Chapter 4 Data Analysis
4.4 Correlation Analysis
4.5.3 Moderation Analysis
Model 1 : Yi=α + β1(G) +β2(R) +εi
Regression 1.0594 (2.386) Residual 139.469
(138.677)
Table 4.22 Regression Analysis of Empathy
Y=Empathy
Table 4.23 Change Statistics of Empathy
Y=Moral Reasoning
Regression 11.124 (11.136) Residual 85.409
(85.397)
Table 4.24 Regression Analysis of Moral Reasoning
Y=Moral Reasoning
Table 4.25 Change Statistics of Moral Reasoning
Full Model Coefficients: Risk Tolerance 0.242
(0.375)
Table 4.26 Coefficients of Full Model
Gender as a moderation variable lies in this regression formula, The information above clearly shows no difference when G×R is involved. On the two factors, empathy and moral reasoning, R square change also vibrates slightly when gender and risk tolerance interaction happened.
4.6 Mediation Analysis
As mentioned of hypothesis 4 in chapter two, risk tolerance is a mediation variable between gender and Sales Helping Behavior. However, the previous regression analysis shows no significant correlation between gender and risk tolerance;
there is no indirect effect. In other words, risk tolerance does not mediate between gender and Sales Helping Behavior. The following figure shows each standardized regression coefficient, but it only exits a direct effect between risk tolerance and Sales Helping Behavior.
Note: * P<0.1; **P<0.05; *** P<0.01
Fig. 4.1 Path Analysis Parameters
4.7 Model-Fit Evaluation
In this section I would like to examine the previous model through LISREL, since there is no significant effect of gender on empathy and moral reasoning.
Moreover, gender is a dummy variable. For these reasons, gender is not adopted in the model. The following coefficients of the figure are standardized solution, but these loadings are computed by MLE (Maximum Likelihood Estimation), which are different from those computed by EFA. The item 「1-1」 of fig. 4.2 stands for the first item of part 1 in the questionnaire, and so on.
The CFA model-fit analysis data shows some good information of the model:
Empathy
Moral Reasoning Sales Helping Behavior -0.031
-0.026
0.339***
0.103*
Risk Tolerance
Gender
-0.053
χ2= 208.15 (74, N=277), df χ2
=2.81 < 3, GFI (goodness-of-fit index) =0.90 is close to 1, AGFI (Adjusted GFI) =0.86 is close to 0.90 and CFI (Comparative Fit Index)
=0.92 > 0.9. Furthermore, NFI (Normed fit index) =0.88 is close to the criterion 0.90, NNFI=0.90 and IFI=0.92 are larger than 0.90, and PNFI is 0.72 larger than 0.5.
Finally, RMSEA (Root Mean Square Error of Approximation) is 0.081 between 0.05 and 0.1. The model is acceptable in all of the mentioned indexes. The data is listed at the end of this chapter.
In order to confirm that gender is not a significant factor to both Sales Helping Behavior and risk tolerance, I split total sample into males and females. First of all, factorial invariance should be examined. Table 4.27 shows that chi-square difference is 21.02 and degree of freedom difference is 11, however, the value is significantly larger than χ(211,0.05)=19.68. It appears that there does not exist factorial invariance between base model (model 0) and model 1. Model 0 combines two separated CFA models into one CFA analysis and each path are freely estimated. Model 1 lets factor loadings be consistent.
Model χ2 df χ2／df RMSEA NNFI CFI GFI
Total 208.15 74 2.81 0.081 0.90 0.92 0.90
Males 84.02 74 1.14 0.037 0.97 0.97 0.89
Females 182.27 74 2.46 0.091 0.86 0.88 0.87 Model 0 266.29 148 1.80 0.076 0.91 0.92 0.86 Model 1 287.31 159 1.81 0.077 0.91 0.92 0.86 △=21.02 △=11
Table 4.27 Multi-Sample CFA Analysis
Although male and female models are different because of factorial variance, the structure of the model does not have significant difference. Since I let path parameters
be consistent to check the chi-square and degree of freedom variance, it appears
△χ2=2.32 and △d.f = 2. But χ(22,0.05)=5.99 > 2.32 shows there is no difference between male and female models. In other words, gender is not a significant factor to this model, and this effect is consistent with prior result estimated by regression.
