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) 10 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 77 Scale: OCCUPATIONAL TURNOVER INTENTION Reliability Statistics Cronbach's Alpha N of Items 906 OT1 OT2 OT3 OT1 OT2 OT3 Item Statistics Std Mean Deviation 3.2358 1.24071 3.4228 1.19105 3.2114 1.23964 Scale Mean if Item Deleted 6.6341 6.4472 6.6585 N 369 369 369 Item-Total Statistics Scale Corrected Cronbach's Variance if Item-Total Alpha if Item Item Deleted Correlation Deleted 5.075 848 835 5.655 755 912 5.117 838 844 Scale Statistics Std Mean Variance Deviation 9.8699 11.353 3.36936 N of Items 78 Scale: JOB SATISFACTION Reliability Statistics Cronbach's Alpha N of Items 847 Item Statistics Std Mean Deviation JS1 JS2 JS3 JS4 JS1 JS2 JS3 JS4 2.8238 2.7669 2.8509 2.6043 Scale Mean if Item Deleted 8.2222 8.2791 8.1951 8.4417 1.05752 1.00265 1.06934 1.07622 N 369 369 369 369 Item-Total Statistics Scale Corrected Cronbach's Variance if Item-Total Alpha if Item Item Deleted Correlation Deleted 7.869 529 870 6.751 839 740 6.647 786 759 7.410 607 839 Scale Statistics Std Mean Variance Deviation 11.0461 12.126 3.48218 N of Items 79 APPRENDIX – FACTOR ANALYSIS Scale: ABUSIVE CUSTOMER KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Approx Chi-Square Sphericity df Sig .769 902.346 10 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings % of Cumulative % of Cumulative Factor Total Variance % Total Variance % 3.203 64.060 64.060 2.797 55.933 55.933 719 14.380 78.440 544 10.880 89.320 328 6.556 95.876 206 4.124 100.000 Extraction Method: Principal Axis Factoring Factor Matrixa Factor AC1 562 AC2 827 AC3 841 AC4 799 AC5 672 Extraction Method: Principal Axis Factoring a factors extracted iterations required 80 Scale: UNREASONABLE DEMANDING CUSTOMER KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Approx Chi-Square Sphericity df Sig .795 1123.214 15 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings % of Cumulative Factor Total Variance % 3.614 60.240 60.240 889 14.811 75.051 602 10.036 85.087 396 6.608 91.695 293 4.877 96.573 206 3.427 100.000 Extraction Method: Principal Axis Factoring Factor Matrixa Factor DC1 785 DC2 630 DC3 782 DC4 788 DC5 666 DC7 681 Extraction Method: Principal Axis Factoring a factors extracted iterations required Total 3.154 % of Cumulative Variance % 52.563 52.563 81 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 .899 1918.494 28 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings % of Cumulative % of Cumulative Factor Total Variance % Total Variance % 5.045 63.060 63.060 4.653 58.165 58.165 749 9.360 72.421 580 7.250 79.671 548 6.849 86.520 388 4.850 91.369 296 3.698 95.068 234 2.926 97.993 161 2.007 100.000 Extraction Method: Principal Axis Factoring Factor Matrixa 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 82 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 .703 387.634 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings % of Cumulative % of Cumulative Factor 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 Factor Matrixa Factor DJ1 697 DJ2 857 DJ3 764 Extraction Method: Principal Axis Factoring a factors extracted 12 iterations required 83 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 Factor Matrixa Factor PJ1 718 PJ2 828 PJ3 771 PJ4 866 PJ5 892 PJ6 791 PJ7 899 PJ8 850 Extraction Method: Principal Axis Factoring a factors extracted iterations required Total 5.498 % of Variance 68.723 Cumulative % 68.723 84 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 % of Variance Cumulative % 2.526 84.195 84.195 313 10.435 94.630 161 5.370 100.000 Extraction Method: Principal Axis Factoring Factor Matrixa Factor OT1 923 OT2 791 OT3 908 Extraction Method: Principal Axis Factoring a factors extracted iterations required Total 2.302 % of Variance 76.740 Cumulative % 76.740 85 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 .737 795.319 000 Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings % of Cumulative % of Cumulative Factor Total Variance % Total Variance % 2.777 69.420 69.420 2.460 61.498 61.498 712 17.794 87.213 344 8.609 95.823 167 4.177 100.000 Extraction Method: Principal