Chat with us, powered by LiveChat Most medical specialty groups historically have relied on primary care physician practices for referrals. At a recent society meeting, the senior partner re - EssayAbode

Most medical specialty groups historically have relied on primary care physician practices for referrals. At a recent society meeting, the senior partner re

 

ASSIGNMENT FOUR

Question One: Most medical specialty groups historically have relied on primary care physician practices for referrals. At a recent society meeting, the senior partner returned with a renewed perspective in terms of looking at the customer base of referrers. “We need to develop relationships with these practices rather than view them as individual transactions when they send us a patient.” How might this perspective shift the strategy of the group? Provide illustrations. 

Question Two: In the digital age, companies like Wayfair, Amazon, and others operate 24/7/365. How does a people-based industry such as healthcare, which has an inseparability between providing the service and the people who deliver it, move to being 24/7/365? The challenge in the digital age is that competition is beyond the bounds of the local market. Assume you are the CEO of a hospital or medical group; what is your response or strategy? Provide illustrations. 
 

This is the Author’s Accepted Manuscript (AAM). Please cite this article as follows:

Gonçalves, F.M.R.R., Cândido, C.J.F., and Feliciano, I.M.P.L. (2020). Inertia, group conformity and patient loyalty in healthcare in the information age. Journal of Service Theory and Practice, 30(3), 307-330.

DOI : http://dx.doi.org/10.1108/JSTP-08-2019-0184

HTML: http://www.emeraldinsight.com/doi/10.1108/JSTP-08-2019-0184

This article is © Emerald Group Publishing and permission has been granted for this version to appear here (https://sapientia.ualg.pt/). Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.

Inertia, group conformity and patient loyalty in healthcare in the information age

Abstract Purpose. To analyse the influence of inertia and group conformity on loyalty in healthcare. Methodology. Structural equation model developed from the literature and tested with cross sectional data from a patient online survey.

Findings. Inertia is a significant antecedent of loyalty and has a stronger effect in healthcare than in other service sectors. Group conformity has no significant effect in healthcare. Research Implications. The strength of the impact of inertia [group conformity] on loyalty depends on the importance of the customer need that the service industry satisfies, in Maslow’s hierarchy of needs. Where inertia (stability need) is equally or more [less] important than the customer need, the influence of inertia on loyalty should be positive and strong [weak or insignificant]. In services that satisfy needs more [equally or less] important than group conformity (belonging need), there may be an insignificant [significant] influence of group conformity on customer loyalty, even [especially] in credence services. Practical Implications. Healthcare providers can exploit the stronger effect of inertia in healthcare through development of inertia-based loyalty policies. Regulatory authorities should be vigilant to ensure that these policies are not detrimental to patients. ‘Inert’ patients must become responsible for assessing their loyalties. Authorities and reference groups must stimulate customer loyalty assessments, and assist by providing impartial information. Originality. This is the first study to address the influence of inertia and group conformity on loyalty in the healthcare sector and, from the perspective of Maslow’s hierarchy of needs, it is the first to do so in any service sector.

Keywords: apathy, habit, online communities, perceived price, repurchase, customer retention, satisfaction, service quality, social influence.

1. Introduction

Inertia is an individual’s apathetic state that contributes to maintaining that individual’s habits and routines and to preventing behavioural change (Genschel, 1997; Chatterjee, 1998; Wu, 2011a; Li, 2015; Lucia-Palacios et al., 2016). Inertia prevents individuals from looking for alternative service providers and from changing consumption behaviours (Wu, 2011a; Lucia Palacios et al., 2016; Gray et al., 2017). In healthcare, in the absence of a strong stimulus, such as clear negative feedback about a current provider, the patient may prefer to avoid change and, consequently, remain loyal to a healthcare organisation.

