The ‘customer is always right’ is a slogan popularized by the management to encourage staffs to take customer complaints seriously (Zikmund & Babin, 2006). This view assumes that customers are always “rational and functional” in their encounters with employees (Harris & Reynolds, 2003). While honest customer feedback is vital in improving business services or products and growth, addressing unrealistic expectations and requests can affect employee morale, leading to high turnover (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 intentions. Research has shown that there are factors that affect employees’ turnover intensions. According to Harris and Reynolds (2003), such factors may include consumer aggression, job satisfaction, workload, distributive justice and management style. In-depth research has shown that some of the aforementioned factors have positive influence whereas others have negative impact on employee turnover intensions (Harris & Reynolds, 2003).
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The research question for this study is; 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 intensions 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), there are customers who have verbal aggression that affects employees’ turnover intention. It is important to note that employees play a mediating role between employers and customers hence 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 lowers staff morale and job satisfaction, which increase turnover. In this view, Zikmund and Babin (2006) admit that support from the management can help staff deal with challenging customers. Ben-Zur and Yagil (2005) highlight that lack of organizational support and customers’ deviance can cause “burnout, emotional exhaustion, and low self-esteem” among staffs. 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 occurs due to customers’ deviance leading to undesirable outcome such as diminished performance, customer dissatisfaction, low commitment to organizational goals and absenteeism. It is therefore beyond reasonable doubt that burnout directly affects employee turnover intensions. Evidences have shown that there are personality resources such as optimism and hardiness that help employees from burning out due to customer aggression (Zikmund & Babin, 2006). Numerous researches have been done to compare the difference in turnover among employees in different employment sectors. Previous research has shown that professionals like doctors rarely encounter customer aggression hence they have more job satisfactions unlike bankers and other employees (Harris & Reynolds, 2003). Consequently, doctors are less likely to leave their jobs or absent themselves from work. Research conducted by Harris and Reynolds (2003) has also shown that majority of the employees in different sectors get little pay and experience pressure from their bosses yet they are less likely to leave their jobs unlike those whose major issue is coping with customer aggression. Zikmund and Babin (2006) reiterate that independence in ones job helps to overcome customer aggression. For instance, in as much as a customer is always right, the doctors can never be questioned for their actions unlike employees in banks and factories (Ben-Zur & Yagil, 2005). In other words, professions where workers are protected from customer aggression record low turnover intensions.
The study will test the null hypothesis that there is no difference in turnover intentions between bank employees (front-desk staff) and factory workers.
Previous researchers have relied on survey methodology in order to obtain anecdotal observation on customer aggression and employees’ turnover intensions (Harris & Reynolds, 2003). Numerous theories presented in the past have been empirically tested through 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 are 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 staffs that spend most of their hours interacting with customers responding to their problems, queries and complaints.
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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 with confidentiality. 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 sampled from the staff of a bank and a factory. It will consist of 10 front-desk staff (bank), 10 factory workers, and 5 managers/supervisors. The sampled participants will be derived 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 are unavailable. Zikmund and Babin (2006) outline four different forms of secondary data, namely, published data, 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 compiled by different researchers in their study. Data published in periodicals and journals will be preferred since they are often reliable and current. 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 in official government sites and databases. In addition, public/private sector reports published by various institutions contain information that can be useful in research (Landrum, 2014). Documentaries and films provide electronic data that can be useful in research.
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 keyed into the MS-Access database for easier analysis.
A statistical package maybe used to analyze data in order to determine the validity of scales used. SPSS and Micro-soft 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 intensions 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 intensions. 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.
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: Sage Publishers, Inc.
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Zikmund, W., & Babin, B. (2006). Essentials of Marketing Research. Mason, OH: Cengage Learning.