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Perceived Organizational Performance and Trust in project manager and top management in Project-based organizations: Comparative Analysis using Statistical and Grey Systems methods

Saad Ahmed JAVED*

College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, People’s Republic of China Department of Management Sciences, COMSATS Institute of Information Technology, Pakistan Email: [email protected]

Ali Murad SYED

College of Business Administration, Imam Abdulrahman Bin Faisal University, Dammam, Kingdom of Saudi Arabia Email: [email protected]

Sara JAVED

Institute for Grey Systems and Decision Sciences, GreySys International Foundation, Lahore, Pakistan Email: [email protected]

*corresponding author

To cite this paper: Javed, S.A., Syed, A.M., & Javed, S. (2018). Perceived Organizational Performance and Trust in Project Manager and Top Management in Project-based organizations: Comparative Analysis using Statistical and Grey Systems methods. Grey Systems: Theory and Application. DOI:10.1108/GS-01-2018-0009

ABSTRACT Purpose: The study aims to empirically analyze the relationship between trust in top management (TTM) and trust in immediate supervisor (TIS), who was organizational project manager in our case, on perceived organizational performance in Pakistani public and private project-based organizations (PBOs). Method: The survey (N =108) was done using a questionnaire that was sent to project managers in the selected PBOs in Pakistan with a request to forward it to their immediate subordinates. Latter, established statistical techniques (correlation and regression analyses) and grey incidence analysis models were applied to test the hypotheses. Findings: The results from both methods reveal that trust in top management was more strongly correlated to perceived organizational performance of PBOs and, in general, public sector employees are more trusting that private sector employees. The grey method revealed that in both private and public PBOs, trust in project manager is greater predictor of perceived organizational performance while statistical analysis confirmed this only for private sector PBOs. According to statistical analysis, the public sector employees who trust their top management are more likely to have good perception of the organizational performance. Later, the study argues that because of the proven superiority of grey methods over statistics on small samples, the results obtained from grey method should be used for decision making and implications. Originality: The study is pioneer in evaluating the association between trust in project manager and trust in top management in project-based organizations using both statistical and grey systems methods. Keywords: trust; top management; immediate supervisor; project-based organization; organizational performance; project manager; grey system theory; statistics; sample size

1. Introduction It has been observed that studies on the elements of success or failure of projects are usually impotent to analyze ―intra-project dynamics‖ and overlook human-related ―soft‖ dimensions of project evolution which are so essential for the project outcomes (Hobday, 2000). Most organizations tend to stress more on the process to achieve project deliverables and less on their employees‘ interaction with the project and organization (Hardy-Vallee, 2012). For instance, Levasseur (2010) concludes that 65 percent of the reasons of project failures in IT sector are due to people related issues and rest due to technical reasons. If even in a ‗technical sector‘ like IT the project failures due to ‗people issue‘ can amount to more than 60 percent then what could be the situation in non-technical sectors encompassing NGO management, construction management, disaster management etc? Perhaps, the figure could be quite alarming. A research

involving more than ten thousand projects from thirty countries, cited in Hardy-Valle (2012), reveals that just 2.5% of the firms effectively finished all of their projects. Thus, it can be argued that Project Managers are too obsessed with the ‗tangible deliverables‘ (physical outcomes) of the projects that they even sometimes oversee the human aspect that is directly responsible for the smooth functioning of the project management processes and organizational performance/productivity. As Weber, McEvily and Radzevick (2008) have demonstrated, lack of trust can result in increase in cost of doing business hence it can be argued that fields like project management where people related issues significantly impacts project failures or successes and achieving project deliverables within cost is the most important objective of almost all project managers, ignoring the role of trust is no more affordable by responsible organizations. Further, in underdeveloped countries like Pakistan where recourses are scarce and clients are becoming more and more conscious and demanding with the passage of time, effective and efficient utilization of resources to minimize project failures is of extremely significant importance. While considering aforementioned context, this research was undertaken to bridge the gap in project management literature concerning human side that is relatively ignored as compare to non-human (or technical) side that deals with management of tangible deliverables (time, cost and quality). Considering the fact that project management literature is more obsessed by the hard issues concerning project performance and less by the soft issues that involve people related aspects, the study identified two soft areas relating to management i.e., the trust in top management (TTM) and trust in immediate supervisor (TIS), and how they affect perceived organizational performance. The strength of their relationship was gauged in the environment surrounding project-based organizations (PBOs) with a view to fill the gap in literature as the review of literature suggested that examination of the strength of relationship of Perceived Organizational Performance with these two factors in PBO context is almost nonexistent. For the general readers, it should be noted that ―project-based organization (PBO) is an organizational form whereby projects are the primary units for coordinating and integrating production and innovation‖ (Wei & Miraglia, 2017). Further, the review of literature (see Ellis & Shockley‐ Zalabak, 2001) suggested that compared to TIS, TTM is more strongly linked to perceived effectiveness of organizations but in project-based organizations where immediate supervisor of the workforce (Project Manager) is more visible than Top Management to most of the employees, the existing research was almost silent. Also, even though the studies report that public sector employees tend to be more satisfied and more trusting than private sector employees (Zeffane & Melhem, 2017) but the relative importance of the trust in immediate supervisor and the trust in top management within public and private systems is not fully explored. More precisely, the research aims to look at the association of Perception of Organizational Performance with Trust in Immediate Supervisor (TIS) and Trust in Top Management (TTM) in Pakistan‘s project-based organizations through two alternative data analysis methods.

