Global Journal of Social Sciences Studies

Volume 3, Number 2 (2017) pp 101-112 doi 10.20448/807. | Research Articles


Procedural Fairness in Restructuring and Layoffs between two Telecom Companies of Pakistan

Jibran Hussain 1Hassan Ali 2 Mobashar Sadik 2 Saba Qasim 4
1 Institute of Public Policy, RIPHAH International Univeristy, Islamabad, Pakistan
2 Department of Engineering Management, Center for Advanced Studies in Engineering, Islamabad
4 School of Business Management (SBM), College of Business (COB), University Utara Malaysia (UUM), Sintok, Malaysia


This study compares impact of Procedural Fairness in Layoffs and Restructuring on Employee satisfaction between two telecom companies [Pakistan Telecommunication Company Limited (PTCL) and Nokia Siemens Network (NSN)] operating in Pakistan. An instrument is developed to collect data, through convenient based nonprobability sampling, whereas, sample size of the target audience is determined through Power and Precision method. Correlation coefficient shows strong positive association between Procedural Fairness in Restructuring and Layoffs with Employee Satisfaction in case of NSN then PTCL. Moreover, regression analysis show that Procedural Fairness in Restructuring and Layoffs are fairer in case of NSN as compare to PTCL. These processes have matured in case of NSN, where employees are more satisfied with the Procedural Fairness in Layoffs than Restructuring. Whereas, employees are not or least satisfied with the Procedural Fairness in Restructuring and found these procedures as shock in case of PTCL, with the least satisfactory level.

Keywords:  Procedural fairness, Distributive fairness, Restructuring, Layoffs, Organizational commitment, NSN, PTCL.

DOI: 10.20448/807.

Citation |Jibran Hussain; Hassan Ali; Mobashar Sadik; Saba Qasim (2017). Procedural Fairness in Restructuring and Layoffs between two Telecom Companies of Pakistan. Global Journal of Social Sciences Studies, 3(2): 101-112.

Copyright: This work is licensed under a Creative Commons Attribution 3.0 License

Funding : This study received no specific financial support.

Competing Interests: The authors declare that they have no competing interests.

History : Received: 16 August 2017/ Revised: 19 September 2017/ Accepted: 4 October 2017/Published: 16 October 2017

Publisher: Online Science Publishing


Globalization has its multifold impacts on economy of Pakistan. Large scale telecom companies emerged with well extended and expanded employment packages. Telecom and Information Technology remained one of the top sectors, responsible for domestic employment expansion and a greater source of Foreign Direct Investment (FDI). These changes have multi fold impacts on economy, improving human resource (HR) practices, employment opportunities, business development, entrepreneurship, tax collection, connectivity and corporate responsibilities are notable. However, financial crisis of last decade hit almost every business around the world. Modern business management objective remained more prone towards cost minimization for profit maximization. Cost cutting philosophies have been adopted by several multinational companies working in Pakistan, which thus resulted in handsome layoffs in this sector, as can be seen in the following graph (1);


Along with multinationals, domestic entity, Pakistan Telecommunication Corporation Limited (PTCL), since 1996, has been managing its operational management on cost cutting philosophy, under Voluntary Separation Schemes (VSS). Thus, in 2007-08 alone more than thirty thousand employees, almost 60% staff were laid off and this policy remained in continuation through 2012, 2014 and 2016, as a result almost fifteen thousand employees were laid off. PTCL once the national giant of more than sixty thousand employees is now limited to just fourteen thousand employees. Cost effective techniques and layoffs are essential for profitability with strict efficiency. However, the process of layoffs requires complete, fair and sustainable transfer of value in terms of process, procedures, information, retirement plans and economic security of the employees, his, thus translates into the welfare of employees. On the contrary, thousands of employees (VSS-08) are still are waiting for their social benefits. This study compares the process of restructuring and layoffs between NSN and PTCL. And how they treated their employee before, during and after the processes.

