Findings from the Service Failure and Recovery Study Essay

Exclusively available on Available only on IvyPanda® Written by Human No AI

Introduction

A customer satisfaction survey investigated the degree of satisfaction with service experience, observations about the quality of service, organizational response, and how the shopper subsequently behaved. The study yielded 104 responses. The present section focuses on testing the following alternative and null hypotheses:

Concerning word-of-mouth:

  • H01: The overall satisfaction with the company will not influence the likelihood of recommendation or positive word-of-mouth.
  • HA1: The overall satisfaction with the company will influence the likelihood of recommendation or positive word-of-mouth.

Concerning effect or emotional response:

  • H02: The positive emotions of the customer following a service recovery will have no effect or decrease the likelihood of repurchase intentions
  • HA2: The positive emotions of the customer following a service recovery will increase the likelihood of repurchase intentions

Results

Satisfaction with Service Experience

On the whole, the quality of customer experience with the service business leaves much to be desired. The dichotomous response of “satisfied” or not (see Table 1 in the Appendices) reveals that dissatisfied customers outnumber the pleased patrons about 3 to 2. In the absolute, this is disastrous given that business enterprises declare it their mission to maximize customer satisfaction. Secondly, the results suggest better than even odds that any customer in the future will come away dissatisfied. Yet a third source of concern is the multiplier effect of a frustrated customer communicating a disappointing experience to others (see following section B).

Analyzing the above outcome by the available socio-demographic information, one finds first of all that women are more likely to come away dissatisfied (Tables 2, 3, and Fig. 1 in the appendices). However, the chi-square test – applicable in this case because the classifying independent variable is binomial – is borderline and does not affirm that the difference vis-à-vis men could not have occurred by chance at the commonly-accepted 0.95 confidence level threshold. Since the nonparametric test is unusually sensitive to low degrees of freedom (that is, the size of the subsample), such below-threshold significance can perhaps be retested with a larger sampling of incidents in the future.

Inspected by customer ages, the raw tabulation (Table 4) is highly fragmented for spanning no less than 33 different ages. Not surprisingly, the chi-square test (Table 5) reveals a significant statistic of 0.82 at 32 df (33 ages less 1), which suggests the unsatisfactory finding that the overall distribution of differences in dissatisfaction incidence by single age may well have occurred by chance in eight of ten survey re-tries. In short, the differences by age are largely random. Nonetheless, visual inspection of Fig. 2 suggests that the incidence of dissatisfaction was greatest among 29 year-olds.

Effect on Word-of-Mouth

On a seven-point scale ranging from 1 “very dissatisfied” to 7 “very satisfied”, overall satisfaction with recent service experiences tended to be low at an average of 3.3 (SD = 2.4, see table 8 in the Appendices). Whatever the mix of service businesses that study participants had in mind and evaluated, it is clear that there exists tremendous opportunity based on being able to deliver delightful customer experiences more consistently.

There is also an opportunity in the finding that those who decided to relate their experiences to others, by whatever channel of communication, tended to be more dissatisfied (mean overall satisfaction = 3.2, S. D. = 2.42) than the tiny minority who said nothing at all to anyone (mean = 5.4, S. D. = 1.8) (Table 10). These findings stand to reason since Swanson and Hsu (2009) asserted that the consequences of service failures can include customer dissatisfaction and negative word-of-mouth, among others.

Whether these average satisfaction values differ meaningfully is another matter, however. On the face of it, the t-test result for two independent samples (across WOM/Not-WOM) yields a significant statistic of 0.02, rather handily meeting the 0.05 decision rule (Table 11). The standard interpretation for such an outcome is that the difference between the mean overall satisfaction ratings of 3.2 and 5.4 could have occurred by chance perhaps twice in a hundred re-surveys. Since it is lower than the required α = 0.05, one must reject the null hypothesis and accept the alternative stated on page 1: The overall satisfaction with the company will influence the likelihood of recommendation or positive word-of-mouth.

On the other hand, Fig. 4 does show that the distribution of overall satisfaction ratings is both bipolar and therefore bimodal, with a serious skew towards the “very dissatisfied” end of the scale. The assumption of a normal distribution cannot be met. The fallback is the cross-break shown in Table 12 and reverting to the nonparametric chi-square test (Table 13). The latter yields the borderline value p = 0.06, enabling one to reject the null hypothesis once again provided the confidence level is loosened to 0.90.