Males Females Factors Items Loading Residuals Loading Residuals
1-1 0.59 0.66 0.52 0.73 1-2 0.67 0.55 0.53 0.72 1-3 0.47 0.78 0.45 0.80 1-4 0.68 0.54 0.79 0.37 Empathy
1-5 0.72 0.48 0.47 0.78 1-8 0.70 0.51 0.53 0.72 1-9 0.73 0.47 0.66 0.56 1-10 0.76 0.43 0.76 0.43 1-11 0.71 0.49 0.74 0.45 Moral
Reasoning
1-12 0.85 0.28 0.78 0.39 2-2 0.74 0.46 0.36 0.87 2-3 0.74 0.46 0.50 0.75 2-4 0.75 0.43 0.87 0.25 Risk
Tolerance
2-5 0.75 0.43 0.73 0.47 Table 4.28 Multi-Sample Individual CFA Analysis
Fig. 4.2 Path Diagram of CFA Model
Chi-Square=208.15 df=74 P-value=0.000 RMSEA=0.081
Empathy Moral Reasoning Risk Tolerance
1-1 1-2 1-3 1-4 1-5 1-8 1-9 1-10 1-11 1-12 2-2 2-3 2-4 2-5 1-1 1
1-2 0.277 1
1-3 0.242 0.270 1
1-4 0.432 0.418 0.341 1
1-5 0.268 0.376 0.208 0.421 1
1-8 0.010 0.043 0.049 0.008 -0.044 1
1-9 0.070 0.145 0.087 0.081 0.066 0.601 1
1-10 0.112 0.174 0.091 0.014 0.079 0.419 0.548 1
1-11 0.150 0.187 0.085 0.058 0.162 0.328 0.403 0.589 1
1-12 0.205 0.183 0.127 0.101 0.237 0.461 0.510 0.572 0.655 1
2-2 0.084 0.172 0.012 0.064 0.158 0.118 0.203 0.190 0.105 0.174 1
2-3 0.077 0.113 0.085 -0.031 0.039 0.249 0.269 0.240 0.172 0.282 0.551 1
2-4 0.100 0.063 -0.034 0.030 0.115 0.235 0.255 0.226 0.213 0.247 0.349 0.461 1
2-5 0.030 0.047 -0.066 -0.043 0.037 0.188 0.180 0.152 0.181 0.228 0.363 0.361 0.653 1 Mean 2.805 2.610 2.798 2.487 2.260 4.152 4.238 3.935 3.819 4.022 3.736 3.881 3.870 3.860 Std. D 1.112 0.996 0.953 0.946 0.911 0.624 0.666 0.827 0.823 0.807 0.789 0.745 0.652 0.706
Table 4.29 Inter-Item Correlation Matrix
Note: *P<0.05 Fig. 4.3 Path Diagram of CFA Model (Male/Female)
0.76*/0.76*
Male: Chi-Square=84.02 df=74 P-value=0.199 RMSEA=0.037 Female: Chi-Square=182.27 df=74 P-value=0.000 RMSEA=0.091
Chapter 5 Conclusions
Explanation and clarification of each hypothesis, managerial implication, limitation of research and further suggestions for study are presented in this chapter.
5.1 Discussions
The four hypotheses mentioned in chapter two are examined by regression.
Detailed information is provided in the following table:
Hypotheses Test Results
H1: Females tend to engage in more Sales Helping Behavior than males do Rejected (No difference) H2: Salespeople with higher risk tolerance engage in more Sales Helping
Behavior
Supported
H3: Males tend to engage in more Sales Helping Behavior under a risk condition than females do
Rejected (No difference) H4: Risk tolerance mediates between Gender and Sales Helping Behavior, and
the level of significance between Gender and Sales Helping Behavior should be reduced.