Term ‘Procedure’ refers to prescribed rules of how things are done, and ‘fairness’ is a persistent concern in social life. So, procedural fairness deals with that quality of procedures which results into a guarantee of fair outcomes between different relations (Verhoogen et al., 2002; Solari, 2003). Generally, it refers to the unfair or fair procedural rules which are implemented in management decisions e.g. hiring practices, resource allocation, salary increment, and policy-making within a group or an organization (Cremer et al., 2008). Group members rely on organizational procedures to reduce their uncertainty. The foundation of common uncertainty can be beliefs, attitudes, feelings, perceptions, and social relations (Blader, 2007; Cremer et al., 2008). According to justice theory, procedural fairness is usually positively related to an extensive array of psychological behaviors and experiences. When procedures are prevention focused rather than promotion focused then fairness has inverse relation with the people self-evaluations (Brockner et al., 2008). In various organizations procedural fairness has proved to impact positively, particularly on employee satisfaction and their interrelationships (Cropanzano et al., 2001; Van, 2005). Two recognized concepts of procedural fairness are: i) intention-based reciprocity which does not need a role of intentionality and ii) outcome-based inequity aversion which considers diversion from fairness concerning the actually attained outcome (Trautmann and Wakker, 2010). Past few decades has witnessed increasing rates of employee participation in decision making process. The relationship between participation and job tension is very complex while interpersonal trust has only a fractional mediating effect; procedural fairness has a full mediating effect (Lau and Tan, 2006; Prooijen and Zwenk, 2009). The relationship between procedural fairness and self-esteem is more evident among managers than non-managers because managers play major roles in determining the response of their subordinates, especially in vital organizational transitions such as downsizing (Wiesenfeld et al., 2000). Downsizing refers to the methods utilized to accomplish a work force diminution such as attrition without replacement, early retirement, outplacement, and layoffs. Different approaches are used depending on their speed of goal achievement, the level to which the organization retains control, and ill effects on employees (Jianga. and Gary, 2000). Fairness is enhanced, particularly when the decision makers treat the subordinates with pride and announce decision in time (Bies, 2001;2005). Downsizing and restructuring process in organizations have infused a sense of uncertainty about jobs among employees at all ranks and job insecurity emerges among employees who survive initial layoffs after a downsizing process. On the other hand, employers also need to retain human element by providing an atmosphere of job security in order to keep their productive human resource efficient and motivated (Astarlioglu et al., 2011). The restructuring and layoff processes, most of the times results in undesirable outcomes for employees. But this consequence is even prominent if it lacks the procedural justice (Brockner and Wiesenfeld, 2005). Two types of layoffs are;  i) under indirect layoffs, employees are expected to obey willingly; e.g., by transfers to different jobs or locations. ii) Direct layoffs, employees are offered help in adjusting to the termination. (Patterson and Flanagan, 1983). Subsequent from fair procedures, more a person bases his self-identity on his relationships with others, more positively he responds to an unfavorable result. On the contrary, more a person bases his self-identity on achievement, more negatively he reacts to an unfavorable result. It means that, competitive employees respond negatively to fair treatment when receiving undesirable results (Holmvall and Bobocel, 2008). More frequently, procedural justice judgments are made in situations where there is unclear information if fairness is truly occurring. Strong identification and desirable outcomes make people believe that group procedures are fair (Blader, 2007). The empirical analysis of justice is limited mostly to wage distribution, compensating wage disparity, and comparison wage rates but the data related to non-monetary components of fairness are incomplete, which makes it difficult to explore the relation between fairness and on-job well-being. Traditional models of worker utility merely consider inputs and outputs, i.e. effort and the wage, leaving the organizational routines task restricted. This issue needs to be addressed because bad performance may signal the necessity to alter routines, and fairness is a fundamental field of intervention if employee well-being is to be enhanced. It is observed that because of lower degree of procedural fairness, satisfaction and loyalty levels are lower in the public sector organizations (Tortia, 2008). The model of procedural justice includes: i) Cooperation in groups e.g. employees and employers, voters and political leaders and so forth (Cremer et al., 2008). (ii) procedural justice, iii) social identity and, iv) behavioral engagement, which are believed to underlie overall procedural justice evaluations (Blader and Tyler, 2003). Organizations that do not take procedural justice into account run the risk to provoke negative organizational attitudes, dissatisfaction with organizational and decisions, disobedience with rules and lack of cooperation among group authority and the group members (Lau and Tan, 2006; Prooijen and Zwenk, 2009). Managing relationships between organizational politics and the performance measures, interpersonal facilitation and job dedication, is a crucial task for managers and organizational structures should be designed to inculcate fairness in employee-organization interactions (Aryee et al., 2004). Human Resource staff also plays major role in ethics management and fairness that can provide real benefits for both the organization and its employees (Weaver and Trevino, 2001).

