Stereotyping is part of the way the brain improves its efficiency. Unfortunately stereotypes of aging are depressingly negative. They have emerged over the last 100 years and are not keeping up with reality. Stereotyping can quickly become discrimination. Researchers must be sensitive to their own stereotypes if they are to avoid ageism in their research.
The global population is undergoing a “once in human history” change. Populations are aging in a way that has never been seen before. The number of people over 65 is exploding as a percentage of the population. In Europe that percentage has gone from 15.4% in 1999 to 20.3% in 2019. It is forecast to rise to 24.7%, by 2030. In all countries in Europe there are now more people over 65 than under 15. The youth markets are declining.
The same forces that are driving these trends are causing populations, and with them markets, to shrink. Across Europe most countries now depend on immigration to maintain their population. The only age segments that are growing are the over 65’s. They are growing not only in numbers but spending power. In the next ten years they will account for 60% of all consumer spending growth in Europe. The “aged market” will become increasingly important to all service businesses.
Not including the over 65’s in “the research sample” will become untenable. Convenience samples of students won’t be acceptable to editors. It is ageist to deny the known differences in consumer behaviour that come with age. We will all have to learn to work with older samples without introducing ageist biases.
The Objective of this Paper
The purpose of this paper is to flag the likely pitfalls. It draws on an emerging literature within neuroscience on the same topic and suggests some solutions.
Our research methodologies are themselves vulnerable to ageism. Within neuro science there is an emerging stream of concern over testing and the over 65’s. The emergence of longitudinal studies has overturned the accepted wisdom drawn from cross sectional work on trends with age. Cross sectional surveys of different age groups will have to argue for the stability of the underlying construct. Many mental, sensual and physical declines are slowing.
Many changes attributed to the ageing brain are due to physical changes in the senses. Declining eye-sight and hearing can significantly skew results. For example, many experiments and studies start with a verbal briefing. Loss of hearing will affect these studies. Services researchers will have to allow for the age related declines of their respondents, especially when studying trends with age.
Inappropriate question format and even location can significantly bias results. Negative ageing stereotypes can be internalized by respondents. An inappropriate survey setting or question structure can trigger “self- ageing”. This is the acceptance of the stereotype and adjusting behaviour accordingly. Neuro- scientists have shown that triggering such self- ageism can influence everything from physical strength to mental ability.

Consumers in online brand communities (OBCs) increasingly engage in undesirable, aggressive behaviors (Dineva and Breitsohl 2021). Whilst a growing number of studies explore hostile Consumer-to-Business (C2B) interactions, including customer misbehavior during service encounter (Harris and Daunt 2013), customer complaints (Istanbulluoglu et al. 2017), and brand sabotage (Kähr et al. 2016), knowledge on hostile Consumer-to-Consumer (C2C) interactions remains limited (Breitsohl et al. 2021). In particular, research on consumers at the receiving end of the hostility, an experience described as cyber-victimization in the psychology literature (Álvarez-García et al. 2017), is scarce. Whilst the negative psychological consequences of cyber-victimization are well-researched, there is a lack of studies that explore consequences related to consumers’ service experience, as highlighted in recent works (Breitsohl et al. 2021, Dineva et al. 2020).

To address this gap, we designed an experiment that explores how cyber-victimization affects three positive service outcomes, namely a victim’s positive word-of-mouth (PWOM) intentions, community satisfaction and community following intentions. Following the cyber-victimization literature (Kowalski et al. 2014), we propose that these outcomes will likely depend upon two contextual factors. First, the perceived severity of victimization incidents, hypothesizing that more severe incidents leading to lower positive service outcomes. Second, the reaction of bystanders (i.e., uninvolved community members who witness the cyber-victimization incident), hypothesizing that positive service outcomes are negatively affected when bystanders reinforce the attacker compared to when they defend the victim (Salmivalli 2010); we also include a novel form of bystander reactions, ‘pretending’, which describes a bystander pretending that he/she did not notice the victimization incident, a phenomenon for which evidence has so far remained anecdotal (Breitsohl et al. 2018).

Using a 2 (victimization severity: severe vs mild) x 3 (bystander reactions: reinforcing vs defending vs pretending) design with 387 service users who were victimized in the past, our results show that, in most cases, consumers in OBCs show lower PWOM intentions, community satisfaction and community following intentions when they are victimized, compared to when they are not. Moreover, when victimization is severe, these outcomes tend to be at their lowest when bystanders engage in pretending, and at their highest when bystanders defend the victim, whilst no significant differences between bystander reactions are found when victimization is mild.

Our findings contribute to the marketing literature by addressing the general lack of knowledge on victims in relation to consumers’ service experience. Furthermore, we offer insights on a novel bystander reaction, pretending, which, surprisingly, turned out to be having the most damaging consequences when victimization was severe. For service practitioners, we offer a first understanding of the undesirable effects of cyber-victimization in online brand communities, and on the type of reactions from bystanders that they may like to encourage.

