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Productivity in an Organizational Setting -A Systematic View of the Causalities at Work- Ingunn Ýr Guðbrandsdóttir Faculty of Industrial Engineering, Mechanical Engineering and Computer Science University of Iceland 2017 Productivity in an Organizational Setting -A Systematic View of the Causalities at Work- Ingunn Ýr Guðbrandsdóttir 30 ECTS thesis submitted in partial fulfillment of a Magister Scientiarum degree in Industrial Engineering MS Committee Guðmundur Valur Oddsson Harald Ulrik Sverdrup Master’s Examiner Ari Jónasson Faculty of Industrial Engineering, Mechanical Engineering and Computer Science School of Engineering and Natural Sciences University of Iceland Reykjavik, May 2017 Productivity in an Organizational Setting.
A Systematic View of the Causalities at Work Productivity in an Organizational Setting 30 ECTS thesis submitted in partial fulfillment of a Magister Scientiarum degree in Industrial Engineering Copyright © 2017 Ingunn Ýr Guðbrandsdóttir All rights reserved Faculty of Industrial Engineering, Mechanical Engineering and Computer Science School of Engineering and Natural Sciences University of Iceland Hjarðarhagi 2-6 107, Reykjavik Iceland Telephone: 525 4000 Bibliographic information: Ingunn Ýr Guðbrandsdóttir, 2017, Productivity in an Organizational Setting.
A Systematic View of the Causalities at Work, Master’s thesis, Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, pp.

89.

Printing: Háskólaprent, Fálkagata 2, 107 Reykjavík.

Reykjavik, Iceland, May 2017 Abstract The purpose of this research was to portray productivity in a larger context than has previously been done, using system analysis.

The result was a single causal loop diagram describing productivity in a work setting.
Information on the components affecting productivity and how they interact was gathered from the industrial and organizational psychology (I-O psychology) literature as researchers in that field have spent a great deal of effort on shedding light on the subject.

Articles from well-known I-O psychology journals were selected for further analysis through a systematic literature search.
From these articles, 45 different causal loop diagrams (CLDs) were constructed based on the causalities described in their theoretical background sections and results.

These CLDs were subsequently synthesized in two steps to create a single CLD describing productivity.
The resulting CLD provides an opportunity to view productivity in the work place in a wider context, making it easier to understand how the different components affecting productivity interact, by balancing and reinforcing their respective effects.

These results provide a foundation for further work towards a theory of productivity.

The ultimate practical purpose of studying productivity must be to be able to control it.

That requires an understanding of the causalities at work.
Útdráttur Tilgangur rannsóknarinnar var að nota kerfisgreiningu (e. system analysis) til að skoða framleiðni starfsmanna í víðara samhengi en áður hefur verið gert.

Útkoman er orsakalykkjurit (e. causal loop diagram) sem lýsir framleiðni á vinnustað.

Upplýsingar um það hvaða þættir hafa áhrif á framleiðni og hvernig þeir verka hver á annan voru sóttar í fræði vinnusálfræðinnar en fræðimenn á því sviði hafa eytt talsverðum tíma í að varpa ljósi á efnið.
Greinar úr þekktum vísindatímaritum á sviði vinnusálfræði voru valdar með kerfisbundnum hætti til frekari greiningar.

Sú vinna skilaði 45 orsakalykkjuritum sem byggjast á því orsakasamhengi sem lýst er í fræðilegum bakgrunni og niðurstöðum greinanna.

Í framhaldinu voru þessi orsakalykkjurit sameinuð í tveimur skrefum með það að markmiði að búa til eitt orsakalykkjurit sem lýsir framleiðni.
Þetta orsakalykkjurit gefur tækifæri til að skoða framleiðni á vinnustað í víðara samhengi, sem getur aukið skilning á því hvernig hinir ólíku áhrifaþættir orka hver á annan með því að draga úr eða auka á áhrif hvers annars.

Þær niðurstöður sem kynntar eru í ritgerðinni geta verið grundvöllur frekari vinnu í átt að kenningu um framleiðni á vinnustað.

Endanlegt markmið slíkra rannsókna hlýtur að vera að geta stýrt framleiðni.

Til þess að ná því markmiði þarf að skilja orsakasamhengið sem liggur að baki.
Table of Contents List of Figures .................................................................................................................... vii List of Tables ........................................................................................................................ x Acknowledgements ............................................................................................................. xi 1 Introduction ..................................................................................................................... 1 2 Method ............................................................................................................................. 3 2.1 Planning ................................................................................................................... 3 2.1.1 Scope .............................................................................................................. 3 2.1.2 Literature search ............................................................................................. 6 2.2 Execution ................................................................................................................. 7 2.2.1 Literature analysis .......................................................................................... 7 2.2.2 Synthesis ........................................................................................................ 7 3 Literature analysis .......................................................................................................... 9 3.1 De Meulenaere et al.
(2016) .................................................................................... 9 3.2 Kim and Ployhart (2014) ....................................................................................... 12 3.3 Delmas and Pekovic (2013) ................................................................................... 14 3.4 Birdi et al.
(2008) ................................................................................................... 16 3.5 Grant (2008) ........................................................................................................... 18 3.6 Probst et al.