Organizational procedural justice can be distinguished into two groups; i) interpersonal justice e.g., manager demeanor, concerns for sabotage, and escorting layoff victims off the premises and, ii) layoff informational justice, which involve communicating a very negative decision to individual ‘‘victims’’ e.g., advanced notice, method of informing, and amount of information. Many companies use individual meetings when informing victims but group notification is used more as the size of the layoff increases (Gilliland and Schepers, 2003). Layoffs infuse a number of normally undesirable psychological states for survivors. Subsequently, job insecurity and job stress may possibly increase (De Vries and Balazs, 1996) and these negative states are most likely to affect important work attitudes and behaviors, including satisfaction, performance, commitment, and turnover (Sweeney and Quirin, 2009).

Quality of the replacement jobs is considered keenly by executives after their layoffs. Many downsized managers end up “underemployed” in jobs that are at lower levels than their previous jobs, for which they are over-qualified and pay less money (Feldman and Leana, 2000). Giving advance notice to subordinates and dealing with departing managers fairly has two complementary benefits. From the employees’ perception, it gives time to downsized managers to adjust to the distress of job loss, to leave self-esteem intact, and to depart with higher energy to find acceptable reemployment rapidly. In accordance with Fairness Theory, there are three major issues to think about when attributing responsibility to organizations for unfair acts. Organizations are held accountable when an alternative state would have been better than a current situation, when the firm could have feasibly avoided creating the negative conditions, and when the harm should never have taken place (Cropanzano et al., 2001). To cope with the injustice, one must learn to recognize it initially. Once this threshold of accountability is traversed, juristic persons will respond because there is no other choice. For example, when AT&T downsized, procedural justice could have diminished adverse employee responses by involving them in the planning process and announcing layoff procedures immediately following the restructuring. Also, voluntarily preceding executive compensation could have provided symbolic assurance to employees and the media that AT&T was sensitive to worker concerns (Christen, 2005).


Instrument: The items of the instrument were originally selected in anticipation of two sub scales; one for procedures and one for quality of interactions. The survey was developed keeping the dimensions of procedural fairness in restructuring and layoffs. Responses are obtained using 5-point Likert scale, where 1 = higly accurate, 2=accurate, 3= neutral, 4= inaccurate and 5 = higly inaccurate. Similar instrument was also used by Mansour-Cole and Scott (1998). The instrument describes the fairness of procedures used in an organization during company restructuirng and associated layoffs. It also describes the respect and consideration shown to employees during the implementation of these procedures. The measure uses fourteen items to access employee perceptions of the way they are treated by management from both an interactive and a procedural stand point.

Varaibles: We applied factor analysis for defining and develoing our variables, and computed three variables each for both set of data; Employee Statisfaction (ES) as dependent variable whereas, Procedural Fainess in Restructuring (PFR) and Procedural Fairness in Layoffs (PFL) as two Independent variables.

Data Collection: A convenient non-probablity radom sampling method is used to collect data from the target population. A multinational telecom vendor, Nokia Siemens Network (NSN), working in private sector and a national telecom service provider, Pakistan Telecommunication Limited (PTCL), working in public sector are selected for study.

Consistency Test: Cronbach Alpha test is used to measure the internal consistancy and stability of the variables. The results of the test based on standrized items; 0.93 and 0.68 for NSN and PTCL respectively.

Estimations: The degree and direction of association is measured through correlation analysis, where as, direction of causation is estimated through general multi varibale regression analysis. The competence of regression results were cross examined through the process of Path Analysis.


