Influence of problematic customers on employees emotional exhaustion and turnover intentions

UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business LE HA THU INFLUENCE OF PROBLEMATIC CUSTOMERS ON EMPLOYEE’S EMOTIONAL EXHAUSTION AND TURNOVER INTENTIONS MASTER OF BUSINESS (Honours) Ho Chi Minh City – Year 2014 UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business LE HA THU INFLUENCE OF PROBLEMATIC CUSTOMERS ON EMPLOYEE’S EMOTIONAL EXHAUSTION AND TURNOVER INTENTIONS ID: 22120032 MASTER OF BUSINESS (Honours) SUPERVISORS: PROF DR NGUYEN DONG PHONG Ho Chi Minh City – Year 2014 ABSTRACT Basically, the research not only examines the effect of problematic customers verbally and nonverbally on employees, which can lead to job dissatisfaction and turnover intention, but also to see if perceived organizational justice moderates the influence and to what extent By utilizing a sample of 369 customer service officers in Ho Chi Minh City, Cronbach’s alpha reliability analysis, EFA and multiple regression analysis function was used to have the most accurate data The study results illustrate strong interactions of both abusive and unreasonably demanding customers with employees’ emotional exhaustion It also proves that affecting emotional side of staffs could lead to job satisfaction and turnover intention simultaneously Fortunately, perceived organizational justice negatively moderates the relationship between unreasonably demanding customers and emotional exhaustion of employees Overall, the results help managers to view the organizational dynamic from perspective of staffs Furthermore, Vietnamese enterprises should start to apply more training sections on client service in general and fair and sensible working procedure in specific to balance customer-employee relationship Although there are some limitations in the paper, valuable directions for future and further researches are available Key words: problematic customers, emotional exhaustion, job satisfaction, turnover intention, perceived organizational justice TABLE OF CONTENTS Chapter INTRODUCTION 1.1 Research background 1.2 Research problem 10 1.3 Research objectives 11 1.4 Research scope 11 1.5 Research contributions and implications 11 1.6 Structure of the thesis 11 Chapter 13 LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 13 2.1 Theoretical background 13 2.1.1 Problematic customers 13 2.1.2 Problematic customers and Emotional exhaustion 14 2.1.3 Emotional exhaustion and Turnover intentions for customer-related activities .15 2.1.4 Emotional exhaustion and Job satisfaction for customer-related activities 16 2.1.5 Job satisfaction and Turnover intentions for customer-related activities .16 2.1.6 Perceived organizational justice (POJ) 17 2.2 Proposed model 19 2.3 Hypotheses summary 19 2.4 Chapter summary 20 Chapter 22 RESEARCH METHODOLOGY 22 3.1 Research design process 22 3.2 Measurement scales 23 3.3 Sampling .27 3.3.5 Data collection method 28 3.3.6 Data analysis method 28 3.4 Chapter conclusions 30 Chapter 31 4.1 Sample analysis 31 4.1.1 Sample description and data clearance 31 4.1.2 Demographics of respondents 31 4.2 Measurement reliability and validity 33 4.2.1 Cronbach’s alpha analysis 33 4.2.2 Exploratory factor analysis (EFA) 35 4.2.3 Regression analysis 40 4.2.4 Final model and Chapter summary 46 Chapter CONCLUSION AND RECOMMENDATIONS 47 5.1 Findings and discussion 47 5.2 Implications and recommendations 48 5.3 Limitations and future research direction .49 References 50 QUESTIONNAIRE 60 APPRENDIX – DESCRIPTIVE INFORMATION 70 APPRENDIX – CRONBACH’S ALPHA 71 APPRENDIX - RESULTS OF MULTIPLE LINEAR REGRESSION 89 LIST OF TABLES Table Survey item summary 23 Table Sample characteristics 32 Table Cronbach's alpha reliability test result .34 Table EFA results – Scales without modification 36 Table KMO and Bartlett’s Test for all variables 38 Table The result of multiple linear regressions of all independent variables and Emotional exhaustion 40 Table The result of simple linear regressions of Emotional exhaustion and Job satisfaction 42 Table The result of multiple linear regressions of Emotional exhaustion and Job satisfaction as independent variables and Occupational turnover as dependent variable 44 LIST OF FIGURES Figure The proposed research model 19 Figure Research design process 22 Chapter INTRODUCTION The chapter contains five sections The first part introduces the background of research, where and why this research takes place Secondly, the purposes of this thesis and the research scope are informed in the chapter Next, some contributions