Successful relationships between health service professionals and patients are key in health care (Frist, 2005). The way health service professionals communicate has been shown to be one of the main aspects patients regard to evaluate their relationship with the doctor (Kenny et al., 2010). Further, successful and thereby relationship-building communication is shown to improve patient health outcomes (Stewart, 1995) and is thereby amongst the primary reasons for treatment success or failure (Landro, 2013). Despite doctor-patient communication’s central role in relationship building in health care, many doctors tend to overestimate their ability in communication (Fong et al., 2010). Poor communication results jeopardize the building of strong relationships and thereby the overall treatment success (Tongue et al., 2005).
At the same time health care professionals are scrutinized online by their patients via customer reviews (Gummerus et al., 2004). These reviews reveal details of the reasons why a patient experienced a particular health service encounter as satisfactory. Patients’ perceptions of the communication and the relationship with the doctor are thus embedded in how the service encounters are described in the verbatim customer reviews. This is in line with research on relational communication. Watzlawick et al., (1967) argue that the relationship between interactant can be assessed by the way of communication. Aspects of communication which define relationships have been specified as relational communication (Millar & Rogers, 1976).
Making use of relational communication theory (Watzlawick et al.,1967) we seek to make three contributions. First, answering the call for more empirical generalizations on relational communication research in health care (Step et al., 2009), we validate the dimensional structure (e.g. dominance, composure as two dimensions) of relational communication within the doctor-patient relationship. Second, overcoming prior’s research’s shortcomings, which found mixed results for the individual relational communication dimensions while using survey and experimental data, using natural language data, we examine which of the relational communication dimension as expressed in the review is most influential for the patient’s perception of the relationship. Third, we corroborate the existence of joint effect of dimensions of relational communication (e.g. dominance and arousal) in doctor-patient communication. Relational communication dimensions are inherently inseparable, which has been confirmed in relationships between friends and strangers (Burgoon & Koper, 1984) indicating the existence of joint effects also in doctor-patient relationships.
We analyze 3,556 customer reviews posted by patients about their interaction with their doctor. Applying text analysis on the verbatim reviews shows that the five relational communication dimensions namely, arousal, composure, intimacy, dominance and task-orientation are present in the patient’s perception of the doctor-patient relationship, which validates the dimensional structure of relational communication in health-related service relationships. From the five relational communication dimensions, arousal, composure and intimacy positively influence patient satisfaction while dominance negatively influences patient satisfaction. The results further show that patients’ perceived arousal is the strongest driver of patient satisfaction. Additionally, our findings provide evidence for the joint effect of some relational communication dimensions. Especially patients’ perceived arousal and dominance together have a strong influence on the overall evaluation of the relationship.

References upon request.

Service encounters are the backbone of service provision, but theoretical models are based on the idea that interactions between frontline employees and consumers are truthful and follow service scripts (Solomon et al., 1985). In a recent study on lying behavior, 92% of the consumers admitted to having told lies in a service encounter in the last 3 months. Their financial gains ranged from $1 (by lying to a grocery store) to $3,000 (by lying to a bank) (Snyder et al., 2022). At the same time, a study of customers revealed that 91% of the customers said that they had been lied to in a recent service encounter, and 57% said that they were lied to on a regular basis. Their financial loss ranged from $5 (paying for a bad meal at a restaurant) to $150 (buying products to escape an awkward sales situation). This suggests that service encounters often are dishonest and that this dishonesty have financial implications for the customer.

Dishonesty is a broad term; often defined as the lack of honesty (Scott and Jehn 1999), and refer to a lack of honor or integrity, cheating, knavishness, corruption, or treachery. The present study focuses on lying as one form of dishonest behavior, which can be defined as “a deliberate choice to mislead a target without giving any notification of the intent to do so” (Ekman 2009, p. 28). The present study builds on and extends existing research of lying behavior by studying characteristics of dishonesty (who is dishonest and about what) and identifies the effects on financial outcomes. It is based on data from 2000 service encounters, where either the customer or the employee have been dishonest. It takes a dual perspective on the service encounters, i.e. a specific dishonest service encounter is viewed both from an employee and a customer perspective.

The purpose of the research is to compare the employee and the customer perspective on dishonesty in service encounters. The underlying assumption is that both actors underestimate the harm of their own dishonest behavior and overestimate the harm of the other actors behavior. In particular, it details service encounters where one actor engages in dishonesty and the other actor choose to respond with further dishonesty. Such dishonest service encounters represent hyperreal service encounters where the service provider has no control of what the outcome will be and how the consumer will react. Based on a theoretical overview and an extensive empirical investigation, the present research provides a number of propositions on dishonesty in service encounters. If dishonesty is as common in service encounters as revealed by previous research, theoretical models must capture this behavior provide guidance for frontline employees and consumers in developing and deploying strategies and scripts to counter this behavior.