The descriptive analysis of fourteen items of the instrument is in the following table. Where, the percentage responses head to head comparing the employee satisfaction of NSN and PTCL are stated below:

  Response rates
Question Company    1             2              3             4           5
Whether the decisions of job reductions and reassignments are followed by kind and respected treatment of management. PTCL 0% 16.7% 16.7% 66.7% 0%
NSN 10% 53.3% 28.3% 8.3% 0%
Whether the employees concerns were heard before making decisions of job changes and eliminations PTCL 13.3% 15% 11.7% 58.7% 1.7%
NSN 0% 36.7% 21.7% 35% 6.7%
Whether the management offered explanations about job change and elimination decisions PTCL 1.7% 35% 13.3% 50% 0%
NSN 0% 53.3% 31.7% 8.3% 6.7%
Whether the management was sensitive to personal needs.. PTCL 0% 30% 8.3% 61.7% 0%
NSN 0% 30% 28.3% 25% 16.7%
Whether the management collected all necessary information PTCL 0% 75% 16.7% 8.3% 0%
NSN 10% 25% 48.3% 16.7% 0%
Whether the management explained clearly all reasons for retructuring PTCL 15% 65% 15% 5% 0%
NSN 33.3% 31.7% 8.3% 6.7% 20%
Whether the employee was treated wit respect and dignity after taking the job change and elimination decisions PTCL 0% 56.7% 15% 28.3% 0%
NSN 10% 31.7% 38.3% 20% 0%
Whether the management treted in truthful manner about restructuring decisions. PTCL 1.7% 70% 15% 13.3% 0%
NSN 10% 45% 31.7% 6.7% 6.7%
Whether the managemnt clarifie the decisions and provided extra information demanded by the employee. PTCL 3.3% 26.7% 21.7% 45% 3.3%
NSN 10% 43.3% 38.3% 8.3% 0%
Whether the management showed some concern for the rights of the employee. PTCL 1.7% 30% 18.3% 46.7% 3.3%
NSN 10% 33.3% 38.3% 11.7% 6.7%
Whether the jb decisios were aplied consistently. PTCL 1.7% 15% 26.7% 56.7% 0%
NSN 10% 43.3% 21.7% 15% 10%
Whether the employees had a rigt to appeal. PTCL 1.7% 13.3% 26.7% 58.3% 0%
NSN 10% 16.7% 31.7% 28.3% 13.3%
Whether the employee at his job level have adequate input to restructuring decision process. PTCL 1.7% 18.3% 10% 70% 0%
NSN 0% 20% 28.3% 41.7% 10%
Whether the procedures were available for timely infoormation. PTCL 1.7% 73.3% 15% 10% 0%
NSN 10% 15% 41.7% 23.3% 10%

3.1. Estimations For Nsn

Table-3.1. **. Correlation is significant at the 0.01 level (2-tailed).
Correlations NSN
    PFR ES
PFR Pearson Correlation 1 .775**
  Sig. (2-tailed)   .000
PFL Pearson Correlation .948** .833**
  Sig. (2-tailed) .000 .000

The correlation coefficient (r) between Employee Satisfaction and Procedural Fairness in Restructuring is positive (0.77**) and statistically significant with p-value (0.000). Similarly, there exist strong positive and statistically significant correlation (0.833**, 0.000) between Employee Satisfaction and Procedural Fairness in Layoffs. Results also show very high positive and significant association (0.95**, 0.000) between Procedural Fairness in Layoffs and Procedural Fairness in Restructuring, in case of NSN data.

