2012.01245.x Martínez, P., & Del Bosque, I. R. (2013). CSR and consumer loyalty: The roles of trust, consumer identification with the company and satisfaction. International Journal of Hospitality Management, 35(December 2013), 89–99. https://doi.org/10.1016/j.ijhm.2013.05.009 Nguyen, T. H. N., Yeh, Q. J., & Huang, C. Y. (2021). Understanding consumer’ switching intention toward traceable agricultural products: Push-pull-mooring perspective. International Journal of Consumer Studies, 46(3), 870–888. Retrieved July 4, 2021, from https://doi.org/10.1111/ijcs.12733 Nystrand, B. T., & Olsen, S. O. (2020). Consumers’ attitudes and intentions toward consuming functional foods in Norway. Food Quality and Preference, 80(March 2020), 103827. https://doi. org/10.1016/j.foodqual.2019.103827 O’Brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41(5), 673–690. https://doi.org/10.1007/s11135-006-9018-6 Patterson, P. G., & Smith, T. (2003). A cross-cultural study of switching barriers and propensity to stay with service providers. Journal of Retailing, 79(2), 107–120. https://doi.org/10.1016/S00224359(03)00009-5 Pervan, S. J., & Johnson, L. W. (2003). Understanding process in relationship marketing: A focus on reciprocity. Journal of Customer Behaviour, 2(2), 167–191. https://doi.org/10.1362/ 147539203322383555 Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879 Polo, Y., & Sesé, F. J. (2009). How to make switching costly: The role of marketing and relationship characteristics. Journal of Service Research, 12(2), 119–137. https://doi.org/10.1177/ 1094670509335771 Saroha, R., & Diwan, S. P. (2020). Development of an empirical framework of customer loyalty in the mobile telecommunications sector. Journal of Strategic Marketing, 28(8), 659–680. https://doi.org/ 10.1080/0965254X.2019.1569110 Schirmer, N., Ringle, C. M., Gudergan, S. P., & Feistel, M. S. (2018). The link between customer satisfaction and loyalty: The moderating role of customer characteristics. Journal of Strategic Marketing, 26(4), 298–317. https://doi.org/10.1080/0965254X.2016.1240214 Sharma, P., Chen, I. S., & Luk, S. T. (2012). Gender and age as moderators in the service evaluation process. Journal of Services Marketing, 26(2), 102–114. https://doi.org/10.1108/ 08876041211215266 Sichtmann, C. (2007). An analysis of antecedents and consequences of trust in a corporate brand. European Journal of Marketing, 41(9/10), 999–1015. https://doi.org/10.1108/03090560710773318 1356 M. M. BUTT ET AL. Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203–220. https://doi.org/10.1016/S0022-4359(01)00041-0 Thaler, R. H., & Sunstein, C. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press. Umashankar, N., Bhagwat, Y., & Kumar, V. (2017). Do loyal customers really pay more for services? Journal of the Academy of Marketing Science, 45(6), 807–826. https://doi.org/10.1007/s11747-0160491-8 Walsh, G., & Beatty, S. E. (2007). Consumer-based corporate reputation of a service firm: Scale development and validation. Journal of the Academy of Marketing Science, 35(1), 127–143. https://doi.org/10.1007/s11747-007-0015-7 Walsh, G., Evanschitzky, H., & Wunderlich, M. (2008). Identification and analysis of moderator variables: Investigating the customer satisfaction‐loyalty link. European Journal of Marketing, 42 (9/10), 977–1004. https://doi.org/10.1108/03090560810891109 Wangenheim, F. V., Wünderlich, N. V., & Schumann, J. H. (2017). Renew or cancel? drivers of customer renewal decisions for IT-based service contracts. Journal of Business Research, 79, 181–188. https://doi.org/10.1016/j.jbusres.2017.06.008 Wang, C., & Wu, L. (2012). Customer loyalty and the role of relationship length. Managing Service Quality: An International Journal, 22(1), 58–74. https://doi.org/10.1108/09604521211198119 Watson, G. F., Beck, J. T., Henderson, C. M., & Palmatier, R. W. (2015). Building, measuring, and profiting from customer loyalty. Journal of the Academy of Marketing Science, 43(6), 790–825. https://doi.org/10.1007/s11747-015-0439-4 Wilkins, S., Hazzam, J., & Megicks, P. (2023). Consumers’ propensity for rollover service contracts: The influences of perceived value, convenience and trust on service loyalty. Journal of Strategic Marketing, 31(3), 516–531. https://doi.org/10.1080/0965254X.2021.1946127 Wilkins, S., & Ireland, J. J. (2022). FMCG firms’ margin management: Consumer trade-offs among product price, quantity and quality. Journal of Strategic Marketing, 30(8), 764–781. https://doi.org/ 10.1080/0965254X.2020.1849362 Wirtz, J., & Lovelock, C. (2016). Services marketing: People, technology, strategy (8th ed.). World Scientific Publishing Company. Woisetschläger, D. M., Lentz, P., & Evanschitzky, H. (2011). How habits, social ties, and economic switching barriers affect customer loyalty in contractual service settings. Journal of Business Research, 64(8), 800–808. https://doi.org/10.1016/j.jbusres.2010.10.007 Yang, Z., & Peterson, R. T. (2004). Customer perceived value, satisfaction, and loyalty: The role of switching costs. Psychology & Marketing, 21(10), 799–822. https://doi.org/10.1002/mar.20030 Yap, B. W., & Khong, K. W. (2006). Examining the effects of customer service management (CSM) on perceived business performance via structural equation modeling. Applied Stochastic Models in Business and Industry, 22(5), 587–606. https://doi.org/10.1002/asmb.648
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