2. LITERATURE REVIEW There are quite abundant studies available on managerial trust and organizational trust in various contexts however when one desires two study the relationship of trust in immediate supervisor and trust in top management with the organizational performance in project-based organizations, the studies are scarce. The possible reason could be that initially project studies were obsessed with technical and engineering issues, with contexts built around the environment of Construction, Development and Engineering industries, whose performance was mostly ‗concrete‘ and tangible and the nature of their work was less operational and they mostly worked on time-bound assignments or projects. For such industries, the management of time and resources (cost) and meeting deliverables (quality) was of prime concern and their concern for work force was less apparent. However, the focus of project studies is now moving from more technical and engineering topics to a broader organizational perspective (Geraldi & Söderlund, 2018). With the evolution and development of Human Resource Management philosophy, the other fields, including Project Management, too evolved and organizations, both local and global, began seeing their workforce, not the machines and tools, as most essential organizational asset (see, e.g., Keegan et al., 2018; Sparrow et al., 2016; Fulmer & Ployhart, 2014). Today, project-based methods of working have become necessary in managing really unique, novel and transient operations and activities (Turner & Keegan, 2001) and thus managing projects in non-conventional way is a need of time. Also, as project management, or project organizing, is at crossroad of different fields it would continue benefiting from concepts and ideas from different fields further enriching its body of knowledge and practices. 2.1.Trust Trust is a very divisive concept in literature. Literature suggests that there exists scant agreement on what trust actually means (Khan, 2012) leading to absence of its universally recognized scholarly definition (Rousseau, Sitkin, Burt & Camerer, 1998) and difficulty in conceptualizing trust (Colquitt, Scott, & LePine, 2007; Warren, 2012). Different scholars have conceptualized trust differently in their studies. Some identifies trust having two forms, ―reliability/ dependability and emotional trust/faith‖, some categorize it into ―cognitive and affective trust‖ (Khan, Breitenecker, Gustafsson, & Schwarz, 2015) and for some, trust is a distinct phenomenon from trustworthiness and trust propensity (Colquitt et al., 2007). Chow and Chan (2008) and Milliken, Morrison and Hewlin (2003) have included trust in social capital as it is not a product of personal attributes of employees but an upshot of their interpersonal relationships. Based on a previous study, Mayer and Gavin (2005) concluded that ‗trust in management is important for organizational performance‘. Weber et al. (2008) have demonstrated, lack of trust can result in increase in cost of doing business hence it can be argued that fields like project management where people related issues significantly impacts project failures or successes and achieving project deliverables within cost is the most important objective of most of the project managers, ignoring the role of trust is no longer affordable by responsible organizations. Adler (2001) has summarized different dimensions and components of trust as shown in Figure 1.

Fig 1. Dimensions and Components of Trust (Source: Alder, 2001) The concept of trust is probably as primitive as the oldest forms of human relationship (Watson, 2005). Although trust remained a vital concept since ages but it received comparatively modest recognition in research until a little while back (Watson, 2005). In the most recent decade, trust has turn into an important study area within the field of organizational studies (Matzler & Renzl, 2006). Interest in the study of trust has been shown by researchers from different fields of knowledge like psychology, management, marketing, organizational behavior, public relations (Watson, 2005), entrepreneurship (Khan, Breitenecker, & Schwarz, 2014; Khan et al., 2015), sociology (Matzler & Renzl, 2006), ethics (Colquitt et al., 2007; Muller et al., 2013), economics (Falk & Kosfeld, 2004; Weber et al., 2008), education (Swain, 2007; Basch, 2012) and science (Haerlin & Parr, 1999; Gauchat, 2012). Even though this multi-disciplinary attention has enriched the concept but so much variety of studies has complicated incorporation of a range of views on trust into a concurrent viewpoint (Watson, 2005).

Trust is often recognized as a key concept in understanding managerial relationships and nourishing and keeping trust is regarded as crucial to productivity of organization and management (Watson, 2005). Studies reveal, trust influences individual performance (Colquitt et al., 2007; Naber, Payne & Webber, 2015), team performance (Dirks, 1999; Khan et al., 2015) and organizational performance (Watson, 2005; Salamon & Robinson, 2008). It has been reported that public sector employees tend to be more satisfied and more trusting than private sector employees (Zeffane & Melhem, 2017). In an environment where interpersonal trust is abundant, fewer resources are available for investigating trustworthiness of others and thus greater resources are available for productive activities (Lim, Morshed & Khun, 2018). Literature demonstrates that in relationships surrounded by superior level of trust, parties involved often sincerely try to help each other on long-run basis (Wang, Shi & Barnes, 2015). Not only in comprehending individual behavior, trust is equally significant in comprehending economic and financial behavior of an organization (Weber et al., 2008). It‘s relation to organizational performance is no more an unfamiliar concept within management literature thus

overlooking the role of trust in an organization can augment distrust resulting in adverse consequences for organization and its management. In this study, managerial trust or trust in management are used synonymously and is the sum of trust in top management and trust in immediate supervisor as defined by Ellis and Shockley‐ Zalabak (2001). This is a relatively new concept of seeing managerial trust in light of trust in immediate supervisor and top bosses and is quite relevant to Project management field as in projects, where Project Manager is immediate and direct supervisor of key personnel and functions whereas Top Management of the company are believe to be more visible to clients than to its workforce on project sites. Thus the study will facilitate how these two trusts varies for the project managers working on the projects of project-based organizations and how this trust in management affects perceived performance of the organizations.