3.1a. DV: employeesatisfaction (ES), Predictors: PFR, PFL
Model Summary NSN
Model R R Square Adjusted R Sq SE of the Estimate    
1 .834a .696 .685 .47841    
Model   SS df Mean Square F Sig.
1 Regression 29.812 2 14.906 65.126 .000b
  Residual 13.046 57 .229    
  Total 42.858 59      
Coefficientsa NSN
    Unstandardized Standardized    
Model   B Std. Error Beta t Sig.
1 (Constant) .026 .273   .095 .924
  PFR -.148 .240 -.142 -.617 .540
  PFL 1.092 .259 .967 4.214 .000

Model 1. NSN
[EmployeeSatisfaction =a – B(PFR)+B1(PFL)]  (-0.14)(PFR)    +   (0.96)(PFL)
(0.54)              (0.000)**   

The results from table 3.1 shows that variation in independent variables (PFR and PFL) in this model (1) significantly explain {(F, 65), (Sig, 0.00)} the variation in dependent variable with coefficient of determination R-Sq (0.69). However, the variable, Procedural Fairness in Restructuring (PFR) shows negative but non-significant impact on employee satisfaction in case of NSN. Which implies that the employees are not satisfied with restructuring procedures. Whereas, Procedural Fairness in Layoffs (PFL) shows strong positive and statistically significant impact on employee satisfaction. This implies that the employees at NSN consider the fairness procedure in layoffs more effective than procedures in restructuring. Although, statistically the impact of PFR on employee satisfaction is not significant however it does exist.

These results had quite interesting implications, so we applied path analysis to see if the regression results are reliable.

Figure-3.1.b. Importance of predictor

Similarly, the path analysis in figure 3.1c and 3.1d show that given all assumptions intact when tested for relevant and relative importance of predictors, in the process of explaining the variations in employee satisfaction, in case of NSN, the model show that only PFL has strong significant and important impact on the path. Whereas, the role of PFR in here has no significant role. As, in fig 3.1d, there is no path from PFR towards employee satisfaction. Implying nonsignificant role of PFR.

4.2a *. Correlation is significant at the 0.05 level (2-tailed).
Correlations PTCL
PFR Pearson Correlation 1 .279* .349**
PFL Pearson Correlation   1 .834**
**. Correlation is significant at the 0.01 level (2-tailed).

The correlation coefficient between Employee Satisfaction and Procedural Fairness in Restructuring is positive (0.349**) and statistically significant with p-value (0.000). Similarly, there exist strong positive and significant correlation (0.83**, 0.000) between Employee Satisfaction and Procedural Fairness in Layoffs. However, there is weak but positive and significant association exists (0.279**, 0.000) between Procedural Fairness in Layoffs and Procedural Fairness in Restructuring, in case of PTCL data.

3.2b. Dependent Variable: ES , Predictors; PFL, PFR
Model Summary PTCL
Model R R Sq Adjusted R Sq SE Estimate    
2 .842a .709 .699 .34960    
Model   SS df Mean Sq F Sig.
2 Regression 17.012 2 8.506 69.594 .000b
  Residual 6.967 57 .122    
  Total 23.978 59      
Coefficientsa NSN
    Unstandardized Standardized    
Model   B Std. Error Beta t Sig.
2 (Constant) -1.087 .522   -2.08 .042
  PFR 1.110 .103 .798 10.7 .000
  PFL .272 .160 .126 1.69 .096

Model 2. PTCL
[EmployeeSatisfaction =a – B(PFR)+B1(PFL)] (0.126)(PFR)   +   (0.798)(PFL)    (0.096)           (0.000)**

The results from table 3.2b shows that variation in independent variables in this model (2) significantly explains {(F, 69), (Sig, 0.00)} the variation in dependent variable with coefficient of determination R-Sq (0.7) and adjusted R-Sq (0.69). 
On the other hand, the regression results show that PFL strongly explains the variation in the dependent variable in our model 2 with slope reaching almost 0.8 and is highly significant with p-value (0.000). Moreover, in case of PTCL Employee Satisfaction seems to have impact from Procedural Fairness in Restructuring, though the impact is weak with a coefficient value of 0.12 but it gets significant at 10% level.  This impact of PFR was missing in the model-1 for the NSN results.

In order to have support to the results of Model-2 we proceed with our path analysis, as we did for model-1.

Figure-3.2 c. Importance of predictors

As, we can see from figure 3.2c, that PFL has strong and relatively very importance in the model to explaining the variations in the employee satisfaction for PTCL employees. Whereas, the PFR (missing in NSN case) appears in case of PTCL data, but have very little or weak role in the process of explaining the variation in the dependent variable.

