Ethics In The Insurance Industry Business Essay

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The term ethics, refers to "A set of moral principles or values, the principles of conduct governing an individual or a group" (Ethics in Insurance, 2009). Business ethics has become a controversial and widely discussed topics recently, mainly due to the illegal acts performed by companies such as Enron and Tyco. Blinded by short term profits, these companies neglect the possible legal risks that they could find themselves in. Falsifying business results, selling nonexistent products, etc. are some of the unethical actions that companies could do. As a result of these careless unethical actions, consumers suffer and lose their trusts in these companies. At that point, a loss in customers' trusts is equal to an eternal loss of business.

Ethics in the insurance industry

The marketing of insurance products is a good topic to investigate business ethics as the intangible and inseparable nature of these products increase the likelihood of ethical abuse (Kennedy and Lawton, 1993).. Also, Diacon and Ennew (1996) considers the fact that there exists an "extensive information asymmetry" (information of products are not fully disclosed to customers) within the insurance industry, and this is another seed for unethical behaviors.

Research question and purpose of this study:

"According to Suisse Romande customers, what are the determinants of ethical sales behavior for insurance professionals? "

While most studies on ethics within the insurance industry have taken an internal view point (investigating the employees), this study will approach the issue externally, prioritizing the customers perceptions. Specifically, this study will investigate whether or not consumers view factors such as Age, Education, Reward System, and Control System (of the employee) impact his ethical sales behavior. A comparison will be made between the internal perceptions ( of people working in insurance industry; done by previous studies) and the external perceptions (the result of this study). This study will also examine if Ethical Selling Behaviors predict Assurance, and if Assurance predict Customer Satisfaction.

The study is conducted in a Suisse Romande setting where most of the respondents are from the French speaking area of Switzerland. This set of respondents was chosen for two reasons: Firstly, Swiss citizens have more experience dealing with the Swiss insurance than expats; secondly, as the research institution (Ecole Hoteliere de Lausanne) is located in the Suisse Romande, it is much easier to gather responses from the same geographic region.

The remaining of this paper will be organized as follows. The following section will summarize previous studies on ethics and customer satisfaction in the insurance industry. Then, the paper will explain the conceptualization model, its latent variables and dimensions and the formulation and testing of hypotheses. Afterwards, the paper will conclude, citing the managerial implications and limitations of this study.

Literature Review:

Ethics in the Insurance industry

Diacon et. al (1996) discusses the vulnerability of the insurance industry to ethical abuses. He believes that several characteristics of the products traded within the insurance industry such as risks, complexity and longevity pose ethical problems for consumers. He takes a conceptual point of view and tries to analyze the ethical issues within the UK insurance industry using the marketing concept of 4 P's:

Product: the product is wrongly marketed and delivered to the customers.

Price: True expense of financial/insurance products are not known for sure until sometime in the future. As such there is a possibility that insurance sellers only discuss the immediate costs such as commission fees to the consumers, while leaving out these future expenses.

Promotion: relates to the discussion of "truth". From a marketing point of view, there are two types of truth. Consumers truth is what consumers believe to be probable while scientific truth has to do with everything that can be proven with facts. By issuing promotional materials that are scientifically true, insurance companies pass the legal test, yet, those materials might not present the consumer truth.

Place (distribution): Most insurance products are sold personally to customers by company's staff. Diacon et. al (1996) identifies Place as the most problematic of the 4P's in fostering ethical abuses. He states that although, a commission based reward system is the best way to increase business as the salesperson only gets paid when he sells a product, it does not guarantee the transactions will be facilitated in an ethical manner. Under the pressure of selling more, the salesperson might undertake unethical behaviors to achieve results.

Sadri (2009) studies the common ethical issues within the Indian Insurance industry. He chooses the middle and high level of management as the study subjects since this group of people derives a high percentage of their earnings from salary. With this reasoning in mind, he hopes that the result of the study will be presented in a less-bias, more ethical manner as this group of respondents is not under the same pressure to sell like the low level salesperson. Questionnaires were used as the main tool of survey and were designed following the 7 P's of service marketing (product, price, place, promotion, physical presence, process). Despite Sadri's speculation, it turns out that even the middle and high level management holds that incentives and bonuses are of higher importance than ethical conducts are.