2.1.1. Trust in Top Management and Trust in Immediate Supervisor Trust is a widely studied concept in social psychology literature and is gaining widespread attention in HR/management literature. Interpersonal trust, support, and respect are manifestations of high group cohesion in a team (APPM, 2012: pp.165). Trust is frequently supposed to be the ‗lubrication‘ that keeps an organization‘s social systems intact and advances its effectiveness and efficiency (Gould-Williams, 2003). Trust in management infuses more power and potency among the subordinates (Bahrami et al., 2012) and is important for organizational performance (Mayer and Gavin, 2005). McCauley and Kuhnert (1992) stressed that ―an employee may trust his peers but not his supervisor‖ thus the level of trust varies. Cook and Wall (1980) too have demonstrated in their research that there is nothing like one trust for all! Most of the works on trust and workplace relationships involves comprehension of managers and their immediate subordinates while trust in top management received very little attention in literature (Ellis & Shockley‐Zalabak, 2001). Employees believe top managers to have power over most of the attributes of organizations so if employees‘ perception concerning organizational attributes, like rules and regulations, are positive then their view concerning top managers are supposedly equally be positive and they are less likely to distrust their top management (McCauley & Kuhnert, 1992). Thus, without gauging trusts in management (top and immediate), it is not appropriate to comprehend how employees see their management and performance of their organization.

2.2.Perceived Organizational Performance In this study, the terms ‗perceived organizational performance‘, ‗perceived firm performance‘ and ‗perception of organization‘s performance‘ are used interchangeably and are abbreviated as ―POP‖. An important factor related to trust is perceived organizational performance. Trust in an organization has been known as the ―feature of a thriving organization‖ (Bahrami et al., 2012). Prusak and Cohen (2001) signified the importance of trust and strong relationships as a social capital that glues an organization together. Bakieve (2013) also considered interpersonal trust an

important attribute of organizational social capital associated to perceived organizational performance and then revealed the influence of interpersonal trust on performance of Police. Allen, Dawson, Wheatley and White (2007) highlighted a brilliant discussion in performance measurement studies concerning two different measures to gauge organizational productivity, each with its own pros and cons. They say ―objective measure‖ are more absolute but are narrow in scope while ―subjective measures‖ lacks absoluteness or reproducibility but afford affluent depiction of a firm‘s productivity relative to its competitors and strengthens the generalizability of the research outcomes (Allen et al., 2007). Further, it has been proven that ‗subjective measures‘ involve ‗perceptual‘ attribute of investigation (Allen et al., 2007) and measures of POP is positively related to organization‘s ‗objective measures‘ (Delaney & Huselid, 1996; Carmeli & Schaubroeck, 2008; Singh, Darwish & Potočnik, 2016). It has also been observed that POP is also dependent on the performance of other organizations in the same industry (Herman & Renz, 2008). In the study by Delaney and Huselid (1996), ―perceptual measures‖ of organizational performance are found to be dependent on ―organizational performance‖ and ―market performance‖. Thus, using subjective measures to gauge organizational performance is not an inappropriate move and with carefully planning subjective measures can successfully access organizational performance (Singh et al., 2016).

2.3.Grey System Theory Grey System Theory (GST) is a theory first proposed by a Chinese professor Julong Deng with the publication of his two papers in 1982 (Mahmoudi et al., 2018; Liu & Forrest, 2007; Julong, 1982). Deng (1982) defined a grey system as ―a system containing knowns and unknowns‖, i.e., a system with incomplete information. Today the Grey System Theory has a well-developed body of knowledge that can be manifested in its Framework, which can be found in Liu, Yang and Forrest (2016: Chapter 2). The theory is in the phase of continuous evolution and has been successfully applied in various fields of natural and social sciences including engineering, economics, management and project management. One of the key advantages of this theory is that it can produce valid results even when sample size is small (Javed & Liu, 2018; Javed & Liu, 2017; Liu & Lin, 2007). This is one of the distinct features of this theory that makes it different from statistics (Ng & Deng, 1995). The theory proposes an alternative method to statistical data analysis and studies have found that in many cases the predictions made through grey systems methods were superior to the predictions made through statistical methods (see, e.g., Javed & Liu, 2018; Lin & Wu, 2011; Chen & Xie, 2005). Grey Incidence Analysis (GIA) models constitute important part of the Framework of GST. GIA models are also known as Grey Relational Analysis (GRA) models. First GIA model was proposed by Julong Deng and is now known as Deng‘s GIA model. Later, Professor Sifeng Liu proposed Absolute Degree GIA model, also called absolute GRA model. In a nutshell, Deng‘s GIA model gives the measure of influence that one variable represented by a data sequence exerts on the other and Absolute Degree GIA model gives the measure of association between them. The foundation of Deng‘s GIA model rests upon Deng’s degree of grey incidence, which is also known as grey relational grade. This degree is represented as γ0i or γ(X0, Xi) and is given by

Where,

Here, X0 = (x0(1), x0(2), …, x0(n)) and Xi = (xi(1), xi(2), …, xi(n)) are the sequences representing a grey system for ξ ∈ (0, 1), the distinguishing coefficient (Liu et al., 2016; Liu, Zhang & Yang, 2017). Usually, the scholars suppose the value of ξ to be 0.5 even though the rationale behind this supposition is not yet universally established. The computing steps to calculate Deng‘s Degree of Grey Incidence for two data sequences X0 and X1 are shown in Liu et al. (2016: pp.74) and have been reproduced below:

Step-I: Calculating the initial image (or average image) of X0 and Xi, i=1,2,…,m, Where, Xi` = Xi/xi(1) = (xi`(1), xi`(2), …, xi`(n)); i=0,1,2,..,m

Step-II: Computing the difference sequences of X0` and Xi`, i=1,2,…,m, as Δi(k) = │x0`(k) - xi`(k)│, Δ = (Δi(1), Δi(2), …, Δi(n)), i = 1, 2,…,m

Step-III: Finding the maximum and minimum differences M = maxi maxk Δi(k), m = mini mink Δi(k)

Step-IV: Calculating incidence coefficients γ0i(k) =

( )

Step-V: Computing the Deng‘s degree of grey incidence γ0i = ∑

( ), i=1,2,…,m

On the other hand, for a system represented by the sequences Xi and Xj, the Absolute Degree of Grey Incidence Analysis model is represented as ɛij = where,

Here, ɛij is absolute degree of grey incidence (Liu et al., 2016; Liu et al., 2017). The computational steps of the model are listed below: Step-I: Calculate the zero-starting point images of two sequences X0 and X1 Step-II: Calculate |s0|, |s1|, and |s1-s0| Step-III: Calculate absolute degree of grey incidence between the sequence X0 and X1 ɛ01 = For the detailed discussion on the Deng‘s and Absolute degree GIA models, their properties and calculation steps, Liu et al. (2016) can be consulted.