Figure-3.2d. Comparing IV effects on DV as target variable.
Figure-3.2e. Comparing IV effects on DV as target variable.

The figures 3.2d and 3.2e, shows the relative importance and intensity of independent variable/s in the process of explaining the variation in the dependent variable i.e., employee satisfaction. Once again it is evident that the PFL has strong role, importance and impact on the satisfaction level of employees in the process of layoffs, the bold line in black and blue in above two figures shows this effect.

On the other hand, interestingly, the predictor Procedural Fairness in Restructuring (PFR) in case of PTCL, shows a weak but significant role in the process. Which implies that the employees at PTCL consider the fairness procedures in restructuring important for their satisfaction. Although, statistically this effect compare to PFL is weak but it has its own dimensions and value. Which thus implies that PTCL employees has greater approach to the process of restructuring along with the fairness in the layoffs, this very impact was missing the NSN case. This also implies that there is greater possibility of errors and irregularities in the procedural fairness of restructuring. Not to mention that more than thirty thousand laid off employees has still reservations about their rights being not fulfilled during the process. As, we already have indicated that VSS 2008, batch of PTCL which accounts more than thirty thousand employees have not been registered with Social welfare and benefit programs i.e. EOB Act 1976 and Social Security Act.  On the other hand, those employees laid off have not been offered any structural programs.


The estimation implies tha the employees at NSN are treated with more repect and kindness when reductions and reassignments are made in their job description. The management at NSN gave more due importance to the the concerns of employees before any changes and elimintion decisions are made about jobs. In NSN the management offered more viable and sensible explanation about restructuring and layoffs. Management is more sensitive to personal needs of employees in NSN while restructuring and layoffs. Factor of Procedural Fairness in Restructuring have less impact on Employee Staisfaction then Procedureal Fairness in Layoffs in case of NSN. There is a mix response for clarity and truthful beahivour of executives while restructuring both in NSN and PTCL and the employees are also not given a clear right to provide an adequate support in such decisions. Management collects all necessary information and treat with more respect and dignity in PTCL. In provision of additional information and clarification demanded by employees, showing concern for the rights of employees, application of consistent job decisions for all employees and provision of right of appeal to employees; NSN employees are more satisfied as compared to PTCL employees. More timely information procedures are applied in NSN about layoffs and its implementation. The Procedural Fairness in Restructuring in case of PTCL has more impact on the process than NSN. Employees of PTCL are less satisfied with the layoff fairness.


The layoff processes have matured in NSN as a result employees are treated with more respect, dignity and truthfulness, there exist high level of employee satisfaction. However, the factor Procedural Fairness in Layoffs have strong positive explantion of the employee staisfaction then Procedural Fairness in Restructuring. People have adequate excess to information and their concerns are well addressed in NSN.

On the other hand, less exposure to restructuring and layoffs have caused a fear of outcomes the employees of PTCL. Although impact of PFR in case of PTCL is positive yet not significant. Employeed satisfection level from Fairness Procedures in Restructuring is very low, as we have seen in model-2 that the coefficeint of PFR is weak and non significant, thus implies that the restructring and reforms are new and act as shock in case of PTCL. Although most recently PTCL has been trying to give more importance to the process and management of procedural fairness. Also in context of extending benefits to their employees during and after the procedures. As Procedural Fairness in Layoffs showed strong significant impact on the employees for both companies, there needs enhancement of conceptual and managerial application of this process. Since, NSN has reduced to a very small firm, but PTCL still has thousands of employees and they have VSS programs in channel in the future. It requires an integrated strong policy to make effective fairness in the procedures of restructuring, especilly in case of PTCL.


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About the Authors

Jibran Hussain
Institute of Public Policy, RIPHAH International Univeristy, Islamabad, Pakistan
Hassan Ali
Department of Engineering Management, Center for Advanced Studies in Engineering, Islamabad
Mobashar Sadik
Department of Engineering Management, Center for Advanced Studies in Engineering, Islamabad
Saba Qasim
School of Business Management (SBM), College of Business (COB), University Utara Malaysia (UUM), Sintok, Malaysia

Corresponding Authors

Jibran Hussain

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