Roman et. al (2004) studies the determinants of ethical behaviours for insurance employees in Spain using the following model :

The study was conducted internally within in the industry (among the employees).He discovers that reward system, control system, age contributes heavily to the ethical sales behavior of the insurance salesperson. However, education does not. Additionally, another finding of the study is that ethical sales behavior contribute to role-conflict intersender and job satisfaction and does not contribute to job performance.

Servqual and customer satisfaction in the insurance industry

The servqual model was developed by Parasuraman et. al (1985) to measure customer satisfaction in relation to service quality. It has 5 dimensions:

Reliability - the ability to perform the promised service

Responsiveness - the willingness to help customers and provide prompt service

Assurance - the knowledge and trustworthiness of employees

Empathy - the caring, individualized service given to customer

Tangibles - the appearance of physical facilities and employees who provide the service

"Customer satisfaction/dissatisfaction", as defined by Oliver (1997), is "the consumer ' s fulfillment response, the degree to which the level of fulfillment is pleasant or unpleasant". As such, customer satisfaction, in a service area of concern, is indicative of the service quality ( Sidiqui et. al, 2010).

Studies done on customer satisfaction in the insurance industry have used a variety of adapted Servqual model. 2 of the most notable ones are by Sidiquii et. al(2010) and Crosby et. al (1987). (could be found in Appendix 1A and 1B respectively).

Table- Summary of insurance service quality models

Model

Author(s)

Dimensions

Context

SERVQUAL

Parasuraman et. al (1985/88)

Assurance, Empathy, Reliability, Responsiveness, Tangibility

Service quality (basis for insurance service models)

Sidiqui et. al (2010)

Customer service, Personal Contact, Product Information, Direct Company Communication, Company Media Advertising, Customer Service Failure, Satisfaction with Contact Person, Satisfaction with Core Service, Satisfaction with Institution, Overall Satisfaction

Insurance service

Crosby et. al (1987)

Assurance, Personalized Financial Planning, Technology, Competence, Corporate Image, Tangibles, Satisfaction with Agents, Satisfaction with Functional services, Satisfaction with Company, Overall Satisfaction.

Insurance service

Conceptualization

This study's model is an adapted synchronization of the models seen in Roman et. al (2004) and Sidiquii et. al(2010).On one hand, It explores the consumer's perception of the determinants of the ethical sales behavior of the insurance salesperson. On the other hand, from a consumers point of view, it also provides a relationship among ethical sales behavior(of the employee), assurance and overall satisfaction (of the customer)

The chosen control variables are of the most widely used types in sociological/humanities research studies.

Reward System

Education

Age

Customer Satisfaction

Assurance

Ethical Sales Behavior

Control variables:

Gender (Male/Female)

Nationality (Swiss vs. non Swiss)

Geographic (Suisse Romande residents)

Occupation (Student/ Working)

Control System

Chart 1- Main research model

The table below is an example of the questions asked in the questionnaire split up into the various dimensions:

Dimension and latent variables

Reward system

Do you think that commissions have a strong influence on salesman ethical behavior?

Does a salesperson's salary influence their ethical behavior?

Control system

Is it necessary for an insurance company to have a code of conduct?

Does the code of conduct, in your opinion affect employee selling behaviour?

Age

Do you believe that the age of an employee can affect their ethical sales behavior?

Education

Is it general opinion that education is an important factor in an individual's ethics and morality?

Do you feel that education level can have an effect on ethical sales behavior?

Ethical selling behavior

If an insurance salesperson has the right profile according to your perceptions (e.g. highly educated, old, make good earnings, strictly enforced by his company's code of conduct), he will be more likely to conduct business ethically.

Assurance

If an insurance salesperson has the right profile according to your perceptions (e.g. highly educated, old, make good earnings, strictly enforced by his company's code of conduct), he will be more likely to make me feel assured

Customer Satisfaction

.If an insurance salesperson has the right profile according to your perceptions (e.g. highly educated, old, make good earnings, strictly enforced by his company's code of conduct), he will be more likely to satisfy me as a customer

Reward System

The Reward System (RE) is a set of processes that motivate employees towards fulfilling individual and organizational goals (Chonko et. al, 1996). An important point when looking at RE, particularly in the insurance industry, is the distinction between a salary based RE and a commission based RE.

