“The customer is always right” is a slogan popularized by the management to encourage their staff to take customer complaints seriously (Zikmund & Babin, 2006). The underlying assumption is that customers are always “rational and functional” in their encounters with employees (Harris & Reynolds, 2003).
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While honest customer feedback is vital in improving business services or products and growth, addressing unrealistic expectations and requests can affect employees’ morale, leading to high turnover rates (Ben-Zur & Yagil, 2005). Therefore, business owners should protect staff from deviant customers to improve employees’ satisfaction, increase confidence in their work and reduce turnover intention.
Research shows that there are a variety of factors which affect employees’ turnover intentions. According to Harris and Reynolds (2003), such factors may include consumer aggression, job satisfaction, workload, distributive justice and management style. In-depth research reveals that some of the aforementioned factors have positive influence, whereas others have negative impact on employees’ turnover intentions (Harris & Reynolds, 2003).
The research question for this study is as follows: does customer deviance influence turnover intentions in the service industry?
The objective of the study is to identify the effect of customer deviance on turnover intentions in the service industry.
Research shows that unruly customers cause psychological and emotional stress to staff through verbal abuse, unreasonable requests, and disrespect for company’s policies (Harry & Reynolds, 2003). According to a study conducted by Zikmund and Babin (2006), some customers display verbal aggression that affects employees’ turnover intention.
As employees play a mediating role between employers and customers, they may suffer from emotional exhaustion (Harris & Reynolds, 2003). When employees face aggression and pressure from their employers, they are likely to develop psychological stress. Harris and Reynolds (2003) point out that psychological stress in the workplace undermines staff morale and job satisfaction, which increases turnover.
In this view, Zikmund and Babin (2006) emphasize that support from the management can help staff to deal with hostile clients. Ben-Zur and Yagil (2005) highlight that lack of organizational support and customers’ deviance can cause “burnout, emotional exhaustion, and low self-esteem” among the personnel. This eventually affects employees’ productivity and retention.
Thus, customer deviance coupled with a lack of organizational support, can increase turnover. Research conducted by Zikmund and Babin (2006) also confirms that burnout among employees often occurs due to consumers’ deviance, which leads to undesirable outcomes such as diminished performance, customer dissatisfaction, low commitment to organizational goals and absenteeism.
It is, therefore, beyond a reasonable doubt that burnout directly affects employees’ turnover intentions. It is shown that there are personality resources such as optimism and hardiness that keep employees from burning out due to customer aggression (Zikmund & Babin, 2006). Numerous studies compare the difference in turnover among employees in different employment sectors.
Previous research demonstrates that professionals such as doctors rarely encounter customer aggression; hence they have more job satisfaction than e.g., bank workers and other employees (Harris & Reynolds, 2003). Consequently, doctors are less likely to leave their job or absent themselves from it.
The research conducted by Harris and Reynolds (2003) also shows that the majority of employees in different sectors get little pay and experience pressure from their bosses, yet they are less likely to leave their jobs, in contrast to those who have to cope with customer aggression.
Zikmund and Babin (2006) reiterate that independence in one’s job helps to overcome customer aggression. For instance, while the customer is always right, the doctors can rarely be questioned for their actions, unlike banks and factories employees (Ben-Zur & Yagil, 2005). In other words, professions where workers are protected from customer aggression record low turnover intentions.
The study will test the null hypothesis that there is no difference in turnover intentions between bank employees (front-desk staff) and factory workers.
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Previous researchers have relied on survey methodology in order to obtain anecdotal observations on customer aggression and employees’ turnover intentions (Harris & Reynolds, 2003). Numerous theories presented in the past have been empirically tested through the use of multiple methodologies.
However, research-based studies have been proved to be more reliable. Therefore, the study design will involve a descriptive research design. In this case, the research will be qualitative in nature. The study will have dependent and independent variables. Customer deviance will be used as an independent variable.
On the other hand, there will be key dependent variables in the study. These will include turnover intention, job satisfaction, customer incivility, and organizational/management support. The study will draw its participants from the front desk and management staff that spend most of their working hours interacting with customers responding to their problems, queries and complaints.
Interview method will be used to collect data from the participants. Each respondent will be interviewed in a 15-minute session using semi-structured questions. The key focus will be on customer incivility, management support, and turnover intentions. It is important to highlight that information provided by participants will be treated as confidential. Data analysis will involve thematic analysis method.
The study focuses on employees’ response to customer aggression. Therefore, the sampled participants will strictly include people who are in banking industry and factory jobs. Moreover, the participants must have ample and direct contact with customers. A convenient sample of 25 participants will be picked from the staff of a bank and a factory.
It will consist of 10 front-desk staff (bank), ten factory workers, and five managers/supervisors. The participants will be selected through random sampling. Moreover, the researcher may use simple but stratified method to sample out participants depending on the nature of employment, age, sex and employment duration.
In order to facilitate this procedure, a preliminary request for participation will be sent to the institutions to obtain approval and informed consent. Upon approval, the researcher will schedule the interview dates to collect the data.
Possible Types of Secondary Data
Secondary data for hypothesis testing will be obtained from existing sources when primary data is unavailable. Zikmund and Babin (2006) outline four different forms of secondary data, namely, published data, which include personnel records, government reports, public sector reports, and electronic records.
Journals, books, and periodicals archived in libraries are the major sources of published data (Zikmund & Babin, 2006). These sources will be used to obtain and compare data acquired by different researchers in their study. Data published in periodicals and journals will be preferred since they are often reliable and present-day.