Effect on Repurchase Intention

To test the second set of hypotheses, we can, for simplicity’s sake, employ:

  • Overall satisfaction (“satis”) as the independent variable (IV) since the database does not include the supplemental questions about the level of emotion (question 24) asked if no service recovery occurred;
  • For the first dependent variable (DV), taking one’s custom away (“recovery 10” or went elsewhere) despite any attempt by the concerned business to mitigate the service failure; and,
  • For a second DV, whether the shopper purchased again from the company (“rebuy”).

Procedurally, one sets up the analyses with a cross-break of each DV in turn as the column headers and the results of the overall scale of satisfaction comprising the rows of the table, as in Tables 14 and 15. Hypothesis evaluation should be possible with the t-test of two independent samples since the IV is scalar and can yield means. However, recall from section B above that the data does not follow a normal distribution but is seriously skewed toward the negative extreme of the scale. Hence, one can fall back on non-parametric measures like the Χ (chi-square) test.

The variable “went elsewhere” may be subject to emotional bias since it is so lopsided in favor of claiming not to have terminated the relationship altogether (Table 16). As it is, the 93% of survey participants who reported the service failure was not serious enough to cause them to terminate the relationship had a mean rating of 3.4 (SD = 2.4), somewhat better than the 1.6 mean (SD = 1.5) found for those who did claim to terminate the relationship. Nonetheless, it is noteworthy that even the 3.4 mean rating of those not terminating the relationship is right in the middle of the seven-point scale, suggesting a reserved kind of dissatisfaction but unhappiness nonetheless.

The second DV may present a more realistic picture. Table 17 shows that the sample was almost evenly divided among those who remained patrons (the service problem was not critical or there may have been no alternative) and those who became lapsed customers. The gap in mean satisfaction rating was also wider as those who made a subsequent purchase from the offending vendor averaged 4.61 on the seven-point scale (SD = 2.31), near the positive end of the scale and 2.3 scale points higher than the mean of 2.29 (SD = 2.0) grudgingly given by the lapsed patrons.

When Student’s t is used to evaluate the hypotheses, one finds a borderline case for the DV “went elsewhere”: p = 0.05, suggesting that the gap in mean satisfaction ratings of 1.9 scale points may well occur by chance about once in twenty sampling attempts from the relevant universe of service customers (Table 18). There is not enough evidence to reject the null hypothesis, particularly since no less than 93% of survey participants claimed to have maintained their patronage even after a disappointing service experience.

Turning to the DV as “patronized the store again or not”, one finds this time that the 2.31 difference in mean satisfaction ratings is associated with a t value of 5.424 that, at 102 df, bears the significance statistic p < 0.00001 (Table 19). Since this means that a gap of that magnitude in average satisfaction ratings could have occurred by chance less than once in 100,000 survey re-samplings, one rejects the null hypothesis and accepts the alternative: “The positive emotions of the customer following a service recovery increases the likelihood of repurchase intentions.”

Falling back on nonparametric assumptions and going by the chi-square test, the result is the same (Tables 20-21). The claim of having maintained patronage versus going elsewhere is associated with p > 0.05 and it is therefore not possible to reject the null hypothesis. On the other hand, average satisfaction ratings do differ materially (p < 0.001), enabling one to once more reject the null hypothesis and accept the alternative that overall satisfaction with complaint handling helps maintain repeat patronage.

Limitations

In theory, the findings of this survey are reliable and representative solely of accessible college-age youth and older adults, with a bias for the former, that comprised the convenience sample in Whitewater (or wherever the survey was run, PLEASE REPLACE). Since survey subjects were left free to refer to any memorable service transaction, findings are also valid for the general category of person-to-person transactions. A purchase at a consumer electronics retailer likely carries as much weight as an online pre-order transaction for the Apple iPad or a visit to a day spa. And yet, business research and policy for products, online marketing, and personal services presumably relies on a differing hierarchy of priorities.