In salary based RE, the sales employee derives most of his earning from his salary. Vice versa, in a commission based RE, he derives most of his earning from commissions. According to John et. al (1989), companies should adopt a salary based RE when they are long term-oriented, gearing towards the future. In contrast, implementation of a commission based RE will allow organizations to reach short term business targets.

Education and Age

It is generally believed that there exists a positive correlation between (Education and Age) and Ethics (i.e., the higher the level of education a person possess, the older he is, the more virtuous he is) (Browing and Zabriskie, 1983; Jones and Gatschi, 1988). In this study, these two variables are included to see if the general belief also holds in the insurance industry.

Control System

This refers to a "set of procedures the organization has for monitoring, directing, evaluating its sales people" (Roman et. al, 2004). Like the discourse of RE, within the discourse of Control System (CS) also exists a long term vs. short term dichotomy. Specifically, the dichotomy is between a behavior based CS and an outcome based CS.

According to Roman et. al (2004), in a behavior based CS, managers clearly state the desired behaviors in addition to the business targets. This also means that employees will be closely supervised and as such, the employees face tremendous risks of punishment when considering performing unethical business conducts. Thus, a behavior based CS discourages unethical actions among employees and is a suitable strategy for companies looking for long term development.

In contrast to the behavior based CS, in an outcome based CS, employees are free to choose whatever methods they want to conducts business as long as the financial goals are met (Roman et. al, 2004). Consequently, companies implementing outcome based CS are exchanging short term financial goals for potential ethical abuses.

Ethical Sales Behavior

This is defined as "fair and honest actions that enable the salesperson to foster long-term relationships with customers based on customer satisfaction and trust" (Roman et. al, 2004). Essentially, taking an ethical approach to sales would mean conducting business while prioritize and take into consideration the benefits of the customers.

Assurance

Being one the dimensions of the Servqual model, Assurance is used in this model as a bridge, connecting ethical sales behavior and customer satisfaction.

As already mentioned in the introduction, due to the highly intangible and inseparable nature of being a service industry, the insurance industry presents a number of risks perceived by the customers. By demonstrating "assurance" (trust, sincerity), corporations could mitigate these risks and increase customer satisfaction.

Utilizing this model, a number of hypotheses can be derived and tested:

H0: Suisse Romande consumers believe that Age of the employee is strongly related to his ethical sales behavior.

H1: Suisse Romande consumers believe that Education of the employee is strongly related to his ethical sales behavior.

H2: Suisse Romande consumers believe that RE of the employee is strongly related to his ethical sales behavior.

H3: Suisse Romande consumer believes that CS of the employee is strongly related to his ethical sales behavior.

H4: From a Suisse Romandes' point of view, ethical sales behavior is strongly related to assurance.

H5: From a Suisse Romandes point of view, assurance is strongly related to customer satisfaction.

Johnson (2011) states that as men and women think quite differently, insurance companies should use different approaches when trying to appeal a product to them. As such, this would prove to be quite interesting to compare perceptions of men and women on the issue of ethical behaviors of insurance sellers:

Women

H6: Female Suisse Romande consumers believe that Age of the employee is strongly related to his ethical sales behavior.

H7: Female Suisse Romande consumers believe that Education of the employee is strongly related to his ethical sales behavior

H8: Female . Suisse Romande consumers believe that RE of the employee is strongly related to his ethical sales behavior.

H9: Suisse Romande consumer believes that CS of the employee is strongly related to his ethical sales behavior.

H10: From a Female Suisse Romandes' point of view, ethical sales behavior is strongly related to assurance.

H11: From a Female Suisse Romandes point of view, assurance is strongly related to customer satisfaction.

Men

H12: Male Suisse Romande consumers believe that Age of the employee is strongly related to his ethical sales behavior.

H13: Male Suisse Romande consumers believe that Education of the employee is strongly related to his ethical sales behavior

H14: Male . Suisse Romande consumers believe that RE of the employee is strongly related to his ethical sales behavior.