FRAMEWORK AND METHODOLOGY Framework and hypotheses Trust leads to enhanced organizational performance (Gloud-Williams, 2003). Studies (Delaney and Huselid, 1996; Carmeli and Schaubroeck, 2008; Singh et al., 2016) suggest that measures of POP are positively related to organization‘s ‗objective measures‘, i.e., a firm‘s real performance. In the work by Ellis and Shockley‐Zalabak, (2001) POP was found to be more strongly linked to TTM than to TIS. But how this relationship can vary in the project-based organizations where immediate supervisor (project manager) is more visible than top management (senior managers) to most of the employees, needed exploration. In light of these questions, the following hypotheses were proposed. H1: Trust in Top Management (TTM) is positively linked to Perceived Organizational Performance (POP).

H2: Trust in Immediate Supervisor/Project Manager (TIS) is positively linked to Perceived Organizational Performance (POP).

Instrument development and its testing Trust in management was considered as the sum of trust in top management (TTM) and trust in immediate supervisor (TIS) in the study. Six research items to gauge TTM (first independent variable) and fourteen research items to gauge TIS (second independent variable) were adapted from Ellis and Shockley‐Zalabak (2001) on 5-point likert scale with range from 1 (very little) to 5 (very great). Perception of Organization‘s Performance (POP), the dependent variable, was measured using the eleven research items adapted from Delaney and Huselid (1996) which considered perception of a firm‘s performance (POP) as the sum of perceived organizational performance (seven research items) and perceived market performance (four research items); on 5 point likert scale with range from 1 (much worse than others) to 5 (much better than others). To gauge the reliability of research instrument, Cronbach‘s alpha value of 11 items associated with POP was calculated that turned out to be 0.877. Cronbach‘s alpha value of the 6 items associated with TTM turned out to be 0.867. Cronbach‘s alpha value of the 14 items associated with TIS turned out to be 0.911. Therefore, the reliability of the research instrument was very good. However, the response rate was about 57 % (112/197). The reasons for low response rate could be attributed to the possibility that several respondents didn‘t either check their emails containing the questionnaire or the emails sent to them went into their spam folder. Another possibility that can‘t be ruled out is that may be many project managers whom the authors sent emails for forwarding them to their immediate subordinates failed to do so for the reasons best known to them. Data collection and analysis The respondents were interviewed using a questionnaire containing close-ended questions against five point likert-scale. An online questionnaire was created for this purpose. There were two parts of the questionnaire. One part contained Demographic Variables and the other part contained close-ended questions to gauge TTM, TIS and POP. Thus, the study involves respondents working in project-based organizations (PBOs) operating in six industries as defined in Kerzner (2009: pp.26). Difficulty in finding sufficient number of employees who directly report to project managers lead the researcher to seek the help of project managers themselves to approach their immediate subordinates. Two project managers from two different high-tech project management firms were contacted who provided to the researchers the email addresses of 224 project management practitioners working in Pakistan‘s project-based organizations (PBOs), on the condition of being anonymity. An online questionnaire was created and a link to it was emailed to all of them who were requested to forward it to their immediate subordinates. However, the email containing the link to questionnaire was successfully delivered to only 197 project managers of different project-based organizations. After several reminders and continuous follow-up, at the end we found 112 responses out of which 108 (= N) responses were properly filled and thus were

selected for data analysis. Out of them 43 were from public sector PBOs and 65 were from private sector PBOs. For grey data analysis, since the data was primary therefore first of all the Geometric Mean of responses obtained against each research item was calculated. Later, using these geometric means the data sequences as required for conducting Grey Incidence Analyses were developed and the tests were executed at the Grey Modeling Software (v6.0), developed by Nanjing University of Aeronautics and Astronautics, China. For statistical data analysis IBM SPSS (version 20) was used. RESULTS AND DISCUSSION The sample comprises the employees who were directly reporting to project managers overseeing projects of project-based organizations from two sectors and five industries. The detail of demographics is presented in table I.

Table I: Demographics (N=108) Descriptions PBOs‘ Industry

Sector

In-house R&D Small Construction Large Construction Aerospace/Defense MIS Engineering Public Sector Private Sector

Frequency 40 11 11 12 21 13 43 65

Percentage 37.0 10.2 10.2 11.1 19.4 12.0 39.8 60.2

Statistical Analysis Correlation and regression analyses were conducted through IBM SPSS (version 20) and the results have been shown in the tables II to V. Missing values, outlying and improperly filled questionnaires were removed from the scene before the data analysis using the software. Table II: Correlations

Pearson Correlation Sig. (2-tailed)

TTM Pearson Correlation Sig. (2-tailed)

1

.481** .000

TTM .481

**

TIS .476

POP

**

.000

.000

1

.565** .000

Public sector PBOs (N = 43)

POP

Private sector PBOs (N = 65)

POP

1

.648** .000

TTM .648

**

TIS .409**

.000

0.006

1

0.227 0.143

TIS

.476** .565**

Pearson Correlation Sig. (2-tailed)