Rejected (No difference)
Table 5.1 Summary of Results of Hypotheses
Gender does not significantly influence Sales Helping Behavior. One of the explanations is that salespeople have basic awareness about helping customers because of their professional ethics. Therefore, both male and female salespeople will show willingness when customers need help. According to the reciprocal theory of consumer behavior, people are more likely to give if they receive (Solomon, 2004).
That is why salespeople are willing to help customers; people will buy more if they get help from these salespeople. According to this fact, a successful or unsuccessful salesperson depends on Sales Helping Behavior.
The other independent variable, Risk Tolerance, shows positive correlation with Sales Helping Behavior. As expected, the more risk tolerance salespeople have, the more Sales Helping Behavior they will engage in. However, Gender is still not a significant factor to Risk Tolerance; in other words, both males and females engage in equivalent Sales Helping Behavior under a risky condition because of their professional ethics.
There is one more interesting phenomenon: if there exists an economic factor between SHB and risk tolerance, a spurious relationship may be formed. In other words, further researchers should put “reward” into consideration, because the intention of engaging in Sales Helping Behavior may involve other factors, such as existing relationships between salespeople and customers, length of relationships, and the cost of the benefit.
5.2 Managerial Implications
Salespeople can become closer to customers through engaging in more Sales Helping Behavior. At present, more and more salespeople not only sell products to customers but one also making friends with them. For this reason, salespeople should be more aware of business is not only business and always keep customers’ needs in mind. There has been an increase of studies relating to SOCO (Selling Orientation-Customer Orientation; Saxe et al., 1982), which clarify the relationships between salespeople and customers. The concept of Sales Helping Behavior is similar to SOCO. This study provides a new scheme to enhance the profit for salespeople.
Managers in all companies can give more training to salespeople depending on the results of this study. Accepting more risk tolerance may be an orientation for those who want to be a successful salesperson. Knowing the components of Sales Helping Behavior and engaging in them will improve the relationships between sales and customers. Eventually, companies will earn higher revenue owning to these enthusiastic salespeople.
This study also provides useful information to some foreign companies who would like to enter Taiwan market, because they should know what traits Taiwan’s salesperson has first. Then, they can do more successful promotion through these well-trained salespeople.
5.3 Limitations of This Research
There is few literature discussing Sales Helping Behavior and therefore, are few scales provided for this study. For this reason, there is approximately to improve this scale and cost benefit analysis. Due to the insufficient studies for Sales Helping Behavior, the major components of SHB create restrictions to the research. There is also a risk tolerance measuring problem because the majority of risk tolerance refers to finance. Another constraint is that most of the participants engage in service industry. Hence the sample does not accurately represent the general population. Last but not least, R square of risk tolerance regressing SHB is not big enough to explain the total variance. Therefore risk tolerance is one of the factor influencing SHB, but not a significant one.
5.4 Further Suggestions
Since there are few studies for Sales Helping Behavior, a great deal of improvement needs to be made on this topic. This study explores two major components of Sales Helping Behavior intention (Empathy & Moral Reasoning), however many unknown factors still remain for researchers to discover. Researchers can develop a scale for SHB first, and then find the exact components of it out.
Along with SHB, risk tolerance is also another interesting subject. Although R square of risk tolerance is not large enough to explain more variance, it still has significant influence on Sales Helping Behavior. Researchers can explore more risk tolerance items to make sure of the effect, and develop sales risk tolerance scale. This study faces many difficulties in measuring because there are few suitable scales for this subject.
For further research, specific groups of Sales Helping Behavior need to be examined, such as service industry. Different industries may show different behavior facing customers, especially for the B2C segment group. Specific study will expand the scale to better explore the differences among various industries. Also, Table 4.16 indicates, some significant influences of demographic variables exist on dependent and independent variables. It provides a way to develop new variables on how to measure SHB. Smith et al. (1983) also explored that Educational level; Job Satisfaction and Urban/Rural background positively correlated with Altruism. In conclusion, developing suitable scales for SHB needs to be a direction for further research; recognizing that service industry have significant differences on empathy and moral reasoning compared to non-service groups (For empathy, p=0.061*; for Moral Reasoning, p=0.018**; *P<0.1, **P<0.05). Moreover, exploring more components of Sales Helping Behavior intention will provide more interesting and
beneficial results. Finally, how to make SHB to be learned benefit is another topic for those interesting in Sales Helping Behavior.