H15: Male Suisse Romande consumer believes that CS of the employee is strongly related to his ethical sales behavior.

H16: From a Male Suisse Romandes' point of view, ethical sales behavior is strongly related to assurance.

H17: From a Male Suisse Romandes point of view, assurance is strongly related to customer satisfaction.

Methodology

Study design and Response rate

An online questionnaire was utilized as the primary method of collecting data. Emails with the link to the questionnaire were sent to 100 recipients, carefully selected, making sure they are Suisse Romande residents. After a course of 3 days, 36 people filled out the questionnaire, representing a response rate of 36%.

Here is a demographic breakdown of the respondents:

Demographic profile

 

Frequency

Percent %

Gender

Male

18

50%

Female

18

50%

Total

36

100%

Nationality

Suisse

26

72%

Non Suisse

10

28%

Total

36

100%

Occupation

Student

6

17%

Working

30

83%

Total

36

100%

Questionnaire (Appendix 2)

There are a total of 27 questions on the questionnaire sent out to the participants. Both qualitative and quantitative data were collected following the receiving of the results. Quantitative data will be used for descriptive and causal analysis while qualitative data will serve as background information, potentially lending justifications for data's behavior.

Each item on the questionnaire comes in either a question form or statement form. This simple variety is introduced into this questionnaire as a way to maintain the focus of the participants, so that they will be less distracted while filling it out. Through testing, it is discovered that it would take on average 7 minutes to fill out the questionnaire.

Not all questions from the questionnaire will be used in the data analysis. Also, the responses are based on a 5 point Likert scale, with 1 being "strongly disagree" while 5 is "strongly agree" (Likert, 1932).

Data Extraction Process

Correlations and regression were run via the respective function in Microsof Excel. Dimension were correlated and regressed against each other in order to discover, if there is any causal relationship amongst them. This process was performed 3 times: one was the complete whole data while 2nd and 3rd time was with male and female data.

If a dimension is defined by more than 1 latent variable (thus, having more than 1 set data), an average is taken and this new average will be used to run the regressions and correlations.

Data Analysis

The following section will be broken down into 3 sub- sections, corresponding to the subjects stated in the hypotheses: Suisse Romande (the whole sample), Male Suisse Romande (50% of the sample), Female Suisse Romande (50% of the sample). Each sub-section will further be broken down into 3 parts: structural analysis, correlation, and preliminary conclusion. The structural analysis, applying regression tools, will attempt and justify if the endogenous variables are good enough to determine the exogenous variable. Whereas, the correlation part will determine if there is any trends between the sets of data. The preliminary conclusion will use the results as the basis to evaluate the hypotheses set out in Conceptualization.

1)Suisse Romande

Chart 2 - Correlation and Regression chart for Suisse Romande

Co.ef= 0.157

p =0.088

Co.ef=0.289

Co.ef=0.071

Co.ef = 0.436

Co.ef= 0.075

Co.ef= 0.268

Customer Satisfaction (R2=0.08)

Assurance (R2=0.18)

p-value =0.007

p =0.697

p=0.516

p =0.49

Ethical selling behaviors (R2=0.107)

R

p=0.119

Educationn

Reward System

Control System

Age

a) Structural analysis

With an R2 of 0.107, it can be said that 10.7% of Ethical Sales Behavior could be explained by Age, Education, CS and RE of the employee. For an equation/model to be good (inputs are good predictors of outputs), the R2 value needs to be at least 0.5. At a R2 of 0.107, these 4 variables are not good predictors of Ethical Sales Behavior. This is further backed up by the high p-values (0.49, 0.51, 0.11, 0.69). In another word, Suisse Romandes do not think that the ethical sales behavior of an insurance employee is determined by his age, his education, his CS and his RE.

Additionally, with an R2 of 0.18, it can be said 18% of Assurance could be explained by Ethical Sales Behavior. Although this equation does not have a high R2 value, the p value is exceptionally good at 0.007. The default confidence interval is 95% for most models and as such, a p value of less than 0.05 confirms that the endogenous variable does have an effect on the exogenous variable. Thus, for Suisse Romande consumers, Ethical Sales Behavior demonstrated by the insurance salespersons will make them feel more assured.