Implications for Future Studies

Springing directly from the limitations of the present data set, the need for dynamic analysis of customer segments, and the need for action-oriented recommendations, it is vital to consider:

  • A considerably larger base of survey subjects to enable rigorous comparisons by gender, income class, age, occupation, and face-to-face or online transactions.
  • Refine coverage to specific service businesses to minimize the confusion with the service aspects of product marketing and retailing.
  • Improve code categories so that they are more meaningful on their own, obviating the need for a decision-maker to look up the coding manual.

That women are liable to come away from a service transaction less satisfied bears investigating. This may be related to the nature of the service purchased or to gender-based undercurrents of customer-service personnel interactions. Greater dissatisfaction among shoppers in their twenties generally and those 29 years of age, in particular, maybe a statistical fluke or it may reflect the lower disposable income (and therefore insecurities) of students and workers still in the bottom rungs of their career ladders. Recommendations concerning a larger base enabling more thorough analysis by gender and age group should also consider other attributes.

Analyzing service faults by product/service type or transaction channel also bears implementation in future studies. A high-involvement product category is likely to generate higher service expectations as do faceless sales channels. For example, a facial cream promising better “anti-wrinkle” action might require on-the-spot demonstration on proper application or reassurances about ingredient safety as part of the service. In the case of auto or health insurance, the proof of the service pudding is tested at need, when the buyer seeks immediate and full satisfaction in return for past investments in premiums.

Appendices

Table 1: Adjudged Outcome of Customer Experience

type of incident
FrequencyPercentValid PercentCumulative Percent
ValidDissatisfied6158.6558.6558.65
Satisfied4341.3541.35100.00
Total104100.00100.00

Table 2: Satisfying/Dissatisfying Critical Incident by Customer Gender

Crosstab
type of incident
DissatisfiedSatisfiedTotal
respondent’s genderMaleCount242347
Expected Count27.619.447.0
% within the type of incident39.3%53.5%45.2%
FemaleCount372057
Expected Count33.423.657.0
% within the type of incident60.7%46.5%54.8%
TotalCount6143104
Expected Count61.043.0104.0
% within the type of incident100.0%100.0%100.0%

Table 3: Chi-Square Test Result for Satisfaction Incidence by Gender

Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)Exact Sig. (2-sided)Exact Sig. (1-sided)
Pearson Chi-Square2.037a1.154
Continuity Corrections1.5061.220
Likelihood Ratio2.0381.153
Fisher’s Exact Test.167.110
Linear-by-Linear Association2.0181.155
N of Valid Cases104
a. 0 cells (.0%) have an expected count less than 5. The minimum expected count is 19.43.
b. Computed only for a 2×2 table
Incidence of Dissatisfaction by Gender
Figure 1: Incidence of Dissatisfaction by Gender