.000

1

.000

.409**

0.227

0.006

0.143

1

**. Correlation is significant at the 0.01 level (2-tailed).

According to correlation analysis, as shown in the table II, in both private and public Projectbased Organizations, perceived organizational performance is most strongly associated to Trust in Top Management. However, in public sector PBOs this association is relatively much stronger which implies that for the employees working under the organizational project managers in public sector project-based organizations their level of trust in top management is significantly connected to their perception of overall organizational performance. Relationship between the two trusts was observed relatively stronger in private PBOs. Table III: Model Summary Model

R

R Square Adjusted R Square Std. Error of the Estimate

1: Public PBOs

.541a

0.293

0.27

0.63712

2: Private PBOs .702a

0.492

0.467

0.46573

a. Predictors: (Constant), TIS, TTM

Table IV: ANOVAa Model

Sum of Squares

df

Mean Square

F

Sig.

1: Private PBOs Regression Residual Total

10.417 2 25.167 62 35.585 64

5.209 12.832 .000b 0.406

2: Public PBOs

8.41 2 8.676 40 17.086 42

4.205 19.386 .000b 0.217

Regression Residual Total

a. Dependent Variable: POP b. Predictors: (Constant), TIS, TTM

Table V: Coefficientsa Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Std. Error 0.335

Beta

(Constant)

B 1.797

TTM TIS (Constant)

0.249 0.258 0.859

0.104 0.111 0.403

0.311 0.300

2.405 0.019 2.322 0.024 2.131 0.039

TTM TIS a. Dependent Variable: POP

0.453 0.285

0.09 0.119

0.585 0.276

5.059 0.000 2.387 0.022

1: Private PBOs 2: Public PBOs

5.360 0.000

The regression analyses, as shown in the tables III to V, show that in private PBOs Trust in Immediate Supervisor (trust in the project manager of the private PBOs) is relatively greater predictor of the perceived performance of the PBOs. However, in public PBOs Trust in Top Management is much greater predictor of the perceived performance of the PBOs. In general, the results are indicating that public sector employees are more trusting.

Grey Incidence Analyses According to Absolute Degree Grey Incidence Analysis model, as shown in the table VI, in both private and public Project-based Organizations, perceived organizational performance is most strongly associated to Trust in Top Management. However, in private sector PBOs this association is relatively stronger which implies that for the employees working under the organizational project managers in private sector project-based organizations their level of trust in top management is more significantly connected to their perception of overall organizational performance. Relationship between the two trusts was observed relatively stronger in public PBOs. Table VI. Absolute Degrees of Grey Incidence ɛ POP TTM TIS a. b.

POP 1 0.5530a 0.5454b 0.5022a 0.5124b

TTM

TIS

1 0.5015a 0.5033b

Private sector PBOs Public sector PBOs

1

According to Deng‘s Grey Incidence Analysis model, as shown in the table VII, in both private and public Project-based Organizations, Trust in Immediate Supervisor (trust in the project manager of the PBOs) is strongest predictor of the perceived performance of the PBOs. Table VII. Deng‘s Degrees of Grey Incidencea γ Private PBOs Public PBOs a.

TTM 0.5832 0.6092

TIS 0.6581 0.6968

Response/dependent variable: POP

The Deng‘s degree based grey data analysis is revealing that, on average, employees in public sector are more trusting (average = 0.6530) than the employees in private sector (average = 0.62065). The result is consistent with the already reported facts (e.g., as reported by Zeffane & Melhem, 2017). Overall, the results from both statistical and grey incidence analyses of data produced not entirely consistent results. Even though according to both approaches, perceived organizational performance is more strongly associated to Trust in Top Management than to Trust in Project Manager but according to statistical correlational analysis this association is much stronger for public PBOs (0.648 > 0.481) and according to absolute degree grey incidence analysis this association is stronger for private PBOs (0.5530 > 0.5454). According to statistical regression analysis, in private PBOs the Trust in Project Manager and in public PBOs the Trust in Top Management are greater predictors of the perceived performance of the PBOs. However, according to Deng‘s grey incidence analysis, in both private and public PBOs the Trust in Project Manager of the PBOs is greater predictor of the perceived performance of the PBOs. Now question arises the results from which method should be trusted? The solution lies in the analysis of the roots of both methods: ―Probability theory and statistics deal with the data nexus or relation of the systems encompassing large samples embodied in statistic history laws, regression models or probability relations, and subject to laws, such as the law of large samples‖ (Ng & Deng, 1995) whereas ―Grey systems theory…focuses on the study of problems involving small samples and poor information… [by]… generating, excavating, and extracting useful information from what is available‖ (Liu et al., 2016). Also, the superiority of grey methods on statistical methods is not unknown in literature (see e.g., Javed & Liu, 2018). Since grey system theory is capable of making sound decision making through small samples as well wherever the predictions through statistics are dependent on larger samples therefore one can argue that the sample size involved in this study was insufficient to make sound judgement concerning the problem under study. Therefore, the results obtained through Grey Incidence Analysis are more likely to be acceptable.