(2007) ................................................................................................. 19 3.7 Patterson et al.

(2004) ............................................................................................ 20 3.8 Dollard et al.
(2000) ............................................................................................... 22 3.9 Podsakoff et al.

(1997) ........................................................................................... 23 3.10 Aiello and Kolb (1995) .......................................................................................... 24 3.11 Wright et al.
(1993) ............................................................................................... 26 3.12 Goodman and Leyden (1991) ................................................................................ 28 3.13 Rodgers and Hunter (1991) ................................................................................... 29 3.14 Shalley (1991) ....................................................................................................... 31 3.15 Larson and Callahan (1990) .................................................................................. 33 3.16 Graen et al.
(1986) ................................................................................................. 34 3.17 Schmidt et al.

(1986) ............................................................................................. 35 3.18 Guzzo et al.

(1985) ................................................................................................ 35 3.19 Latham and Saari (1982) ....................................................................................... 36 3.20 Schmidt et al.
(1979) ............................................................................................. 36 3.21 Kazanas (1978) ...................................................................................................... 37 3.22 Schein et al.

(1977) ................................................................................................ 38 3.23 Kim and Hamner (1976) ........................................................................................ 38 3.24 Umstot et al.
(1976) ............................................................................................... 39 3.25 Latham and Locke (1975) ..................................................................................... 41 3.26 Weinstein and Holzbach (1973) ............................................................................ 41 3.27 Rothe (1970) .......................................................................................................... 42 v 4 Synthesis ........................................................................................................................ 43 4.1 Synthesis: Step 1 .................................................................................................... 43 4.2 Synthesis: Step 2 .................................................................................................... 53 5 Discussion ...................................................................................................................... 59 References .......................................................................................................................... 65 Appendix A ........................................................................................................................ 87 Appendix B ......................................................................................................................... 91 vi List of Figures Figure 1 The three stages of the research process.
................................................................ 3 Figure 2 Wheel of science (Wallace, 1971).

......................................................................... 4 Figure 3 Wheel of science with the 5 steps of theory-building ............................................. 6 Figure 4 Causal relationships from the literature of De Meulanere et al.

(2016) ................ 11 Figure 5 Causal relationships from the results of De Meulenaere et al.
(2016) .................. 12 Figure 6 Causal relationships from the literature in Kim and Ployhart (2014) ................... 13 Figure 7 Causal relationships from the results of Kim and Ployhart (2014) ....................... 13 Figure 8 Causal relationships from the literature of Delmas and Pekovic (2013) .............. 15 Figure 9 Causal relationships from the results of Delmas and Pekovic (2013) .................. 15 Figure 10 Causal relationships from the literature of Birdi et al.
(2008) ............................ 17 Figure 11 Causal relationships from the results of Birdi et al.

(2008) ............................... 18 Figure 13 Causal relationships from the results of Grant (2008) ........................................ 19 Figure 14 Causal relationships from the literature of Probst et al.

(2007) .......................... 19 Figure 15 Causal relationships from the results of Probst et al.
(2007) .............................. 20 Figure 16 Causal relationships from the literature of Patterson et al.

(2004) ...................... 21 Figure 17 Causal relationships from the results of Paterson et al.

(2004) ........................... 22 Figure 18 Causal relationships from the results of Dollard et al.

(2000) ............................ 22 Figure 19 Causal relationships from the literature of Podsakoff et al.
(1997) .................... 23 Figure 20 Causal relationships from the resutlts of Podsakoff et al.

(1997) ....................... 24 Figure 21 Causal relationships from the literature in Aiello and Kolb (1995) .................... 25 Figure 22 Causal relationships from the results of Aiello and Kolb (1995) ....................... 26 Figure 23 Causal relationships from the literature of Wright et al.

(1993) ......................... 27 Figure 24 Causal relationships from the results of Wright et al.
(1993) ............................. 28 Figure 25 Causal relationships from the literature of Goodman and Leyden (1991) .......... 29 vii Figure 26 Causal relationships from the results of Goodman and Leyden (1991) .............. 29 Figure 27 Causal relationships from the literature of Rodgers and Hunter (1991) ............. 30 Figure 28 Causal relationships from the results of Rodgers and Hunter (1991) ................. 31 Figure 29 Causal relationships from the literature of Shalley (1991) ................................. 32 Figure 30 Causal relationships from the results of Shalley (1991) ..................................... 32 Figure 31 Causal relationships from the literature of Larson and Callahan (1990) ............ 33 Figure 32 Causal relationships from the results of Larson and Callahan (1990) ................ 34 Figure 33 Causal relationships from the literature of Graen et al.
(1986) ........................... 34 Figure 34 Causal relationships from the results of Graen et al.