Group conformity is, in turn, a social influence through which individuals replicate the attitudes and behaviours of a reference group or group leader (Hornsey and Jetten, 2005; Nitzan and Libai, 2011; Gu et al., 2016). Similarly to inertia, group conformity can determine, to a certain extent, customer buying behaviours (Tsai and Pai, 2012; Gu et al., 2016; Toker-Yildiz, 2017), and loyalty to a healthcare provider.

Both inertia and conformity can be influenced by strong opinions circulating on the internet or other media, and can influence patient loyalty. The internet, published materials, social and other media raise awareness, urge people to change, create models/ideals of health and fitness, and influence patient opinions, needs and choices. In particular, the internet and other media can affect patient inertia in changing healthcare providers, create group conformity behaviours to mimic new trends, and affect patient loyalty.

The advent and omnipresence of the internet and other media makes the relationships between group conformity, inertia and patient loyalty an interesting research topic and contributes to raising the research question of how strong the influence of these variables is on loyalty. More specifically, it contributes to raising the two research questions addressed in this study: (1) how does inertia influence loyalty in healthcare, and, (2) how does group conformity influence loyalty in healthcare.

Previous research on the impact of inertia on service customer loyalty is scarce (Wu, 2011a; Kim and Kang, 2016; Gray et al., 2017). Similarly, research on the influence of group conformity on service customer loyalty is also scant (Ruiz-Mafe et al., 2016; Saleem et al., 2016; Toker-Yildiz et al., 2017). Besides this scarcity, the research on these topics in the healthcare management area is completely non-existent. As far as the authors are aware, no research in the specific context of healthcare has addressed the impact of inertia or conformity on loyalty.

The study of inertia and conformity as antecedents to loyalty is important in the context of healthcare because health is a major priority need for human beings. Alongside the importance of healthcare, stability (inertia) and belonging (group conformity) are similarly important needs to human beings (Maslow, 1970; Tsai et al., 2017). Specifically, health and inertia are on the second most important level of human needs (safety/stability), whereas group conformity is on the third most important level (love/belonging). Given that humans attribute priority to the satisfaction of some needs over others, it is important to understand how patients relate and prioritise health, inertia and group conformity. Consequently, this paper aims to identify factors that influence patient loyalty in healthcare, in the context of the information economy, and to study the influence of inertia and conformity on loyalty.

Maslow’s (1970) hierarchy of human needs adds novelty to the study because it has not been considered in previous works. In fact, this research is the first to study the influence of inertia and group conformity on customer loyalty from the perspective of Maslow’s (1970) theory of human motivation. Alongside helping to develop the main research hypotheses of this study, Maslow’s hierarchy of needs allows a comparison of the strength of the relationships between inertia, conformity and loyalty across industries, which has not been made to date. This comparison across service industries, which satisfy needs at different levels of Maslow’s (1970) hierarchy, suggests significant research implications for the healthcare and for other service industries. Specifically, this study discovers that the strength of the impact of inertia [group conformity] on loyalty depends on the importance of the customer need that the service industry satisfies. Where inertia is equally or more [less] important than the customer need, the influence of inertia on loyalty is positive and strong [weak or insignificant]. In services that satisfy needs more [equally or less] important than group conformity, there is an insignificant [significant] influence of group conformity on customer loyalty. From these theoretical implications, several practical implications are drawn for major healthcare stakeholders.

Besides the main research variables (inertia and conformity), this study considers the influence of three additional variables: price, quality and satisfaction. These variables have been researched as determinants to customer loyalty in both services and manufacturing industries, and studies have established them as significant antecedents to customer loyalty (Moliner, 2009; Lobo et al., 2014; Buell et al., 2016; Zhou et al., 2017). Moreover, the literature on loyalty, in the specific context of healthcare, has identified price, quality and satisfaction as key success factors (Zhou et al., 2017). Increasingly, patients make more careful choices regarding healthcare providers: insurance companies and regulatory agencies press healthcare providers for improved quality (Arbel and Greenberg, 2016); accreditation and standardisation certificates are less able to differentiate competitors (Marimon et al., 2009; Cândido et al., 2019), and patients are starting to look for affordable quality healthcare in foreign countries (Han and Hyun, 2015). Consequently, private hospitals that do not deliver service quality at reasonable prices, and do not satisfy their patients, risk losing patient loyalty and market share (Anbori et al., 2010). Consistent with these arguments, these variables are considered together with inertia and group conformity in this research.