CONCLUSION AND RECOMMENDATIONS Studies show that human resource issues influence perception of firm performance (Brierley & Gwilliam, 2017; Perry-Smith & Blum, 2000; Delaney & Huselid, 1996). Also, the effect of trust on perception is not unknown in literature. Trust has repeatedly been related to variety of perceptions associated with contentment (Ellis and Shockley‐Zalabak, 2001). Building upon earlier researches, Matzler and Renzl (2006) concluded that trust in senior management increases

job contentment and that shared trust between management and subordinates increases latter‘s job contentment. Thus the managers who are seen as trustworthy are in better position to negotiate and compel their subordinates to work on new assignments or new project. The teams of such managers can perform better under non-routine tasks. It has been widely acknowledged that trust is a decisive factor resulting in the increased firm performance (Gould-Williams, 2003). Distrust by superiors result in absence of motivation to perform well in subordinates (Falk and Kosfeld, 2004) and the resulting lack of commitment may lead to even project failure (Levasseur, 2010). Further, if trust is either incomplete or entirely missing, employees often add to the cost to alleviate their predicaments (Weber et al., 2008). Studying trust in project-based organizations is necessary because interpersonal trust is one of the factors that not only affects centralization and decentralization in organizations but is also crucial to comprehend the economic necessity of decision making (Malone, 1997). According to statistical correlation analysis and absolute-degree based grey data analysis, in both private and public trust in top management was more strongly correlated to perceived organizational performance of Pakistani PBOs. Both methods reveal that, in general, public sector employees are more trusting that private sector employees. There is an agreement between the two data analyses methodologies as far as these findings are concerned. The regression analysis showed that trust in the project manager is relatively greater predictor of the perceived performance of the private sector project-based organizations (PBOs) in Pakistan whereas in public PBOs, the trust in top management is much greater predictor of the perceived performance of the PBOs. Considering the views of the people who are directly reporting to the project managers in PBOs, according to statistical analysis (and Deng‘s degree-based grey data analysis as well) for the private sector employees who trust their immediate supervisors (project managers) are more likely to have good perception of the performance of their PBO. Again, there is an agreement between the two methodologies. According to statistical analysis, the public sector employees who trust their top management are more likely to have good perception of the performance of their PBO. However, Deng‘s degree-based grey data analysis reveals that not only in private PBOs, in public PBOs as well, trust in project manager is greater predictor of perceived performance of the PBOs. Here the two methods are producing contradictory findings. Thus the results from which methodology should be used for policy implications? As highlighted in the aforementioned section and considering the association between statistics and probability theory, it can be argued that statistical analysis tries to make predictions from the data that exhibits probability distribution and require large sample size to make reliable predictions while on the other hand grey system theory makes predictions by excavating maximum information from the incomplete or small data sets and is known for making better predictions under uncertainty thus once can conclude that in the given scenario the findings from the grey data analysis can be used for policy implications and future decision making, as the sample size in the study was small. The study shows if sample size is not properly selected then statistical analyses can produce misleading results. The study suggests that reliability and validity of research instrument and soundness of framework alone can‘t guarantee the validity of the results, if sample size is not appropriately selected using the standard methods of sample selection as proposed in statistical literature. On the other hand, since Grey System Theory and its models work well on small samples as well therefore the results produced in this study through grey incidence analyses are

more likely to be acceptable. These results imply that in both private and public sectors Projectbased Organizations, trust in project managers, working on the projects of these PBOs, is more significant predictor of the perceived performance of these PBOs i.e., the immediate subordinates of the project managers who see their immediate supervisor (project manager) as trustworthy are more likely to perceive their organization (not project, strictly speaking!) as wellperforming. These results have particular significance and implications. For the decision makers (who are usually top managers) of the Project-based Organizations, the organizations for whom organizational success primarily depends on the success of their projects, it is important to nourish such an environment in their organizational projects which can foster a trustworthy relationship between their appointed project managers and their workforce working under those project managers. If their project managers‘ subordinates don‘t see him reliable they are more likely to be suspicious about their organizational performance as well. This can reduce their motivation level and citizenship behavior and can cause different problems in long run. Also, as the results and literature as well revealed that public sector employees are more trusting than private sector employees so the public and private nature of the two systems also seems influencing the variation in trust level. This nature of a system/organization is usually beyond the control of the management/controllers of the organization/system. Thus, the management of private sector can devise some other methods and incentives to boost up the overall trust level. For example, for private sector project-based organizations, easier way is to promote the good and trusting image of the project manager (rather than the top management) among the employees as it is a stronger predictor of the perceived organizational performance. The study suggests to future researchers when a sample size seems small or insufficient then grey data analysis should be preferred over statistical analysis. Here it is worth noting, the current study doesn‘t negate the importance of statistics as its successes are well-known to the data analysts and the scientific community however since grey system theory is grounded on different sets of principles and hypotheses therefore its strengths and limitations are different from that of statistics. Also, future researchers can re-test the three-variables framework presented in this study by enlarging the sample or by retesting it in different environments to confirm (or disconfirm!) the findings of the current study. Further, the possibility of another interpretation of the difference between the results obtained from the two approaches cannot be ruled out. Acknowledgement The work on this paper was started when S. A. Javed, the corresponding author, was writing his Masters in Project Management thesis, under the supervision of Dr. A. M. Syed, which was submitted to COMSATS Institute of Information Technology (CIIT), Pakistan, as a requirement for graduation. Therefore, he wants to thank CIIT. Later, after joining PhD program at Nanjing University of Aeronautics and Astronautics (NUAA), China, he revised the work. During the revision phase, Sara Javed from the GreySys International Foundation, Pakistan, significantly helped. The authors also want to thank the anonymous reviewers for their comments on the earlier version of this paper.