Table 4: Crosstabulation of Dissatisfaction Incidence by Age of Customer

Crosstab
type of incident
DissatisfiedSatisfiedTotal
respondent’s age18Count202
Expected Count1.2.82.0
% within the type of incident3.3%.0%1.9%
21Count112
Expected Count1.2.82.0
% within type of incident1.6%2.3%1.9%
22Count011
Expected Count.6.41.0
% within type of incident.0%2.3%1.0%
23Count112
Expected Count1.2.82.0
% within type of incident1.6%2.3%1.9%
24Count213
Expected Count1.81.23.0
% within type of incident3.3%2.3%2.9%
25Count314
Expected Count2.31.74.0
% within type of incident4.9%2.3%3.8%
26Count303
Expected Count1.81.23.0
% within type of incident4.9%.0%2.9%
27Count314
Expected Count2.31.74.0
% within type of incident4.9%2.3%3.8%
28Count235
Expected Count2.92.15.0
% within type of incident3.3%7.0%4.8%
29Count9413
Expected Count7.65.413.0
% within type of incident14.8%9.3%12.5%
30Count235
Expected Count2.92.15.0
% within type of incident3.3%7.0%4.8%
31Count538
Expected Count4.73.38.0
% within type of incident8.2%7.0%7.7%
32Count235
Expected Count2.92.15.0
% within type of incident3.3%7.0%4.8%
33Count213
Expected Count1.81.23.0
% within type of incident3.3%2.3%2.9%
36Count415
Expected Count2.92.15.0
% within type of incident6.6%2.3%4.8%
37Count145
Expected Count2.92.15.0
% within type of incident1.6%9.3%4.8%
38Count235
Expected Count2.92.15.0
% within type of incident3.3%7.0%4.8%
39Count101
Expected Count.6.41.0
% within type of incident1.6%.0%1.0%
40Count123
Expected Count1.81.23.0
% within type of incident1.6%4.7%2.9%
41Count101
Expected Count.6.41.0
% within type of incident1.6%.0%1.0%
43Count011
Expected Count.6.41.0
% within type of incident.0%2.3%1.0%
44Count101
Expected Count.6.41.0
% within type of incident1.6%.0%1.0%
45Count213
Expected Count1.81.23.0
% within type of incident3.3%2.3%2.9%
48Count112
Expected Count1.2.82.0
% within type of incident1.6%2.3%1.9%
49Count112
Expected Count1.2.82.0
% within type of incident1.6%2.3%1.9%
50Count101
Expected Count.6.41.0
% within type of incident1.6%.0%1.0%
52Count123
Expected Count1.81.23.0
% within type of incident1.6%4.7%2.9%
55Count101
Expected Count.6.41.0
% within type of incident1.6%.0%1.0%
56Count123
Expected Count1.81.23.0
% within type of incident1.6%4.7%2.9%
57Count101
Expected Count.6.41.0
% within type of incident1.6%.0%1.0%
59Count123
Expected Count1.81.23.0
% within type of incident1.6%4.7%2.9%
63Count202
Expected Count1.2.82.0
% within type of incident3.3%.0%1.9%
69Count101
Expected Count.6.41.0
% within type of incident1.6%.0%1.0%
TotalCount6143104
Expected Count61.043.0104.0
% within type of incident100.0%100.0%100.0%

Table 5: Test of Significance for Dissatisfaction by Age

Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square24.783a32.815
Likelihood Ratio30.66032.534
Linear-by-Linear Association.1071.744
N of Valid Cases104
a. 64 cells (97.0%) have expected count less than 5. The minimum expected count is.41.
Dissatisfaction by Single Age
Figure 2: Dissatisfaction by Single Age

Table 6: Dissatisfaction Incidence by AGE CLASS of Respondent

Age classes * type of incident Crosstabulation
type of incident
DissatisfiedSatisfiedTotal
Age classes18 to 29Count261339
Expected Count22.916.139.0
% within Age classes66.7%33.3%100.0%
% within type of incident42.6%30.2%37.5%
30 to 39Count191837
Expected Count21.715.337.0
% within Age classes51.4%48.6%100.0%
% within type of incident31.1%41.9%35.6%
40+ yearCount161228
Expected Count16.411.628.0
% within Age classes57.1%42.9%100.0%
% within type of incident26.2%27.9%26.9%
TotalCount6143104
Expected Count61.043.0104.0
% within Age classes58.7%41.3%100.0%
% within type of incident100.0%100.0%100.0%

Table 7: Test of Significance for Dissatisfaction by AGE CLASS

Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square1.872520.3921
Likelihood Ratio1.886720.3893
N of Valid Cases104
a. 0 cells (.0%) have an expected count less than 5. The minimum expected count is 11.58.
Dissatisfaction Incidence by AGE CLASS
Figure 3: Dissatisfaction Incidence by AGE CLASS

Table 8: Descriptive Statistics for “Overall Satisfaction” Rating

Descriptive Statistics
NMinimumMaximumSumMeanStd. Deviation
overall satisfaction104173453.322.443
Valid N (listwise)104

Table 9: Mean “Overall Satisfaction” Rating by Whether Shoppers Engaged in Word of Mouth Subsequently

Group Statistics
discussed with anyoneNMeanStd. DeviationStd. Error Mean
overall satisfactionYes973.162.418.246
No75.431.813.685
Distribution of Overall Satisfaction Rating by Whether Shopper Engaged in Word of Mouth
Figure 4: Distribution of Overall Satisfaction Rating by Whether Shopper Engaged in Word of Mouth

Table 10: Mean Satisfaction Ratings by Whether Shopper Engaged in Word-of-Mouth

Group Statistics
discussed with anyoneNMeanStd. DeviationStd. Error Mean
overall satisfactionYes973.1652.4180.246
No75.4291.8130.685