Reference
Aaker, David A., Keller, Kevin Lane (1990). “Consumer Evaluations of Brand Extensions.” Journal of Marketing 54: 27-41.
Ansic, M. P. D. (1997). "Gender difference in risk behavior in financial
decision-making: An experimental analysis." Journal of economic psychology 18:
605-628.
Aries, E. J., Johnson, F. L. (1983). "Close friendship in adulthood: Conversational content between same-sex friends." Sex Roles 9: 1183-1196.
Assael, M. (1981). "Consumer behavior and marketing action." Kent Publishing Co., Boston, MA,: 80.
Bar-Tal, D. (1985-1986). "Altruistic motivation to help: Definition, utility and operationalization." Humboldt J. Soc. Relat(13): 3-14.
Baumann, D. J., Cialdini, R. B., Kenrick, D. T. (1981). "Altruism as hedonism:
Helping and self-gratification as equivalent responses." Journal of personality and social psychology 40: 1039-1046.
Bendapudi Neeli; Singh S. N., & Bendapuri Venkat (1996). "Enhancing helping behavior: An intergrative framework for promotion planning." Journal of marketing 60: 33-49.
Borofsky, G. L., Stollak, G. E., Messe, L. A. (1971). "Sex difference in bystander reactions to physical assault." Journal of experimental social psychology 7: 313-318.
Brief, A. P. and S. J. Motowidlo (1986). "Prosocial organizational behaviors."
Academy of management journal 11: 710-725.
Carlson, Michael and Miller, Norman (1987). "Explanation of the relation between negative mood and helping." Psychological Bulletin 102: 91-108
Chang, C.-C. and S. A. Devaney (2001). "Determinants of objective and subjective risk tolerance." Proceedings of the associaiton for financial counseling and planning education.
Cialdini, R. B., M. Schaller, D. Houlihan, K. Arps, F. Fultz, and A. Beaman (1987).
"Empathy-based helping: Is it selfishly or selflessly motivated?" Journal of personality and social psychology 52: 749-758.
Clark, M. S., Isen, A. M. (1982). "Toward understanding the relationship between feeling states and social behavior." Cognitive social psychology(78-108).
Cordell, D. M. (2002). "Risk tolerance in two dimensions." Journal of financial planning.
Darmon, Rene Y., Rigaux, Benny P., Balloffet, Pierre (2003). "Designing sales force satisfying selling positions: a conjoint measurement approach." Industrial marketing management 32: 501-515
Dion Paul A., Banting P. M. (2000). "Compariosns of alternative perceptions of sales performance." Industrial marketing management 29: 263-270.
Eagly, A. H., Crowley, M. (1986). "Gender and helping behavior: A meta-analysis review of the social psychological literature." Psychol. Bull 100: 283-308.
Eisenberg, N., McCreath, H., Ahn, R. (1988). "Vicarious emotional responsiveness and prosocial behavior: Their interrelations in young children." Personality and Social Psychology Bulletin 14: 298-311.
George, J. M. (1998). "Salesperson mood at work: implications for helping customers." The journal of personal selling & sales management 18: 23-30.
George, J. M. (2000). "Emotions and leadership: the role of emotional intelligence."
Human relations: 1027-1055.
George, J. M.; Brief, A. P. (1992). "Feeling good- doing good: A conceptual analysis of the mood at work-organizational spontaneity relationship." Psychological Bulletin 112: 310-329.
George, J. M. (1991). "State or trait: Effects of positive mood on prosocial behaviors at work." Journal of applied psychology 76: 299-307.
Gilbert A. Churchill, J. (1979). "A Paradigm for Developing Better Measures of
Marketing Constructs." Journal of Marketing Research (JMR) 16.