References: 1. Adler, P. S. (2001, March–April). Market, Hierarchy, and Trust: The Knowledge Economy and the Future of Capitalism. Organization Science, 12(2), 215–234. 2. Allen, R. S., Dawson, G., Wheatley, K., & White, C. S. (2007). Perceived diversity and organizational performance. Employee Relations, 30(1), 20-33. 3. Bahrami, S., Hasanpour, M., Rajaeepour, S., Aghahosseni, T., & Hodhodineghad, N. (2012). The relationship between organizational trust and nurse administrators‘ productivity in hospitals. Iranian Journal of Nursing and Midwifery Research, 17(6), 451-455. 4. Bakieve, E. (2013). The Influence of Interpersonal Trust and Organizational Commitment on Perceived Organizational Performance. Journal of Applied Economics and Business Research, 3(3), 166-180. 5. Basch, Cheryl A. (2012). Student-Teacher Trust Relationships and Student Performance. Education Doctoral. Paper 118. Retrieved from http://fisherpub.sjfc.edu/cgi/viewcontent.cgi?article=1119&context=education_etd 6. Brierley, J. A., & Gwilliam, D. (2017). Human Resource Management Issues in Accounting and Auditing Firms: A Research Perspective. Routledge. 7. Carmeli, A., & Schaubroeck, J. (2008). Organisational Crisis- Preparedness: The Importance of Learning from Failures. Long Range Planning, 41(2), 177-196. 8. Chen, X.D., & Xie, C.D. (2005). On productive differential equations model of natural gas. Journal of Guizhou Educational College. 4, 001. Retrieved from http://en.cnki.com.cn/Article_en/CJFDTotal-GZJY200504001.htm 9. Chow, W. S. & Chan, L. S. (2008). Social network, social trust and shared goals in organizational knowledge sharing. Information & Management, 45(7), 458–465. 10. Colquitt, J. A., Scott, B. A., & LePine, J. A. (2007). Trust, trustworthiness, and trust propensity: a meta-analytic test of their unique relationships with risk taking and job performance. Journal of applied psychology, 92(4), 909. 11. Cook, J., & Wall, T. (1980). New work attitude measures of trust, organizational commitment and personal need non‐fulfilment. Journal of occupational psychology, 53(1), 39-52. 12. Delaney, J. T. & Huselid, M. A. (1996). The Impact of Human Resource Management Practices on Perceptions of Organizational Performance, Academy of Management Journal, 39(4). 949-969. 13. Julong D. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288-294. 14. Dirks, K. T. (1999). The effects of interpersonal trust on work group performance. Journal of applied psychology, 84(3), 445. 15. Ellis, K., & Shockley‐Zalabak, P. (2001) Trust in top management and immediate supervisor: The relationship to satisfaction, perceived organizational effectiveness, and information receiving. Communication Quarterly, 49(4), 382-398. 16. Falk, A. & Kosfeld, M. (2004). Distrust - The Hidden Cost of Control. IZA Discussion Paper No. 1203; IEW Working Paper No. 193. Retrieved from http://ssrn.com/abstract=560624 17. Fulmer, I. S., & Ployhart, R. E. (2014). ―Our Most Important Asset‖ A Multidisciplinary/Multilevel Review of Human Capital Valuation for Research and Practice. Journal of Management, 40(1), 161-192.

18. Gauchat, G. (2012). Politicization of Science in the Public Sphere A Study of Public Trust in the United States, 1974 to 2010. American Sociological Review, 77(2), 167187. 19. Geraldi, J., & Söderlund, J. (2018). Project studies: What it is, where it is going. International Journal of Project Management. 36(1), 55-70. 20. Gould-Williams, J. (2003). The importance of HR practices and workplace trust in achieving superior performance: a study of public-sector organizations. International Journal of Human Resource Management, 14(1), 28-54. 21. Haerlin, B. & Parr, D. (1999, August). How to restore public trust in science. Nature, 400, p. 499. doi:10.1038/22867. Retrieved from http://www.nature.com/nature/journal/v400/n6744/full/400499a0.html 22. Hardy-Vallee, B. (2012, February). The Cost of Bad Project Management. Gallup – Business Journal. Retrieved from http://www.gallup.com/businessjournal/152429/cost-bad-project-management.aspx 23. Herman, R. D., & Renz, D. O. (2008). Advancing nonprofit organizational effectiveness research and theory: Nine theses. Nonprofit Management and Leadership, 18(4), 399-415. 24. Hobday, M. (2000). The project-based organisation: An ideal form for managing complex products and systems? Research Policy, 29(7-8), 871–893. 25. Javed, S. A., & Liu, S. (2017). Evaluation of project management knowledge areas using grey incidence model and AHP. In 2017 International Conference on Grey Systems and Intelligent Services (GSIS), (pp. 120-120). IEEE. DOI: 10.1109/GSIS.2017.8077684 26. Javed, S. A., & Liu, S. (2018). Predicting the research output/growth of selected countries: application of Even GM (1, 1) and NDGM models. Scientometrics, 115(1), 395-413. 27. Keegan, A., Ringhofer, C., & Huemann, M. (2018). Human resource management and project based organizing: Fertile ground, missed opportunities and prospects for closer connections. International Journal of Project Management. 36(1), 121–133. 28. Kerzner, H. (2009). Project management: a systems approach to planning, scheduling, and controlling (10th ed.). New Jersey: John Wiley & Sons, Inc. 29. Khan, M.S. (2012). Role of trust and relationships in geographically distributed teams: exploratory study on development sector, International Journal of Networking and Virtual Organisations, 10(1), 40–58. 30. Khan, M. S., Breitenecker, R. J., Gustafsson, V., & Schwarz, E. J. (2015). Innovative Entrepreneurial Teams: The Give and Take of Trust and Conflict. Creativity and Innovation Management, 24(4), 558-573. 31. Khan, M. S., Breitenecker, R. J. & Schwarz, E. J. (2014). Entrepreneurial Team Locus of Control: Diversity and Trust. Management Decision, 52(6), 1057–1081. 32. Levasseur, R. E. (2010). People Skills: Ensuring Project Success—A Change Management Perspective. Interfaces, 40(2), 159-162. 33. Lim, S., Morshed, A. M., & Khun, C. (2018). Trust and macroeconomic performance: A two-step approach. Economic Modelling, 68, 293-305. 34. Lin, SL., & Wu, SJ. (2011). Is grey relational analysis superior to the conventional techniques in predicting financial crisis?. Expert Systems with Applications, 38(5), 5119-5124.