and implications are mentioned And finally, the research structure is addressed at the end of this chapter 1.1 Research background Since 1909, the famous motto of Harry Gordon Selfridge about customer satisfaction “Customer is always right” has been widely used by every business in customer service sector or department Started from the basic idea that customer complaints should be taken seriously, customer satisfaction has become a critical element for a successful organization Many researchers have explored the link between customer satisfaction and business performance in both firm-level and macro-level analysis (Williams & Naumann, 2011) Employees are coached and trained to be fully aware of meeting customers’ requirements However, the pressure of satisfying these needs sometimes can be stressful, for example in Vietnam, the level of employee intent to stay in the organization is lower than those of other countries in the Asia Pacific Region, although the employee engagement level of Vietnamese companies is much higher (Ruge, 2011) According to Ruge in the presentation to the America Chamber of Commerce in February of 2011, the most possible cause for this can be excessive workload and job pressure Moreover, the highest rates of employee turnover go to Business, Technical support and Production, Operation support with average 12% and 17% in the report for Vietnam Labor Market Overview and Trends (Lu, 2012), which are positions have the most interactions with customers This is beyond common job satisfaction Basically, it is not only about job security, benefits and opportunities for development but also about the feeling that they are respected and protected from verbally abused, threatened with violence or even physically attacked The significance of employee engagement, nevertheless, is not usually considered as an objective for organizations Achieving customer satisfaction, on the other hand, is often the ultimate goal for managers, particularly those in service industries as evidenced by the emphasis on customer satisfaction survey Meeting the demands of customers as much as possible is one of the solutions since satisfaction is based on a customer’s experience of the extent to which a provider fulfills his or her expectations (Gerpott et al, 2001) Nonetheless, not every requirement can be met immediately and be the reason to have unpleasant or problematic customers (Grandey et al, 2004) There is a claim that the bigger customers are the more demanding they become and sometimes, the more unreasonable they can be This happens due to the unequal power between customer-employee relationships as “the customer is always right” and occurs aggression from customers (Allen and Gilbert, 2002, p.551).Unfortunately, most studies, such as Chinh and Anh (2008), Burrows et al (2009), Hau and Thuy (2012), on customer-employee relationship in Vietnam have disregarded the mental side of employees while overestimating the customers’ behaviors and opinions Therefore, these factors can cause emotional exhaustion for customer service officers, who have to deal face-to-face with this problem every day The employee commitment to customer-oriented activities can be negatively affected, which potentially leads to employee turnover Although they want to stay in the company, will they be still willing to customer-related tasks, or will they just leave and find another career path which can be less stressful? In such cases, the role of managers and companies in handling complaints and solving customer-related issues is extremely critical There are possibilities that organizational considerations can moderate these problems by perceived organizational support or justice, which have been demonstrated in various studies about perceived organization justice and work-related attitudes (Elamin, 2012; Howard and Cordes, 2010) Another problem that managers have to overcome as a consequence of emotional exhaustion is low organizational performance As there are several evidences for the positive effects of employee engagement on business performance (Schneider, Macy, Barbera and Martin, 2009), it is said that engaged employees produce ROA, profits and market value that exceeds the replacement costs of assets Starting from high employee retention, businesses will have to spend more cost and time for training new employees who may not be up to par the old ones Since the service quality is unstable, productivity will get worse and customers cannot be happy with bad service In China, there are few studies have been processed based on the