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Licensed Unlicensed Requires Authentication Published by De Gruyter Oldenbourg May 10, 2017

Does Social Media Increase Labour Productivity?

Miruna Sarbu

Abstract:

Social media applications such as wikis, blogs or social networks are being increasingly applied in firms. These applications can be used for external communication and internal knowledge management. Firms can potentially increase their productivity by optimising customer relationship management, marketing, market research and project management. On the other hand, the use of social media might lead to shirking among employees and might be, in general, very time-consuming preventing employees from managing their normal workload. This might lead to a decrease of labour productivity. This paper analyses the relationship between social media applications and labour productivity using firm-level data of 907 German manufacturing and service firms. The analysis is based on a Cobb-Douglas production function. The results reveal that social media might be related to labour productivity in an negative way which points towards a suboptimal use of social media.

JEL Classification: L10; M20; O33

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Appendix

Table 6:

Distribution of firms across industries.

IndustryObservationsPercentage
Consumer goods818.93
Chemical industry485.29
Other raw materials576.28
Metal and machine construction727.94
Electrical engineering9710.69
Precision instruments626.84
Automobile313.42
Retail trade556.06
Wholesale trade505.51
Transportation and postal serv.657.17
Media services283.09
Computer and telecommunication services808.82
Financial services454.96
Real estate and leasing services232.54
Management consultancy and advertising242.65
Technical services677.39
Services for enterprises222.43
Sum907100

  1. Source: ZEW ICT Survey, own calculations.

Table 7:

Correlations between social media applications: correlation coefficients.

WikiBlogSocialCollaborationPrivatePrivatePrivate
networkPlatformWikiBlogSocial
network
Wiki1.00
Blog0.191.00
Social
Network0.190.551.00
Collaboration
Platform0.340.130.131.00
Private
Wiki0.190.140.180.181.00
Private
Blog0.170.270.180.180.311.00
Private
Social network0.180.210.250.210.280.291.00

  1. Source: ZEW ICT Survey, own calculations.

Table 8:

Firm characteristics by use of social media applications.

VariableWikiBlogSocialCollaboration
networkplatform
Sales 2009 (in mio)52.9433.9945.90210.34
Number of employees 2009277284274505
Investments 2009 (in mio)4.583.452.808.27
Labour productivity 2009 (sales per emp.)0.170.130.160.22
Share of employees with PC 20070.650.590.610.62
Share of export sales 20060.190.100.120.14
Share of high qualified employees 20060.380.300.300.35
Share of medium qualified employees 20060.480.530.540.50
Share of low qualified employees 20060.080.090.090.09
Share of employees <30 years 20060.260.230.240.26
Share of employees 3050 years 20060.570.580.570.54
Share of employees >50 years 20060.160.180.170.18
Share of firms using B2B e-commerce 20070.750.690.680.72
Share of firms using B2C e-commerce 20070.180.330.290.24
Share of firms with training 20060.730.880.860.93
Share of firms with consulting 20060.910.760.740.81

  1. Source: ZEW ICT Survey, own calculations.

Table 9:

2SLS regression with all social media dummies: second stage.

Dependent variable: log labour productivity
(1)(2)(3)(4)(5)
Constant term1.0921.4901.5471.5391.562
(0.510)(0.450)(0.438)(0.440)(0.437)
Log. labour0.2390.1880.1720.1780.168
(0.087)(0.075)(0.073)(0.074)(0.073)
Log. investments0.3670.2840.2730.2760.276
(0.082)(0.076)(0.074)(0.074)(0.075)
Employees with PC (share of firms)0.3300.3300.3430.337
(0.133)(0.133)(0.133)(0.133)
Export activity (share of export sales)0.4860.4600.4780.447
(0.153)(0.151)(0.153)(0.154)
Highly qualified employees (share of empl.)0.3210.3300.3320.355
(0.184)(0.182)(0.183)(0.184)
Medium qualified employees (share of empl.)0.1130.1020.1130.111
(0.144)(0.142)(0.143)(0.143)
Employees <30 (share of employees)0.1090.1180.1070.106
(0.159)(0.156)(0.158)(0.156)
Employees >50 (share of employees)0.2930.3030.2970.300
(0.172)(0.172)(0.173)(0.174)
B2B e-commerce (dummy variable)0.0180.0080.0100.001
(0.059)(0.058)(0.059)(0.059)
B2C e-commerce (dummy variable)0.0150.0280.0220.027
(0.070)(0.069)(0.069)(0.069)
Training (dummy variable)0.0080.0120.0070.011
(0.073)(0.072)(0.072)(0.072)
Consulting (dummy variable)0.0550.0490.0510.045
(0.059)(0.058)(0.059)(0.058)
East Germany (dummy variable)0.2860.2880.2900.290
(0.062)(0.061)(0.061)(0.061)
Wiki (dummy variable)0.008
(0.080)
Blog (dummy variable)0.2870.272
(0.080)(0.087)
Social network (dummy variable)0.1580.021
(0.073)(0.079)
Collaboration platform (dummy variable)0.092
(0.077)
Industry dummies (dummy variables)yesyesyesyesyes
R20.0950.2440.2640.2550.263
χ2(1)(Wald test)12.88(0.000)4.59(0.032)13.33(0.009)
Number of observations907854854852851

  1. Significance levels: : 10%, : 5%, : 1%. Robust standard errors in parentheses. Reference categories: unqualified employees, employees 30–50 years. Labour and investments instrumented in all specifications with their values of 2006.