35. Liu, S., & Forrest, J. (2007). The current developing status on grey system theory. The Journal of Grey System, 19(2), 111-123. 36. Liu, SF., Yang, Y., & Forrest, J. (2016). Grey Data Analysis – Methods, Models and Applications. Springer. DOI: 10.1007/978-981-10-1841-1 37. Liu, SF, Zhang, H., & Yang, Y. (2017). Explanation of terms of grey incidence analysis models. Grey Systems: Theory and Application, 7(1), 136 – 142. 38. Mayer, R. C., & Gavin, M. B. (2005). Trust in management and performance: who minds the shop while the employees watch the boss?. Academy of Management Journal, 48(5), 874-888. 39. Malone, T. W. (1997). Is Empowerment Just a Fad? Control, Decision Making, and IT. Sloan Management Review, 38(2), 23-25. 40. Matzler, K. & Renzl, B. (2006). The Relationship between Interpersonal Trust, Employee Satisfaction, and Employee Loyalty. Total Quality Management & Business Excellence, 17(10), 1261-1271. 41. Mahmoudi, A., Feylizadeh, M.R., & Darvishi, D. (2017). A note on ―A multiobjective programming approach to solve grey linear programming.‖ Grey Systems: Theory and Application, 8(1), 35-45. 42. McCauley, D. P., & Kuhnert, K. W. (1992). A theoretical review and empirical investigation of employee trust in management. Public Administration Quarterly, 16(2), 265-284. 43. Milliken, F. J., Morrison, E. W., & Hewlin, P. F. (2003). An exploratory study of employee silence: Issues that employees don't communicate upward and why. Journal of Management Studies, 40(6), 1453-1476. DOI:10.1.1.471.3802 44. Muller, R., Andersen, E. S., Kvalnes, Ø., Shao, J., Sankaran, S., Rodney Turner, J., Biesenthal, C., Walker, D., & Gudergan, S. (2013). The Interrelationship of Governance, Trust, and Ethics in Temporary Organizations. Project Management Journal, 44(4), 26–44. 45. Naber, A., Payne, S. C., & Webber, S. S. (2015, January). The Relative Influence of Trustor and Trustee Individual Differences on Peer Assessments of Trust. In Academy of Management Proceedings (Vol. 2015, No. 1, p. 14926). Academy of Management. 46. Ng, D. K., & Deng, J. (1995). Contrasting grey system theory to probability and fuzzy. ACM Sigice Bulletin, 20(3), 3-9. 47. Perry-Smith, J. E., & Blum, T. C. (2000). Work-family human resource bundles and perceived organizational performance. Academy of management Journal, 43(6), 1107-1117. 48. Prusak L, & Cohen D. (2001). How to invest in social capital. Harvard Business Review. 79(6), 86-93. 49. Rousseau, D. M., Sitkin, S. B., Burt, R. S. & Camerer, C. (1998). Not So Different After All: A Cross-discipline View of Trust. Academy of Management Review, 23(3), 393-404. 50. Salamon, S. D., & Robinson, S. L. (2008). Trust that binds: the impact of collective felt trust on organizational performance. Journal of Applied Psychology, 93(3), 593601. 51. Singh, S., Darwish, T. K., & Potočnik, K. (2016). Measuring Organizational Performance: A Case for Subjective Measures. British Journal of Management, 27(1), 214-224.

52. Sparrow, P., Brewster, C., & Chung, C. (2016). Globalizing human resource management. Routledge. 53. Swain, J. E. C. (2007). The influence of relational trust between the superintendent and union president (Doctoral dissertation). Bozeman, Montana: Montana State University. Retrieved from http://scholarworks.montana.edu/xmlui/bitstream/handle/1/2378/SwainJ1207.pdf?seq uence=1&isAllowed=y 54. Turner, J. R., & Keegan, A. (2001). Mechanisms of Governance in the Project-based Organization: Roles of the Broker and Steward. European Management Journal, 19(3), 254–267. 55. Wang, C.L., Shi, Y., & Barnes, B. R. (2015). The role of satisfaction, trust and contractual obligation on long-term orientation. Journal of Business Research. 68(3), 473-479. 56. Warren, J. S. (2012). Trust in Immediate Supervisor, Trust in Top Management, Organizational Trust Precursors: Predictors of Organizational Effectiveness (Unpublished doctoral dissertation). University of Phoenixv. ProQuest LLC (UMI Number 3583299) 57. Watson, K. L. (2005). Can There Be Just One Trust? A Cross-Disciplinary Identification Of Trust Definitions And Measurement (Unpublished doctoral dissertation). Retrieved from The Institute for Public Relations database; http://www.instituteforpr.org/wp-content/uploads/2004_Watson.pdf 58. Weber, R. A, McEvily, B. & Radzevick, J. R. (2008), Who do you distrust and how much Does It Cost? An Experiment on the measurement of trust, Paper No. 103: Department of Social and Decision Sciences. Retrieved from http://repository.cmu.edu/sds/103 59. Wei, Y., & Miraglia, S. (2017). Organizational culture and knowledge transfer in project-based organizations: Theoretical insights from a Chinese construction firm. International Journal of Project Management, 35(4), 571-585. 60. Zeffane, R. & Melhem, S.J.B. (2017). Trust, job satisfaction, perceived organizational performance and turnover intention: A public-private sector comparison in the United Arab Emirates, Employee Relations, 39(7), 1148-1167.