interactions of customer behaviors and employee emotional response to observe their influences on the service quality and business performance However, to be the best of our knowledge, in Vietnam nowadays, the problem has not been investigated seriously and been found in not many papers 1.2 Research problem Nowadays, every business is aware of the essentiality of customers to their operations and existence And Vietnamese organizations also acknowledge this matter This requires full researches from various aspects of the firms, which include the interactions between customers and the ones who directly provide the care and service – customer service officers Unfortunately, as mentioned previously in the last session, for Vietnam market, there are a large number of local studies from clients’ perspective but not so many from employees’ side It is extremely significant to understand the effect of customers, especially over demanding ones, on staffs and how to deal with them Will it actually relate to employee’s emotions and to what extend? Will it cause a more serious problem for a business – turnover intention? Therefore, it is indispensable to investigate influence of problematic customers on employee’s emotional exhaustion and turnover intentions Scale: EMOTIONAL EXHAUSTION KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Approx Chi-Square Sphericity df Sig Factor Total 5.045 749 580 548 388 296 234 161 1918.494 28 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings % of Cumulative % of Cumulative Variance Total % Variance % 63.060 63.060 4.653 58.165 58.165 9.360 72.421 7.250 79.671 6.849 86.520 4.850 91.369 3.698 95.068 2.926 97.993 2.007 100.000 Extraction Method: Principal Axis Factoring a Factor Matrix Factor EE1 712 EE2 789 EE3 648 EE4 676 EE5 887 EE6 671 EE7 816 EE8 863 Extraction Method: Principal Axis Factoring factors extracted iterations required .899 Scale: DISTRIBUTIVE JUSTICE KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Approx Chi-Square Sphericity df Sig Factor 703 387.634 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings % of Cumulative % of Cumulative Total Variance Total % % Variance 2.192 73.050 73.050 1.804 60.148 60.148 476 15.857 88.907 333 11.093 100.000 Extraction Method: Principal Axis Factoring a Factor Matrix Factor DJ1 697 DJ2 857 764 DJ3 Extraction Method: Principal Axis Factoring a factors extracted 12 iterations required Scale: PROCEDURAL JUSTICE KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Approx Chi-Square Sphericity df Sig .889 2703.660 28 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Factor Total 5.799 560 515 373 280 207 166 100 % of Variance 72.485 6.997 6.440 4.665 3.500 2.592 2.070 1.252 Cumulative % 72.485 79.482 85.922 90.587 94.087 96.679 98.748 100.000 Extraction Method: Principal Axis Factoring a Factor Matrix Factor PJ1 PJ2 PJ3 PJ4 PJ5 PJ6 PJ7 PJ8 718 828 771 866 892 791 899 850 Extraction Method: Principal Axis Factoring a factors extracted iterations required Total 5.498 % of Variance 68.723 Cumulative % 68.723 Scale: OCCUPATIONAL TURNOVER INTENTION KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Approx Chi-Square Sphericity df Sig .735 754.508 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Factor Total 2.526 313 161 % of Variance 84.195 10.435 5.370 Cumulative % 84.195 94.630 100.000 Extraction Method: Principal Axis Factoring a Factor Matrix Factor OT1 923 OT2 791 908 OT3 Extraction Method: Principal Axis Factoring a factors extracted iterations required Total 2.302 % of Variance 76.740 Cumulative % 76.740 Scale: JOB SATISFACTION KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Approx Chi-Square Sphericity df Sig Factor Total 2.777 712 344 167 795.319 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings % of Cumulative % of Cumulative Variance Total % Variance % 69.420 69.420 2.460 61.498 61.498 17.794 87.213 8.609 95.823 4.177 100.000 Extraction Method: Principal Axis Factoring a Factor Matrix Factor JS1 579 JS2 948 JS3 884 JS4 667 Extraction Method: Principal Axis Factoring a factors extracted 10 iterations required .737 Scale: ALL VARIABLES KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Approx Chi-Square Sphericity df Sig .781 12611.757 528 000 Total Variance Explained Initial Eigenvalues Factor 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Total 11.111 5.897 2.437 2.064 1.647 1.213 1.043 891 758 673 604 532 473 424 371 339 297 291 260 222 207 204 183 171 % of Variance 33.668 17.869 7.386 6.256 4.991 3.676 3.162 2.699 2.297 2.038 1.831 1.612 1.434 1.284 1.123 1.028 899 881 788 674 628 619 