Grable, J. E.; Lytton, R. H. (1998). "Investor risk tolerance: Testing the efficacy of demographics as differentiating and classifying factors." Financial Counseling and Planning 9: 61-73.
Harris, M., & Bays, G. (1973). "Altruism and sex roles." Psychological Reports 32:
1002.
Jones, Gareth R., George J. M. (1998). "The experience and evolution of trust:
Implications for cooperation and teamwork." Academy of management review 23:
531-546.
Kevin E. Voss, E. R. S., Bianca Grohmann (2003). "Measuring the hedonic and utilitarian dimensions of consumer attitude." Journal of Marketing Research (JMR):
310-320.
Kwaku, Atuahene-Gima (1997). "Adoption of new products by the sales force: The construct, Research propositions, and managerial implications." J PROD INNOV MANAG 14: 498-514
McCabe, M. R. (2002). "The relationship between sex differences and helping behavior of college students."
McColl-Kennedy, J. R., C. S. Daus, et al. (2003). "The role of gender in reactions to service failure and recovery." Journal of service research 6: 66-82.
Mckim, R. A. (1992). "Risk management-back to basics." Cost engineering 34.
Mitchell, V.-W. (1992). "Understanding consumers' behavior: Can perceived risk theory help." Management decisions 30.
Moncrief, W. C., E. Babakus, et al. (2000). "Examining gender differences in field sales organizations." journal of business research(49): 245-257.
Organ, D. W. (1988). "A restatement of the satisfaction-performance hypothesis."
Journal of management 14: 547-557.
Peter, J. P., Ryan, M. J. (1976). "An investigation of perceived risk at the brand level."
Journal of Marketing Research (JMR) 13: 184-188.
Piliavin, Jane Allyn; Charng, H.-w. (1990). "Altruism: A review of recent theory and research." Annual review of sociology 16: 27-65.
Roszkowski, M. J., Snelbecker, G. E., & Leimberg, S. R. (1993). "Risk-tolerance and risk aversion." The tools and techniques of financial planning 4th ed.: 213-225.
Roszkowski, Michael J.; Davey G., Grable John E. (2005). "Insights from psychology and psychometrics on measuring risk tolerance." Journal of financial planning 18.
Saxe, R., Weitz., B. A. (1982). "The SOCO Scale: A Measure of the Customer Orientation of Salespeople." Journal of Marketing Research 19: 343-351
Schneider, S., Lopes, L., (1986). "Reflection in preferences under risk: Who and when may suggest why." Journal of experimental psychology: Human perception and performance 12: 535-548.
Smith, C. Ann, Organ Dennis W., and Near, Janet P., (1983). "Organizational
citizenship behavior: Its nature and antecedents." Journal of Applied Psychology 68:
653-663
Solomon, M. R. (2004). "Consumer behavior: Buying, having and being." 254.
Sparks, B. V. C. (1997). "Communication in the service provider-customer
relationship: The role of gender and communication strategy." Journal of Hospitality and Leisure Marketing 4: 3-23.
Sung, J.; Hanna, S. (1996). "Factors related to household risk tolerance: An ordered profit analysis." Consumer Interest Annual 42: 227-228.
Switzer, C. L., Switzer, G. E., Stukas, A. A., &Baker, C. E. (1999). "Medical students motivations to volunteer: gender differences and comparisons to other volunteers."
Journal of Prevention & Intervention in the community 18: 53-64.
Wilson, D. W., & Kahn, A. (1975). "Rewards, cots, and sex differences in helping behavior." Psychological Reports 36: 31-34.
Wright, C. W. (1996). "An examination of the influence of mood, procedural justice and prosocial personal of organizational citizenship behavior."
Chung Yen Y, Ding, C. G. (2002). "Development of the sales locus of control scale."
Journal of occupational and organizational psychology 75: 233-245.