Lastly, with an R2 of 0.08 and p value of 0.08, Assurance is not a good predictor of Customers' Satisfaction for Suisse Romande consumers. Applying the theory of Servqual model, although Assurance might not be good indicator of Customer Satisfaction in this case, the remaining 4 dimensions might be (Reliability, Responsiveness, Tangibles, Empathy).

b) Correlation:

With a correlation coefficient of 0.15, 0.07, 0.267, 0.07, there exists weak positive trends between Age, Education, RE, CS and Ethical Selling Behavior.

At a correlation coefficient of 0.43, there exists a minor positive trend between Ethical Selling Behavior and Assurance. A minor positive trend (0.288) also exists for Assurance and Customer Satisfaction. Hence, a general observation can be made: The more ethical sales behavior that an insurance employee demonstrates, the more assured and satisfied the customers will be.

c) Preliminary Conclusion:

Hypotheses H0, H1,H2, H3, and H5 are rejected and only H4 stands.

2)Male Suisse Romande:

Chart 3 - Correlation and Regression chart for Male Suisse Romande

Co.ef= 0.044

p =0.016

Co.ef=0.559

Co.ef=0.22

Co.ef = 0.165

Co.ef= 0.11

Co.ef= 0.007

Customer Satisfaction (R2=0.313)

p-value =0.514

p =0.635

p=0.238

p =0.803

Ethical selling behaviors (R2=0.132)

R

p=0.424

Educationn

Reward System

Control System

Age

Assurance (R2=0.027)

a)Structural Analysis:

Similar to the findings for general Suisse Romande consumers, Male Suisse Romande consumers do not regard Age, Education, CS, RE to be the determinants of Ethical Sales Behavior of the insurance salespersons. This observation is backed up by an R2 of 0.132 and high p-values (0.803, 0.23, 0.42, 0.63).

Interestingly, while Ethical Selling Behaviors is a good predictor of Assurance for the whole sample, it is not for the case of Male Suisse Romande consumers ( R2 = 0.07, p = 0.51). However, with an R2 of 0.31 and a p value of 0.015, Male Suisse Romande consumers link Assurance with Customer Satisfaction.

b)Correlation:

There exists a weak positive trends between RE, CS, Age and Education of the employee to Ethical Selling Behaviors (correlation coefficient of 0.04, 0.22, 0.007, 0.11). A weak positive trend is also observed between ethical selling Behaviors and Assurance. However a strong positive trend (correlation coefficient of 0.55) is observed between Assurance and Customer Satisfaction.

c)Preliminary Conclusion:

H12,H13,H14,H15,H16 are rejected. H17 stands.

3)Female Suisse Romande:

Chart 4 - Correlation and Regression chart for Female Suisse Romande

Co.ef= 0.044

p =0.03

Co.ef=0.511

Co.ef=0.335

Co.ef = 0.193

Co.ef= 0.429

Co.ef= 0.108

Customer Satisfaction (R2=0.26)

p-value =0.442

p =0.039

p=0.093

p =0.099

Ethical selling behaviors (R2=0.401)

R

p=0.222

Educationn

Reward System

Control System

Age

Assurance (R2=0.037)

a)Structural Analysis:

For the case of Suisse Romande consumers, 40% of the insurance employees Ethical Selling Behaviors can be attributed to his Age, Education, CS and RE (R2 = 0.4). Among these attributes, Education of the employee is a good predictor of Ethical Sales Behavior (p-value = 0.039) while Age, CS and RE are not ( p-values are 0.22, 0.09, 0.49, respectively).

Similar to Male Suisse Romande consumers, Female Suisse Romande consumers do not regard Ethical Selling Behaviors to be a strong indicator of Assurance (R2=0.03, p-value= 0.44). However, they do think that Customer Satisfaction can be determined by Assurance (R2=0.26, p-value= 0.03).

b)Correlation:

Similar to the results found for Suisse Romande and Male Suisse Romande consumers, RE,CS, Age and Education are positively correlated to Ethical Selling Behavior (correlation coefficient of 0.099, 0.335, 0.108, 0.42). Ethical Selling Behavior and Assurance also have weak positive correlation relationship (correlation coefficient = 0.19). And finally, Assurance has a strong positive correlation with Customer Satisfaction (correlation coefficient = 0.52).

c)Preliminary Conclusion:

H6, H7, H8, H9, H10 are rejected. H11 stands.

