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Table 4 Factors affecting latent profile types

From: Analysis of latent profiles and affected factors according to the implementation of a protection system against customer bullying in Korea

Characteristics

Categories

Comparison group (Ref= Lagging type (Type 1))

Medium type (Type 2)

Relative preventive type (Type 3)

Excellent type (Type 4)

OR

p

95% CI

OR

p

95% CI

OR

p

95% CI

Age

0.972

0.022

0.948-0.996

0.998

0.823

0.976-1.019

0.972

0.150

0.936-1.010

Gender (ref= male)

6.507

< 0.001

4.069-10.405

2.757

< 0.001

1.923-3.953

3.207

< 0.001

1.723-5.966

Service period

1.005

0.001

1.002-1.007

1.001

0.541

0.998-1.003

1.002

0.258

0.998-1.006

Position (ref= Staff)

2.677

< 0.001

1.592-4.501

2.174

0.003

1.314-3.596

4.680

< 0.001

2.402-9.118

Occupational category

(ref=other)

Sales

2.038

0.102

0.868-4.783

2.219

0.034

1.060-4.645

1.361

0.604

0.425-4.363

Health and social welfare

1.966

0.199

0.701-5.518

1.138

0.798

0.422-3.071

2.019

0.326

0.497-8.208

Call center

4.289

0.008

1.466-12.542

2.449

0.079

0.902-6.650

1.398

0.728

0.212-9.232

Visiting service

0.403

0.108

0.134-1.219

0.580

0.230

0.238-1.413

0.201

0.090

0.031-1.285

Worker monitoring scope

1.071

0.387

0.917-1.251

0.974

0.718

0.843-1.124

1.391

0.001

1.138-1.702

Decrease in the number of customers causing problems

0.666

0.009

0.491-0.903

0.781

0.083

0.590-1.033

0.876

0.596

0.537-1.430

Decrease in disputes with customers

1.379

0.047

1.005-1.893

1.310

0.067

0.981-1.751

2.177

0.004

1.275-3.718

Worker satisfaction

2.049

< 0.001

1.664-2.524

1.419

< 0.001

1.176-1.711

2.234

< 0.001

1.577-3.165

  1. -2 Log Likelihood = 2558.639, df=36, p= <.001
  2. Cox and Snell R2 = .251, Nagelkerke R2 = .292