The reminder of the article is organised as follows. Section 2 reviews the literature and develops the research hypothesis. Section 3 summarises the research methodology, with details on sample size, measurement tool and data analysis. Section 4 presents a description of the sample and the main empirical evidence. Sections 5 and 6 contain a theoretical discussion and draw out the research implications. Finally, Section 7 concludes the article and presents research limitations.

2. Literature review and hypotheses

This study addresses two research questions: how does inertia influence loyalty and how does conformity influence loyalty. In accordance with these research questions, this section reviews the literature on inertia, group conformity and loyalty, and subsequently reviews the related literature on price, quality and satisfaction. Research hypotheses are carefully developed, initially with the aid of the relevant literature on service management, and then with the aid of the literature on the healthcare sector, when available.

Inertia is a state of inactivity that inhibits creativity, innovative thinking and behaviour change (Chatterjee, 1998). Inertia is synonymous with apathy, habit, routine, and no changes (Genschel, 1997; Wu, 2011a; Li, 2015; Gray et al., 2017). Change requires a break with the past, abandoning old routines, habits, and shifting to new ways of thinking; conversely, inertia maintains the general state of things, the habit, the status quo. Likewise, in this paper, inertia is considered as an individual’s apathetic state that maintains their habits and routines and can contribute to preventing behavioural change.

Consumer inertia key aspects are automaticity, lack of awareness and very little conscious deliberation (Liu-Thompkins and Tam, 2013; Olsen et al., 2013). The consumer buys from the same provider because it is convenient (Wu, 2011a), requires less effort (Gray et al., 2017), does not involve consideration of alternatives (Lucia-Palacios et al., 2016), avoids the stress and risks associated with switching providers (Liu-Thompkins and Tam, 2013; Kim and Kang, 2016) and prevents the need to learn new service routines and practices (Wu, 2011a; Kim and Kang, 2016).

Although inertia has the potential to influence consumer behaviour, there is scarce management research addressing the impact of inertia on loyalty (Wu, 2011a; Kim and Kang, 2016; Gray et al., 2017). According to a search conducted by the authors in the Web of Science database, only eight empirical studies have addressed the direct relationship between these variables in service industries. Table 1 is a summary of these studies with authors’ names, research aims, methodologies, main conclusions, and other aspects. This table shows evidence of a significant relationship between inertia and loyalty, which varies from a not very strong influence (0.05) to a strong impact (0.335). The first study, Ranaweera and Neely (2003), found a small but insignificant relationship between inertia and customer retention. However, all other studies found a significant relationship in the expected direction, that is, the higher the inertia, the greater the level of customer loyalty, or the lower the likelihood of switching provider. In all of these studies, inertia has a positive and direct effect on loyalty. Gray et al. (2017) adds that the effect of inertia can last a significant length of time (the researchers conducted two surveys, 11 months apart from each other, and the inertia effects were still in place in the second survey). Lucia-Palacios et al. (2016) further emphasise that the omission of inertia from loyalty models can lead to biased results and, Liu-Thompkins and Tam (2013) concur, ignoring inertia can lead to negative consequences on consumer purchase behaviour, particularly if marketing strategies ignore the specific nature of inertia.