Table 11: T-test for Overall Satisfaction Rating by Whether Shopper Engaged in Word-of-Mouth

Independent Samples Test
Levene’s Test for Equality of Variancest-test for Equality of Means
Equal VariancesFSig.tdfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the Difference
LowerUpper
overall satisfactionAssumed3.670.06-2.42102.000.02-2.260.93-4.12-0.41
Not assumed-3.117.630.02-2.260.73-3.96-0.57

Table 12: Cross Tabulation Between Overall Satisfaction Rating and Propensity for Word-of-Mouth

overall satisfaction * discussed with friends Crosstabulation
discussed with friends
YesNoTotal
overall satisfactionVery DissatisfiedCount39241
Expected Count36.05.041.0
% within overall satisfaction95.1%4.9%100.0%
% within discussed with friends44.8%16.7%41.4%
2Count13013
Expected Count11.41.613.0
% within overall satisfaction100.0%.0%100.0%
% within discussed with friends14.9%.0%13.1%
3Count628
Expected Count7.01.08.0
% within overall satisfaction75.0%25.0%100.0%
% within discussed with friends6.9%16.7%8.1%
4Count404
Expected Count3.5.54.0
% within overall satisfaction100.0%.0%100.0%
% within discussed with friends4.6%.0%4.0%
5Count213
Expected Count2.6.43.0
% within overall satisfaction66.7%33.3%100.0%
% within discussed with friends2.3%8.3%3.0%
6Count8412
Expected Count10.51.512.0
% within overall satisfaction66.7%33.3%100.0%
% within discussed with friends9.2%33.3%12.1%
Very satisfiedCount15318
Expected Count15.82.218.0
% within overall satisfaction83.3%16.7%100.0%
% within discussed with friends17.2%25.0%18.2%
TotalCount871299
Expected Count87.012.099.0
% within overall satisfaction87.9%12.1%100.0%
% within discussed with friends100.0%100.0%100.0%

Table 13: Nonparametric Test of Statistical Significance for Mean Overall Satisfaction Rating by Propensity for Word-of-Mouth

Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square12.295a6.056
Likelihood Ratio12.8326.046
Linear-by-Linear Association5.8771.015
N of Valid Cases99
a. 9 cells (64.3%) have expected count less than 5. The minimum expected count is.36.

Table 14: Crosstabulation of Overall Satisfaction Rating by Whether the Shopper Went Elsewhere and Terminated the Relationship

Crosstab
went elsewhere (terminating relationship)
YesNoTotal
overall satisfactionVery DissatisfiedCount63541
Expected Count2.838.241.0
% within went elsewhere (terminating relationship)85.7%36.1%39.4%
2Count01414
Expected Count.913.114.0
% within went elsewhere (terminating relationship).0%14.4%13.5%
3Count088
Expected Count.57.58.0
% within went elsewhere (terminating relationship).0%8.2%7.7%
4Count055
Expected Count.34.75.0
% within went elsewhere (terminating relationship).0%5.2%4.8%
5Count123
Expected Count.22.83.0
% within went elsewhere (terminating relationship)14.3%2.1%2.9%
6Count01414
Expected Count.913.114.0
% within went elsewhere (terminating relationship).0%14.4%13.5%
Very satisfiedCount01919
Expected Count1.317.719.0
% within went elsewhere (terminating relationship).0%19.6%18.3%
TotalCount797104
Expected Count7.097.0104.0
% within went elsewhere (terminating relationship)100.0%100.0%100.0%

Table 15: Crosstabulation Between Overall Satisfaction and Whether the Shopper Ever Patronized the Company Again

Crosstab
purchased again from the company
YesNoTotal
overall satisfactionVery DissatisfiedCount63541
Expected Count18.122.941.0
% within purchased again from the company13.0%60.3%39.4%
2Count7714
Expected Count6.27.814.0
% within purchased again from the company15.2%12.1%13.5%
3Count448
Expected Count3.54.58.0
% within purchased again from the company8.7%6.9%7.7%
4Count415
Expected Count2.22.85.0
% within purchased again from the company8.7%1.7%4.8%
5Count123
Expected Count1.31.73.0
% within purchased again from the company2.2%3.4%2.9%
6Count9514
Expected Count6.27.814.0
% within purchased again from the company19.6%8.6%13.5%
Very satisfiedCount15419
Expected Count8.410.619.0
% within purchased again from the company32.6%6.9%18.3%
TotalCount4658104
Expected Count46.058.0104.0
% within purchased again from the company100.0%100.0%100.0%