Conclusion

Summary of findings

Based on the results obtaining from the primary research (the questionnaire), most of the hypotheses set out in the Conceptualization section do not stand. After performing correlation and regression analysis, it can be said that the variables in the model do not have a strong relationship with each other. Furthermore, results are inconsistent among the 3 control groups for some variables (Suisse Romande, Male Suisse Romande, Female Suisse Romande). For instance, Education was found to be good predictor of Ethical Selling Behavior for Female Suisse Romandes, yet, it is not the same for Suisse Romandes and Male Suisse Romandes. Another example would be: even though Assurance is good predictor of Customer Satisfaction for Male and Female Suisse Romandes, it is not for the general Suisse Romandes.

A justification for the inconsistent results across the controlled groups could be grounded in the simple notion of "different people think differently". Indeed, each person's general perception is affected by a variety of factors such as upbringing, past relationships, etc. and as such, depending on these factors, each person will hold different sets of beliefs and values. For this study, both quantitative data and qualitative data were collected. While some people would readily tick on a 5 , indicating that they strongly agree to the idea that Age has an impact on Ethical Selling Behaviors, some others would tick only a 2 ("Disagree") and write a short answer such as "Age is not an indicator of ethics… Old people could be immoral and so could young people be as well."

In relation to the secondary research (prior studies), no studies have been conducted on the topic of customer's perception of the ethics of insurance employees. Most studies done on ethics in Insurance Industry usually take an organizational point of view and analyze the related topics in an internal manner. Hence, no direct comparison can be made between the findings from this study and from secondary sources. Moreover, the difference between what customers think and what insurance professionals think are quite significant. Specifically, Roman et. al (2004) found insurance professionals believe Age, CS and RE could predict Ethical Selling Behaviors; yet, this study, coming from a customer's point of view, confirms the opposite and support the notion that these variables are not sufficient to predict Ethical Selling Behaviors.

Research Limitations

Small sample size: Realistically, a sample size of 36 people is far from being representative of the population of the Suisse Romande region in Switzerland. This small sample size will affect the generalizability of the result.

Lack of prior research studies on the topic: As mentioned before, no studies have been done on measuring/determining the customer's perception of ethics in insurance industry. This lack of prior research leads to a lack of methodological and theoretical support and forces the research team to come up with new, untested methods of structuring the questionnaire.

Lack of incentives for respondents: Any form of rewards could have increased the response rate.

Limited access (to the respondents): The main topic of this study is related to perceptions. Perceptions, thoughts and such are qualitative constructs and application of the Likert Scale could give a quantitative measure of this qualitative variable. However, the Likert Scale is strictly a measurement tool and as such it could not reveal why the variable has such a value. Even though responders were given the opportunity to elaborate their answers in a text box, very few chose to do so.

Ideally, as the sample size is quite small (n=36), the respondents could have been called into a room and fill the questionnaire on the spot. Afterwards, a discussion group could be organized to obtain more qualitative data - to know more about the respondents' perceptions.

Managerial Implications

Hiring and Marketing Practice:

With the results from the analysis, although minimal, in the eyes of the consumers, age and education do have an impact on the ethical sales behavior of the insurance employees. Using education as an example, knowing that the Suisse Romande customers value education, a company, if reputable enough could set the hiring bar high and only take in graduates of well-known universities. And when conducting business, if the employee happens to graduate from a famous school, he should either explicitly (introduce himself verbally) or implicitly (hand the customers his name card with his university name printed on top of it) to the customer to make an impression.

Raising Awards and Better Control:

Also from the studies, it is observed that, to a certain degree, Swiss Romande customers do think a better reward system and tighter control system will make employees perform more ethically. So if words got out in the public that a company A has a good CS and is paying its employees high salary, customers might feel more reassured while dealing with company A's employees and when they are more reassured, they will also be more satisfied.

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