Personnel records will encompass personal communications that can be used as sources of secondary data (Landrum, 2014). Personal letters and diaries can provide information, but efforts must be taken to eliminate any bias they may contain. According to Zikmund and Babin (2006), government reports, particularly “surveys, tax records, and census data”, can also provide secondary data for hypothesis testing (p. 37).
They are widely available on official government websites and databases. In addition, public/private sector reports published by various institutions contain information that can be useful in the research (Landrum, 2014). Documentaries and films provide electronic data that can also be helpful in the study.
To test the study’s hypothesis, the researcher will use more than one type of secondary data (Landrum, 2014). Government reports, newspaper/magazine articles, and private sector reports will be useful sources of secondary data. These sources will provide useful statistics on turnover rates in the banking and manufacturing industries. This will allow the researcher to compare turnover rates between factory and banking staff.
Possible Measurement Benchmarks and Scales
A benchmark indicates the critical point at which the difference between the sample mean and the expected value becomes significant, that is, it supports the null hypothesis (Landrum, 2014). A p-value indicates the acceptable level of significance of a test (Zikmund & Babin, 2006). In most studies, the p-values of 0.1, 0.05, and 0.01 are used as benchmarks for acceptable levels of type I error.
When the value obtained from statistical tests, such as t-test or Z-test, is lower than the benchmark value, it indicates that the difference is significant or the null hypothesis is not supported. According to Zikmund and Babin (2006, p. 155), the main scales used to measure variables include “nominal, ordinal, ratio, and interval” scales. The nominal scale classifies variables into mutually exclusive groups while the ordinal scale organizes data in a ranking order or hierarchy. In an interval scale, the difference between any two values is fixed.
On the other hand, a ratio scale is similar to an interval one, but contains “a true zero point” (Zikmund & Babin, 2006, p. 157). The type of measurement scale to be used in research depends on the nature of the study variables. The proposed research will use a single measurement benchmark, namely, p = 0.05. Higher values than 0.05 will indicate an acceptable level of significance, i.e., the null hypothesis will be accepted.
To measure turnover intentions, job satisfaction, customer incivility perceptions, and organizational support, the study will use the Likert (interval) scale. This scale will provide quantitative differences between the participants’ responses with respect to the four study variables.
As mentioned earlier, data will be obtained from secondary sources such as books, journals, periodicals, government reports, amongst other published materials. Primary data will be obtained from structured interviews.
The researcher will email all the participants in advance in order to explain to them the intent of the study and to assure them about the confidentiality of the information that they are to provide during interviews. Responses given by participants will be entered into the MS-Access database for easier analysis.
A statistical package may be used to analyze data in order to determine the validity of scales used. SPSS and Microsoft Excel will assist in calculating statistical frequencies (Landrum, 2014). Use of hierarchal regression will aid in comparing the effect of independent variable on the dependent variable such as turnover intentions and level of satisfaction. A co-relational analysis will help to establish the relationship between customer’s deviance and employees’ turnover intentions.
Upon examining the behavior of employees in various work environments, the researcher will be able to establish the relationship between customer deviance and employees’ turnover intentions. The researcher will consider all demographic factors such as age, sex, job characteristics and hours of interaction with customers.
Discussion and implications
Depending on the results obtained in the study and the laid objectives, the researcher will be able to make conclusions. Therefore, discussion will be conclusive by approving or disapproving the research hypothesis (Landrum, 2014). The conclusion will determine the implications of the research.
Hence, the researcher will make recommendations based on the research implications. It is worth pointing out that major findings will help to formulate managerial implications such as reinforcement of customer orientation and distributive justice.
Plans for analyzing the obtained data
Upon conducting the interviews with the sampled set of employees, the collected materials will be organized and subjected to thematic analysis in order to find out types of data that occur with certain frequency, which will allow for initial qualitative evaluation of influence of the independent variable (customer deviation) on the dependent variables (turnover intention, job satisfaction, customer incivility, and management support).
The standard data analysis scheme of editing, coding, and filing the information will be used (Zikmund & Babin, 2006, p. 479). After that, the filed information will be evaluated in accordance with Likert scale, and a hierarchical regression will be employed in order to capture the qualitative differences between the responses of the interviewees.
Statistical software can be used to determine the qualitative differences and allow for easier co-relational analysis of the obtained data. The null hypothesis can then be tested using the p-value method.
Plans for analyzing the achieved results
The results will be presented by describing the sampled set of workers, explaining the methodology used in the study, and displaying the results obtained in each of the steps of analyzing the data. The null hypothesis will then be accepted or rejected (depending on the result of the p-value test), and, in case of the positive outcome, the research question (“Does customer deviance influence turnover intentions in the service industry?”) will be answered along with presenting the quantitative results obtained.
Perceived lacunae of the results will be subjected to discussion. The discussion will also include a comparison between the outcome of the research and the data that is present in secondary sources (reports, journal articles, books, etc.) related to the topic, as well as possible explanations for the achieved results. The implications of the study will also be considered, and recommendations based on them will be made.
Ben-Zur, H., & Yagil, D. (2005). The Relationship between Empowerment, Aggressive Behaviours of Customers, Coping, and Burnout. European Journal of Work and Organizational Psychology, 14, 81-99.
Harris, L. C., & Reynolds, K. L. (2003). The Consequences of Dysfunctional Customer Behaviour. Journal of Service Research, 6, 144-161.
Landrum, E. (2014). Research Methods for Business: Tools and Applications. New York, NY: Sage Publishers Inc.
Zikmund, W., & Babin, B. (2006). Essentials of Marketing Research. Mason, OH: Cengage Learning.