Axis Factoring Factor Matrixa Factor 579 948 884 667 JS1 JS2 JS3 JS4 Extraction Method: Principal Axis Factoring a factors extracted 10 iterations required 86 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 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 Initial Eigenvalues % of Cumulative Variance % 33.668 33.668 17.869 51.538 7.386 58.924 6.256 65.180 4.991 70.171 3.676 73.847 3.162 77.009 2.699 79.708 2.297 82.005 2.038 84.043 1.831 85.875 1.612 87.487 1.434 88.920 1.284 90.204 1.123 91.327 1.028 92.356 899 93.255 881 94.136 788 94.924 674 95.597 628 96.226 619 96.845 554 97.399 517 97.916 Extraction Sums of Squared Loadings % of Cumulative Total Variance % 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 Loadingsa Total 8.344 8.785 4.432 6.410 4.100 4.282 4.435 87 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 Pattern Matrixa 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 88 PJ8 782 OT1 825 OT2 833 OT3 771 JS2 -.415 JS3 JS4 Extraction Method: Principal Axis Factoring Rotation Method: Promax with Kaiser Normalization.a a Rotation converged in iterations Factor Correlation Matrix Factor 1.000 -.443 237 -.374 013 -.443 1.000 202 577 407 237 202 1.000 146 451 -.374 577 146 1.000 194 013 407 451 194 1.000 417 -.365 021 -.315 104 415 -.376 403 -.261 077 Extraction Method: Principal Axis Factoring Rotation Method: Promax with Kaiser Normalization .571 535 909 417 -.365 021 -.315 104 1.000 110 415 -.376 403 -.261 077 110 1.000 89 APPRENDIX - RESULTS OF MULTIPLE LINEAR REGRESSION Model Summary Adjusted R Std Error of Model R R Square Square the Estimate a 688 474 462 6714 a Predictors: (Constant), DC_PJ, AC, DJ, AC_DJ, DC, PJ, DC_DJ, AC_PJ ANOVAa Sum of Mean Model Squares df Square F Sig Regression 146.004 18.251 40.489 000b Residual 162.269 360 451 Total 308.273 368 a Dependent Variable: EE b Predictors: (Constant), DC_PJ, AC, DJ, AC_DJ, DC, PJ, DC_DJ, AC_PJ Coefficientsa Standardi zed Unstandardized Coefficie Coefficients nts Std B Error Beta t Sig .183 17.815 000 038 039 046 050 372 8.779 110 2.431 -.159 -3.263 -.374 -7.562 000 016 001 000 813 713 617 598 1.229 1.403 1.621 1.673 -.043 -.671 -.026 -.397 241 4.314 -.150 -2.663 502 691 000 008 351 346 469 458 2.846 2.891 2.132 2.182 Model (Constan 3.258 t) AC 330 DC 094 DJ -.151 PJ -.376 AC_DJ -.037 055 AC_PJ -.025 063 DC_DJ 242 056 DC_PJ -.122 046 a Dependent Variable: EE Collinearity Statistics Tolerance VIF 90 Mod Dimen Eigenva el sion lue 1 4.770 2.307 786 707 Collinearity Diagnosticsa Variance Proportions (Con Conditio stant AC_ AC_ DC_ DC_ n Index ) AC DC DJ PJ DJ PJ DJ PJ 1.000 00 00 00 00 00 00 00 00 00 1.438 00 00 00 00 00 04 04 05 04 2.464 00 00 00 00 00 15 01 04 31 2.597 00 00 00 00 00 03 18 33 03 167 138 064 034 028 a Dependent Variable: EE Model R 5.347 5.884 8.664 11.785 13.095 00 00 02 04 94 03 02 57 09 29 Model Summary Adjusted R R Square Square 569a 324 a Predictors: (Constant), EE 12 14 52 16 06 07 07 00 52 34 03 01 09 86 00 32 44 01 01 01 20 51 02 03 00 Std Error of the Estimate 322 71675 ANOVAa Sum of Mean Model Squares df Square F Regression 90.349 90.349 175.868 Residual 188.540 367 514 Total 278.889 368 a Dependent Variable: JS b Predictors: (Constant), EE Coefficientsa 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 .000b Sig .000 000 32 23 01 03 00 20 39 00 02 01 91 a Dependent Variable: JS Model Summary Adjusted R Std Error of Model R R Square Square the Estimate a 573 328 325 9229 a Predictors: (Constant), JS, EE ANOVAa Sum of Mean Model Squares df Square Regression 152.463 76.231 Residual 311.733 366 852 Total 464.195 368 a Dependent Variable: OT b Predictors: (Constant), JS, EE Coefficientsa Unstandardized Standardized Coefficients Coefficients Model B Std Error Beta (Constant) 2.403 340 EE 531 JS -.262 a Dependent Variable: OT 064 067 433 -.203 F 89.502 Sig .000b t 7.075 Sig .000 8.307 -3.896 000 000 ... problematic customers causing influence on emotional exhaustion of employees, and how perceived organizational justice can moderate this relationship Abusive customers H1 Emotional exhaustion Unreasonably... 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