Table 16: Mean Satisfaction Ratings by Whether Shopper Claimed to Have Terminated the Relationship

Group Statistics
went elsewhere (terminating relationship)NMeanStd. DeviationStd. Error Mean
overall satisfactionYes71.571.512.571
No973.442.454.249

Table 17: Mean Satisfaction Ratings by Whether Shopper Patronized the Business Again

Group Statistics
purchased again from the companyNMeanStd. DeviationStd. Error Mean
overall satisfactionYes464.612.314.341
No582.292.035.267

Table 18: T-Test Result for Overall Satisfaction by Those Reporting to Have Terminated the Relationship or Not

Independent Samples Test
Levene’s Test for Equality of Variancest-test for Equality of Means
FSig.tdfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the Difference
LowerUpper
Overall satisfactionEqual variances assumed11.663.001-1.986102.050-1.872.943-3.741-.002
Equal variances not assumed-3.0038.478.016-1.872.623-3.295-.448

Table 19: T-Test Result for Mean Satisfaction Rating Versus Ever Having Patronized the Store Again

Independent Samples Test
Levene’s Test for Equality of Variancest-test for Equality of Means
FSig.tdfSig. (2-tailed)Mean DifferenceStd. Error Difference95% Confidence Interval of the Difference
LowerUpper
Overall satisfactionEqual variances assumed5.4220.0225.4241020.000002.3160.4271.4693.162
Equal variances not assumed5.34390.3070.000002.3160.4331.4553.176

Table 20: Chi-Square Result for Satisfaction Ratings Versus Claiming to Have Maintained the Relationship or Not

Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square11.791a6.067
Likelihood Ratio13.3406.038
Linear-by-Linear Association3.8341.050
N of Valid Cases104
a. 9 cells (64.3%) have expected count less than 5. The minimum expected count is.20.

Table 21: Chi-Square Result for Satisfaction Rating Distribution versus Having Patronized the Establishment Again

Chi-Square Tests
ValuedfAsymp. Sig. (2-sided)
Pearson Chi-Square29.160a6.000
Likelihood Ratio31.5226.000
Linear-by-Linear Association23.0551.000
N of Valid Cases104
a. 6 cells (42.9%) have an expected count less than 5. The minimum expected count is 1.33.
Cite This paper
You're welcome to use this sample in your assignment. Be sure to cite it correctly

Reference

IvyPanda. (2022, March 14). Findings from the Service Failure and Recovery Study. https://ivypanda.com/essays/findings-from-the-service-failure-and-recovery-study/

Work Cited

"Findings from the Service Failure and Recovery Study." IvyPanda, 14 Mar. 2022, ivypanda.com/essays/findings-from-the-service-failure-and-recovery-study/.

References

IvyPanda. (2022) 'Findings from the Service Failure and Recovery Study'. 14 March.

References

IvyPanda. 2022. "Findings from the Service Failure and Recovery Study." March 14, 2022. https://ivypanda.com/essays/findings-from-the-service-failure-and-recovery-study/.

1. IvyPanda. "Findings from the Service Failure and Recovery Study." March 14, 2022. https://ivypanda.com/essays/findings-from-the-service-failure-and-recovery-study/.


Bibliography


IvyPanda. "Findings from the Service Failure and Recovery Study." March 14, 2022. https://ivypanda.com/essays/findings-from-the-service-failure-and-recovery-study/.

More Essays on Consumer Science
If, for any reason, you believe that this content should not be published on our website, you can request its removal.
Updated:
This academic paper example has been carefully picked, checked and refined by our editorial team.
No AI was involved: only quilified experts contributed.
You are free to use it for the following purposes:
  • To find inspiration for your paper and overcome writer’s block
  • As a source of information (ensure proper referencing)
  • As a template for you assignment
1 / 1