Live Covid-19
United States 100,906,111
Cases: 100,906,111
Deaths: 1,106,990
Recovered: 98,320,554
Active: 1,478,567
India 44,674,874
Cases: 44,674,874
Deaths: 530,633
Recovered: 44,138,805
Active: 5,436
France 38,078,565
Cases: 38,078,565
Deaths: 159,245
Recovered: 37,022,916
Active: 896,404
Germany 36,557,861
Cases: 36,557,861
Deaths: 158,198
Recovered: 35,913,000
Active: 486,663
Brazil 35,436,031
Cases: 35,436,031
Deaths: 690,298
Recovered: 34,262,104
Active: 483,629
South Korea 27,408,854
Cases: 27,408,854
Deaths: 30,793
Recovered: 26,431,550
Active: 946,511
Japan 25,268,073
Cases: 25,268,073
Deaths: 50,461
Recovered: 20,766,771
Active: 4,450,841
Italy 24,488,080
Cases: 24,488,080
Deaths: 181,733
Recovered: 23,799,178
Active: 507,169
United Kingdom 24,024,746
Cases: 24,024,746
Deaths: 197,253
Recovered: 23,758,420
Active: 69,073
Russia 21,623,268
Cases: 21,623,268
Deaths: 392,283
Recovered: 21,023,627
Active: 207,358
Turkey 17,005,537
Cases: 17,005,537
Deaths: 101,400
Recovered:
Active: 16,904,137
Spain 13,614,807
Cases: 13,614,807
Deaths: 116,108
Recovered: 13,403,322
Active: 95,377
Vietnam 11,518,149
Cases: 11,518,149
Deaths: 43,177
Recovered: 10,608,988
Active: 865,984
Australia 10,759,272
Cases: 10,759,272
Deaths: 16,264
Recovered: 10,546,102
Active: 196,906
Argentina 9,739,856
Cases: 9,739,856
Deaths: 130,034
Recovered: 9,591,684
Active: 18,138
Netherlands 8,544,770
Cases: 8,544,770
Deaths: 22,920
Recovered: 8,499,904
Active: 21,946
Taiwan 8,379,467
Cases: 8,379,467
Deaths: 14,500
Recovered: 8,054,926
Active: 310,041
Iran 7,559,924
Cases: 7,559,924
Deaths: 144,645
Recovered: 7,335,330
Active: 79,949
Mexico 7,132,792
Cases: 7,132,792
Deaths: 330,525
Recovered: 6,400,759
Active: 401,508
Indonesia 6,682,437
Cases: 6,682,437
Deaths: 160,026
Recovered: 6,474,271
Active: 48,140
Poland 6,354,511
Cases: 6,354,511
Deaths: 118,340
Recovered: 5,335,940
Active: 900,231
Colombia 6,318,021
Cases: 6,318,021
Deaths: 141,911
Recovered: 6,142,640
Active: 33,470
Austria 5,583,979
Cases: 5,583,979
Deaths: 21,230
Recovered: 5,515,749
Active: 47,000
Portugal 5,546,290
Cases: 5,546,290
Deaths: 25,517
Recovered: 5,501,942
Active: 18,831
Greece 5,404,690
Cases: 5,404,690
Deaths: 34,309
Recovered: 5,345,133
Active: 25,248
Ukraine 5,341,284
Cases: 5,341,284
Deaths: 110,586
Recovered: 5,217,903
Active: 12,795
Malaysia 5,001,908
Cases: 5,001,908
Deaths: 36,716
Recovered: 4,943,392
Active: 21,800
Chile 4,939,304
Cases: 4,939,304
Deaths: 62,587
Recovered: 4,867,554
Active: 9,163
North Korea 4,772,813
Cases: 4,772,813
Deaths: 74
Recovered: 4,772,739
Active: 0
Israel 4,729,614
Cases: 4,729,614
Deaths: 11,882
Recovered: 4,704,016
Active: 13,716

Effect of Integrated Personnel Payroll Information System (IPPIS) on Cost Reduction in Federal Universities in South East Nigeria

Effect of Integrated Personnel Payroll Information System (IPPIS) on Cost Reduction in Federal Universities in South East Nigeria

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  • October 6, 2022
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ABSTRACT

The study examined the Influence of integrated Personnel and Payroll information system (IPPIS) on cost reduction in South-East Federal universities. The specific objectives were to: Assess the influence of IPPIS recruitment/payroll records on cost reduction in South-East Federal Universities; determine the influence of IPPIS promotion records on cost reduction in South-East Federal Universities and identify the influence of IPPIS retirement and pension records on cost reduction in South-East Federal Universities. The study used the descriptive survey design approach. A total population of four thousand, five hundred and twenty-five (4525), staff was used. The sample size of 354, using Freund and William’s statistic formula at 5 percent margin of error. 297 staff returned the questionnaire and accurately filled. Data was presented and analyzed by mean score and Z – test was used to test the hypotheses. The findings showed that IPPIS recruitment/payroll records had significant positive influence on cost reduction in South-East Federal Universities, Z (95, n = 297), 6.67 < 12.069 = p. < 0.05. IPPIS promotion records had significant positive influence cost reduction in South-East Federal Universities, Z (95, n = 297), 7.181 < 9.038= p. < 0.05 and IPPIS retirement and pension records had significant positive influence cost reduction in South-East Federal Universities, Z (95, n = 297), 8.109 < 9.284 = p. < 0.05. The study concluded that IPPIS recruitment/payroll records, IPPIS promotion records and IPPIS retirement and pension records had significant positive influence on cost reduction in South-East Federal Universities. The study recommended that all the staff of the Universities should have their payroll presentation for all the employees of the institutions at the centralized state treasury and each staff records should be centrally and properly kept with vital accounting packages.

Keywords: Integrated Personnel Payroll Information System (IPPIS); Cost Reduction; Recruitment/Payroll Records; Promotion Records; Federal Universities

Authorship: Prof. Eze, F. O. and Asso. Prof. Nnamani, E. | FULL PDF

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