554 517 Cumulative % 33.668 51.538 58.924 65.180 70.171 73.847 77.009 79.708 82.005 84.043 85.875 87.487 88.920 90.204 91.327 92.356 93.255 94.136 94.924 95.597 96.226 96.845 97.399 97.916 Extraction Sums of Squared Loadings % of Cumulative Variance Total % 10.844 32.861 32.861 5.595 16.954 49.815 2.159 6.542 56.358 1.784 5.407 61.765 1.389 4.210 65.975 891 2.699 68.674 785 2.379 71.053 Rotation Sums of Squared a Loadings Total 8.344 8.785 4.432 6.410 4.100 4.282 4.435 25 144 437 98.352 26 131 398 98.751 27 112 340 99.091 28 079 239 99.330 29 059 178 99.508 30 051 155 99.663 31 041 126 99.788 32 039 118 99.906 33 031 094 100.000 Extraction Method: Principal Axis Factoring a When factors are correlated, sums of squared loadings cannot be added to obtain a total variance a Pattern Matrix Factor AC1 925 AC2 534 AC3 786 AC4 662 DC3 719 DC4 880 DC5 825 DC7 434 EE1 554 EE2 744 EE3 638 EE4 593 EE5 880 EE6 775 EE7 745 EE8 999 DJ1 575 DJ2 683 DJ3 818 PJ1 610 PJ2 645 PJ3 771 PJ4 897 PJ5 899 PJ6 886 PJ7 797 PJ8 782 OT1 OT2 OT3 JS2 JS3 JS4 Extraction Method: Principal Axis Factoring a Rotation Method: Promax with Kaiser Normalization a Rotation converged in iterations Factor Correlation Matrix Factor 5 1.000 -.443 237 -.374 013 417 415 -.443 1.000 202 577 407 -.365 -.376 237 202 1.000 146 451 021 403 -.374 577 146 1.000 194 -.315 -.261 Extraction Method: Principal Axis Factoring Rotation Method: Promax with Kaiser Normalization .013 407 451 194 1.000 104 077 825 833 771 -.415 417 -.365 021 -.315 104 1.000 110 415 -.376 403 -.261 077 110 1.000 APPRENDIX - RESULTS OF MULTIPLE LINEAR REGRESSION Model R a Model Summary Adjusted R Std Error of R Square Square the Estimate 474 462 6714 688 a Predictors: (Constant), DC_PJ, AC, DJ, AC_DJ, DC, PJ, DC_DJ, AC_PJ a ANOVA Sum of Mean Squares Square Model df Regression Residual Total 146.004 162.269 308.273 360 368 18.251 451 F 40.489 Sig b 000 a Dependent Variable: EE b Predictors: (Constant), DC_PJ, AC, DJ, AC_DJ, DC, PJ, DC_DJ, AC_PJ Coefficients Model Unstandardized Coefficients Std B Error (Constan 3.258 t) 183 AC 330 038 DC 094 039 DJ -.151 046 PJ -.376 050 AC_DJ -.037 055 AC_PJ -.025 063 DC_DJ 242 056 DC_PJ -.122 046 a Dependent Variable: EE a Standardi zed Coefficie nts Beta Collinearity Statistics t Sig 17.815 000 372 8.779 110 2.431 -.159 -3.263 -.374 -7.562 -.043 -.671 -.026 -.397 241 4.314 -.150 -2.663 000 016 001 000 502 691 000 008 Tolerance 813 713 617 598 351 346 469 458 VIF 1.229 1.403 1.621 1.673 2.846 2.891 2.132 2.182 a Collinearity Diagnostics Variance Proportions (Con stant Mod Dimen el Eigenva sion lueConditio 4.770 n Index) 00 1 2.307 1.000 AC 00 786 1.438 00 00 707 2.464 00 00 167 2.597 00 00 138 5.347 00 00 064 5.884 03 02 034 8.664 02 04 028 11.785 57 94 13.095 09 29 DC 00 00 00 00 12 14 52 16 06 DJ 00 00 00 00 07 07 00 52 34 a Dependent Variable: EE Model R a Model Summary Adjusted R Std Error of R Square Square the Estimate 324 322 71675 569 a Predictors: (Constant), EE ANOVA a PJ 00 00 00 00 03 01 09 86 00 AC_ DJAC_ PJDC_ DJDC_ PJ 00 00 00 00 04 04 05 04 15 01 04 31 03 18 33 03 32 20 32 20 44 51 23 39 01 02 01 00 01 03 03 02 01 00 00 01 Model Regression Residual Total Sum of Squares 90.349 188.540 278.889 a Dependent Variable: JS b Predictors: (Constant), EE Mean Square F 90.349 175.868 514 df 367 368 Coefficients a Sig b 000 5.4 Unstandardized Coefficients Model (Constant) AveEE B 4.403 -.541 Std Error 129 041 Standardized Coefficients Beta -.569 t 34.053 -13.262 Sig .000 000 a Dependent Variable: JS Model R a Model Summary Adjusted R Std Error of R Square Square the Estimate 328 325 9229 573 a Predictors: (Constant), JS, EE ANOVA a Model Regression Residual Total Sum of Squares 152.463 311.733 464.195 df 366 368 a Dependent Variable: OT b Predictors: (Constant), JS, EE Coefficientsa Mean Square 76.231 852 F 89.502 Sig b 000 Unstandardized Coefficients B 2.403 531 -.262 JS a Dependent Variable: OT Model (Constant) EE Std Error 340 064 067 Standardized Coefficients Beta 433 -.203 t 7.075 8.307 -3.896 Sig .000 000 000 ... Unreasonablydemanding customers have a negative effect on emotional exhaustion levels of customer service officers H3 – Emotional exhaustion has a negative effect on employee turnover intentions. .. 13 2.1.1 Problematic customers 13 2.1.2 Problematic customers and Emotional exhaustion 14 2.1.3 Emotional exhaustion and Turnover intentions for customer-related... regressions of all independent variables and Emotional exhaustion 40 Table The result of simple linear regressions of Emotional exhaustion and Job satisfaction 42 Table The result of