Table 10:

FSLR with instrumented labour, investments and social media: first stage regression of Table 5, Column 4 (I).

Dependent variable: dummy for use of social software
Employees with PC (share of firms)0.104
(0.063)
Export activity (share of export sales)0.065
(0.080)
Highly qualified employees (share of employees)0.181
(0.094)
Medium qualified employees (share of employees)0.065
(0.066)
Employees <30 (share of employees)0.071
(0.084)
Employees >50 (share of employees)0.041
(0.089)
B2B e-commerce (dummy variable)0.072
(0.031)
B2C e-commerce (dummy variable)0.001
(0.037)
Training (dummy variable)0.034
(0.035)
Consulting (dummy variable)0.036
(0.031)
East Germany (dummy variable)0.018
(0.031)
Industry dummies (dummy variables)yes
Log. labour 20060.056
(0.014)
Log. investments 20060.005
(0.009)
Private use of wiki (dummy variable)0.086
(0.042)
Private use of blog (dummy variable)0.208
(0.055)
Private use of social network (dummy variable)0.167
(0.037)
Constant term0.169
(0.100)
Observations844
R20.266
F-statistic (test for weak instruments)13.79(p=0.000)
Hansen-Sargan test: Hansen’s J Chi2(2): 2.93304(p=0.2307)
Hausman test: robust score Chi2(3): 15.2048(p=0.0016)
Hausman test: robust regression F(3,810): 4.99168(p=0.0020)

  1. Significance levels: : 10%, : 5%, : 1%. Robust standard errors in parentheses. Reference categories: unqualified employees, employees 30–50 years.

Table 11:

FSLR with instrumented labour, investments and social media: first stage regression of Table 5, Column 4 (II).

Dependent variable: log. labour 2009 (log. number of employees)
Employees with PC (share of firms)0.103
(0.101)
Export activity (share of export sales)0.048
(0.084)
Highly qualified employees (share of employees)0.221
(0.155)
Medium qualified employees (share of employees)0.178
(0.117)
Employees <30 (share of employees)0.190
(0.113)
Employees >50 (share of employees)0.202
(0.135)
B2B e-commerce (dummy variable)0.071
(0.032)
B2C e-commerce (dummy variable)0.036
(0.041)
Training (dummy variable)0.038
(0.049)
Consulting (dummy variable)0.012
(0.036)
East Germany (dummy variable)0.008
(0.037)
Industry dummies (dummy variables)yes
Log. labour 20060.944
(0.023)
Log. investments 20060.031
(0.013)
Private use of wiki (dummy variable)0.005
(0.047)
Private use of blog (dummy variable)0.097
(0.055)
Private use of social network (dummy variable)0.040
(0.042)
Constant term0.030
(0.170)
Observations844
R20.906
F-statistic (test for weak instruments)232.42(p=0.000)
Hansen-Sargan test: Hansen’s J Chi2(2): 2.93304(p=0.2307)
Hausman test: robust score Chi2(3): 15.2048(p=0.0016)
Hausman test: robust regression F(3,810): 4.99168(p=0.0020)

  1. Significance levels: : 10%, : 5%, : 1%. Robust standard errors in parentheses. Reference categories: unqualified employees, employees 30–50 years.

Table 12:

FSLR with instrumented labour, investments and social media: first stage regression of Table 5, Column 4 (III).

Dependent variable: log. investments 2009
Employees with PC (share of firms)0.283
(0.219)
Export activity (share of export sales)0.008
(0.274)
Highly qualified employees (share of employees)0.245
(0.359)
Medium qualified employees (share of employees)0.274
(0.305)
Employees <30 (share of employees)0.085
(0.315)
Employees >50 (share of employees)0.176
(0.378)
B2B e-commerce (dummy variable)0.074
(0.111)
B2C e-commerce (dummy variable)0.037
(0.131)
Training (dummy variable)0.165
(0.157)
Consulting (dummy variable)0.055
(0.116)
East Germany (dummy variable)0.155
(0.115)
Industry dummies (dummy variables)yes
Log. labour 20060.678
(0.055)
Log. investments 20060.319
(0.044)
Private use of wiki (dummy variable)0.052
(0.134)
Private use of blog (dummy variable)0.245
(0.155)
Private use of social network (dummy variable)0.027
(0.109)
Constant term3.988
(0.615)
Observations844
R20.547
F-statistic (test for weak instruments)39.01(p=0.000)
Hansen-Sargan test: Hansen’s J Chi2(2): 2.93304(p=0.2307)
Hausman test: robust score Chi2(3): 15.2048(p=0.0016)
Hausman test: robust regression F(3,810): 4.99168(p=0.0020)

  1. Significance levels: : 10%, : 5%, : 1%. Robust standard errors in parentheses. Reference categories: unqualified employees, employees 30–50 years.

Published Online: 2017-5-10
Published in Print: 2017-6-27

© 2017 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston

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