邱皓政著 (2003)，結構方程模式：LISREL 的理論、技術與應用，雙葉書廊
Appendix 1 Chinese Questionnaire
第二部份
第三部份
以下我們還需要您的基本資料，請您放心填寫，以下的資料僅供本問卷統計之用，我們 將完全保密。
1. 您的性別？ □男 □女
2. 您的婚姻狀況？ □未婚 □已婚（有 個小孩）
3. 您所從事的產業？ □保險業 □金融業 □科技業 □仲介業 □服務業 □其他行業 ___________
4. 您的學歷？ □國中以下 □高中職／五專 □大學／專科 □碩士 □博士 5. 您擔任銷售人員多久？ □一年以內 □一年～兩年 □兩年～三年
□三年～四年 □四年～五年 □五年以上 6. 您目前在任職單位中擔任的職位？ □自行創業 □一般職員 □主管
□顧問／幕僚 □研究人員 □其他____
7. 您的年齡？ □20 歲以下 □21~25 歲 □26~30 歲 □31~35 歲 □36~40 歲 □41~45 歲 □46~50 歲 □51 歲以上
8. 您平均一個月的薪水多少(包含分紅獎金)？
□三萬以下 □三萬～四萬 □四萬～五萬 □五萬～六萬 □六萬以上
9. 您平均一個月拿到的分紅獎金約佔全部薪水的多少？ □0%~10% □10%～20%
□21%～30% □31%～40% □41%～50% □51%以上
10. 您過去的成長經驗 □非常不順利 □有一些小挫折，但還稱得上順利 □一直以 來都非常順利
11. 您目前的工作地點 □新竹以北 □苗栗～雲林 □嘉義以南 □宜花東 12. 您主要負責的客戶為 □公司客戶（B to B） □一般客戶（B to C）
本問卷到此結束，請您再次確認每個問項是否均有填寫；非常感謝您的參與，您的寶貴意見 將對本研究有莫大助益。
祝您 萬事順心 工作順利
Appendix 2 English Questionnaire
The first part
1.When customers are nasty to me, I feel very little responsibility to treat them well
１ ２ ３ ４ ５
2. I sometimes find it difficult to see things from customers’ point of view
１ ２ ３ ４ ５
3. Other customers’ purchase-related misfortunes do not usually disturb me a great deal
１ ２ ３ ４ ５
4. If I’m sure I’m right about something, I don’t waste much time listening to other customers’ arguments
１ ２ ３ ４ ５
5. When I see customers being treated unfairly, I sometimes don’t feel very much pity for them
１ ２ ３ ４ ５
6. I would feel obligated to do a favor for customers who needed it, even though they had shown no gratitude for past favors
１ ２ ３ ４ ５
7. When dealing with customers, I would describe myself as a pretty soft-hearted person
１ ２ ３ ４ ５
8. When dealing with customers, I choose alternatives that are intended to meet customers’ needs
１ ２ ３ ４ ５
9. When dealing with customers, I choose a course of action that maximizes the help other customers receive
１ ２ ３ ４ ５
10.When dealing with customers, I choose a course of action that considers the rights of all customers involved
１ ２ ３ ４ ５
11. My decisions are usually based on concern for the welfare of customers
１ ２ ３ ４ ５
12. When dealing with customers, I choose alternatives that minimize the negative consequences to customers
１ ２ ３ ４ ５
13. I help a customer who I don’t know that well with a
product-unrelated problem when my knowledge is greater than his or hers
The second part
1. If possible, I will not actively promote new products because I’m afraid that the bad sales performance will influence my bonus.
１ ２ ３ ４ ５
2. I like to promote new products because it’s challenge. １ ２ ３ ４ ５ 3. I would spend my effort to study how to promote new
products, no matter what the products are hot in the future.
１ ２ ３ ４ ５
4. I will still promote products as usual even though I don’t think many people will buy them.
１ ２ ３ ４ ５ 5. I will still promote products as usual even though I
expect that customers will only buy a small number of products.
１ ２ ３ ４ ５
6. There are two kinds of products following. Which one do you prefer to sell?
One can contribute high premiums with unstable sale quantities. The other can contribute low premiums with stable sale quantities.
7. Please evaluate your level of risk tolerance?
Low premiums stable sale quantities
High premiums unstable sale quantities
Risk Averse
Risk Lover Strongly
disagree (1)
Strongly agree (5)