Table . 1

Study Aim Method Industry Main conclusion Coefficient
Gray et al. (2017) Investigate the extent customer inertia switching intent to which PLS-SEM influences brand Cell phone services Inertia has moderating switching direct and effects on intentions 0.08** (absolute value)
Kim and Clarify the effects of user loyalty PLS-SEM Mobile Inertia played a significant 0.258***
Kang (2016) and nonconscious continued use inertia on communication platform role in loyalty but establishing user no effect on
services (e.g.: actual continued use
Lucia- Examine the effect of inertia on PLS-SEM WhatsApp) Cloud services Inertia is one of the main 0.254**
Palacios et al. (2016) the likelihood of cloud services switching to reasons for cloud not switching to services (absolute value)
Liu- Explore the impacts of attitudinal Hierarchical Convenience Attitudinal loyalty and habit 0.05***
Thompkins and Tam loyalty and habit on loyalty and purchase behavioural regression behaviour store retail influence and ignoring repeat purchase inertia can lead
(2013) Lai et al. Extend the customer retention OLS Auto insurance to negative The higher consequences the inertia, the 0.335***
(2011) model with inertia, and switching costs satisfaction Regression analysis service (compulsory greater the retention level of customer
Wu (2011a) Develop a model of loyalty including Hierarchical customer satisfaction and regression insurance) Mobile communication Positive customer effect of inertia on loyalty 0.131**
inertia analysis services
Lin and Sun (2009) Explore the association customer satisfaction of internet CB-SEM and loyalty Internet retail Specific can positively holdup cost (habit) influence e- 0.15***
with specific holdup cost (habit) loyalty, but influence cannot positively e-satisfaction
Ranaweera and Neely Develop a model of retention including Correlation customer inertia, price Phone communication Absence relationship of a linear between inertia 0.038 n.s .
(2003) perception, quality indifference and services and customer not mean retention does absence of a
nonlinear relationship

Note: n.s. Not significant. ** Significant at the 5 percent level. *** Significant at the 1 percent level.

Inertia can be beneficial for service providers. Organisations may create obstacles to prevent customer loss and brand renouncement, which makes customers ‘inert’ in the face of possible change and thus contribute to their loyalty (Lin and Sun, 2009; Pollack, 2017). The removal of these obstacles usually implies some cost, effort or discomfort for the customer and, because of that discomfort, the customer may prefer to remain with their current service provider (Lin and Sun, 2009; Wu, 2011a; Li, 2015; Pollack, 2017). Inertia has been seen as mostly irrational, because it is passive and non-conscious (Olsen et al., 2013), but it might as well be seen as efficient because inertia avoids active planning and the balancing of alternatives at each consumption decision (Olsen et al., 2013). Inertia can be positive for the consumer, because it saves effort but, over time, the deliberate ignorance of alternatives and blind loyalty to a service provider can become detrimental.

In summary, the management literature on the relationship between inertia and loyalty suggests that (1) there can be different degrees of inertia, and (2) inertia can have significant consequences for the consumer and for the service provider. Similarly, in this study, customer inertia is considered as a variable that can assume different degrees and that can affect customer loyalty: the higher the degree of inertia, the higher the resulting level of loyalty. In the healthcare literature, however, there are no studies addressing the relationship between inertia and loyalty. Consequently, besides the literature already reviewed, Maslow’s (1970) theory of human motivation is here used to overcome the lack of research in healthcare and help to hypothesise a relationship between these variables.

According to Maslow, stability (inertia) and freedom from illness (health) are two human needs and part of the larger group of safety needs (level 2 of Maslow’s pyramid): when an individual ‘is taken ill [he] may … develop fear, nightmares, and a need for protection and reassurance never seen in him before’ (Maslow, 1970:40). Until such fears concerning health are relieved – and protection and reassurance are ensured – no progress can be made toward higher levels of the pyramid (Zalenski and Raspa, 2006). This indicates that, when their health is at stake, individuals also look for the protection and reassurance (safety and stability) that result from maintaining the same service provider (inertia). The patients may not wish to abdicate the feeling of safety and reassurance (Maslow, 1970) which results from being cared for by someone familiar. They may feel safe and reassured because they are being cared for by a professional or a healthcare organisation they already know. Consequently, the relationship between inertia and loyalty might be even stronger in healthcare than in other service sectors, because inertia (stability) and health are both needs at a very important level of the Maslow (1970) pyramid. Thus, the first hypothesis is:

H1: Patient inertia positively affects patient loyalty. Individuals identify with social groups (Lee et al., 2010; Tsai and Pai, 2012). This identification involves self-categorisation, which occurs through a person’s comparison of their own defining characteristics (beliefs, education, occupation, preferences…) and those of the group (Lee et al., 2010; Tsai and Pai, 2012). Identification involves also affective commitment, which makes the identification with the reference group stronger, because of feelings of attachment and belonging to the group (Tsai and Pai, 2012). People accept the influence of groups (Ruiz-Mafe, 2016) whose characteristics they share and for whom they feel something (Nitzan and Libai, 2011). This social influence can shape an individual’s awareness, opinions and attitudes (Saleem et al., 2016). The shaping of opinions occurs through information sharing with members of the group in private communications, public communications or mass media (Nitzan and Libai, 2011; Ruiz-Mafe et al., 2016). The internet and online communities are a new means to interact (Tsai and Pai, 2012), which amplifies the social influence of reference groups. Internet and other media can quickly take the group’s views to members and affect their perceptions, attitudes and behaviours (Lucia-Palacios et al. 2016). Through communication, reference groups exert an influence that contributes to align the group members’ behaviours with the norms and standards that the group considers appropriate (Gu et al., 2016). More generally, social interaction with reference groups can influence the adoption of new behaviours by individuals, the continuance of current behaviours and the ending of old behaviours (Nitzan and Libai, 2011). Group conformity can be defined as a social influence through which individuals replicate the beliefs, attitudes and behaviours of a reference group (Hornsey and Jetten, 2005).

Although group conformity has the potential to influence consumer behaviour, little management research has addressed the impact of conformity on customer loyalty (Nitzan and Libai, 2011; Saleem et al., 2016; Toker-Yildiz et al., 2017). According to a search in the Web of Science database, only eight empirical studies have addressed the direct relationship between these variables in service industries. Table 2 is a summary of these studies, indicating authors’ names, research aims, methodologies, main conclusions, and other aspects. This table shows evidence of a significant relationship between group conformity and loyalty. Only one of the studies, Saleem et al. (2016), found an insignificant relationship between conformity and customer retention. All other studies found significant relationships, which varies from a small/medium influence (0.181) to a strong impact (0.586). All of these significant relationships are in the expected direction, that is, the higher the group conformity/social influence, the greater the level of customer loyalty, or the lower the likelihood of defection to a different provider.

Table . 2

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Study Aim Method Industry Main conclusion Coefficient
Toker- Study the impact of online social Bayesian Online wellness Social interactions are more 0.181**
Yildiz et al. interactions and incentives on monetary consumers’ repeat inference, spatial programme effective than monetary incentives when both are (network size)
(2017) Gu et al. usage behaviour Understand the factors that Tobit model PLS-SEM Social present Relational bonds and social 0.190***
(2016) influence users’ continuance networking sites influence affect the continued
intention and loyalty use to and loyalty of individuals specific services
Lucia- Palacios Examine the the likelihood effect of inertia on of switching to PLS-SEM Cloud services The research indicates that social pressure (subjective 0.244**
et al. (2016) cloud services of norms) can explain the usage cloud services
Ruiz- Analyse the role of social CB-SEM Online travel Subjective norm has a direct 0.324***
Mafe et al. influences on towards online loyalty formation travel communities community sites an influence on loyalty towards online travel community
(2016)
Saleem et al. Explore the influence and effects of social other variables on CB-SEM Banking industry Social influence has no direct effect on customer loyalty n.s.
(2016) Tsai and Pai 2012 customer loyalty Investigate how building affects online community development of CB-SEM Online retail Community participation elicits community 0.22***
relationships with customers identification, which in turn influences loyalty intentions
Nitzan and Libai Explore the role social network of customers’ in their defection Survival analysis – Mobile phone communications Social variables increase the explaining power of the 0.586*** (exposure to