(1986) ............................... 35 Figure 35 Causal relationships from the results of Schmidt et al.

(1986) ........................... 35 Figure 36 Causal relationships from the results of Guzzo et al.
(1985) .............................. 36 Figure 37 Causal relationships from the results of Latham and Saari (1982) ..................... 36 Figure 38 Causal relationships from the results of Schmidt et al.

(1979) ........................... 37 Figure 39 Causal relationships from the literature of Kazanas (1978) ................................ 37 Figure 40 Causal relationships from the results of Schein et al.
(1977) ............................. 38 Figure 41 Causal relationships from the literature of Kim and Hamner (1976) ................. 38 Figure 42 Causal relationships from the results of Kim and Hamner (1976) ..................... 39 Figure 43 Causal relationships from the literature of Umstot et al.

(1976) ......................... 40 Figure 44 Causal relationships from the results of Umstot et al.
(1976) ........................... 40 Figure 45 Causal relationships from the literature of Latham and Locke (1975) ............... 41 Figure 46 Causal relationships from the results of Latham and Locke (1975) ................... 41 Figure 47 Causal relationships from the results of Weinstein and Holzbach (1973) .......... 42 Figure 48 Causal relationships from the results of Rothe (1970) ........................................ 42 Figure 50 Wellbeing CLD from synthesis step 1 ................................................................ 49 Figure 54 The process of producing effective workers (M. Smith, 2011) .......................... 60 Figure 55 The adapted process of producing effective workers ......................................... 61 Figure 56 An extended view of employee productivity ...................................................... 63 viii Figure 57 The motivation CLD resulting from synthesis step 1 in a larger format ............ 93 Figure 58 The wellbeing CLD resulting from synthesis step 1 in a larger format .............. 95 Figure 59 The HR management CLD resulting from synthesis step 1 in a larger format ................................................................................................................ 97 Figure 60 The CLD resulting from synthesis step 2 in a larger format ............................... 99 ix List of Tables Table 1 Steps of the theory-building process (Handfield & Melnyk, 1998).
........................ 5 Table 2 The 27 articles used in the research, in descending order, based on publication date.
................................................................................................. 8 Table 3 Items discarded in synthesis step 1 ........................................................................ 44 Table 4 Items joined with other items in synthesis step 1 ................................................... 45 Table 5 List of discarded items in synthesis step 2 ............................................................. 54 Table 6 List of the items joined in synthesis step 2 ............................................................. 56 Table 7 List of items in the synthesized CLD ..................................................................... 57 Table 8 List of all items at every step of the research ......................................................... 87 x Acknowledgements First, I would like to thank my advisors, Dr. Guðmundur Valur Oddsson and Dr. Harald Ulrik Sverdrup for their support, interest and motivation during my work on this thesis.
Furthermore, I would like to thank Arndís Ósk Jónsdóttir, Jóhanna Katrín Friðriksdóttir and Vaka Valsdóttir, for reading through the thesis and making valuable suggestions for improvement.

Last but not least, I would like to thank my family and friends, and my parents in particular, for their support throughout my studies.

xi 1 Introduction Managers of organizations today face a constant demand for performance in the form of bottom line growth.
In essence, the operation of any organization can be described as a transformation process.

Inputs in the form of materials, labor, capital etc.

are fed into a system where they are transferred into outputs of higher value.

In order to grow, the organization needs to enhance this process.

In simple terms this entails increasing the ratio of output to input by either decreasing intake for a fixed output or producing more or better output with the same amount of input.
Continually striving to improve the transformation process is necessary but how this is achieved is a strategic decision.

Reducing input has been the method of choice in the last decade with managers focusing on identifying and eliminating waste in the operation of the firm.
Approaches such as Lean Manufacturing, Supply Chain Management and Business Process Re-engineering have delivered positive results, although at some point, one might expect the effect of such efficiency gains on the bottom line to diminish and even cease to be worthwhile, thus directing attention to increasing the amount and quality of output.

According to Peter F. Drucker, often named the founder of modern management, there is plenty of room for improvement in that area.
In fact, he famously stated that “the most important contribution management needs to make in the 21st century is […] to increase the productivity of knowledge work and knowledge workers” (Peter F Drucker, 1999).

The first half of the twentieth century saw extreme improvements in the productivity of the manual worker and automation further added to these gains.

Today, however, the majority of the workforce is increasingly made up of knowledge workers.
Identifying ways of improving their productivity, that is, extracting more output from the same input, is therefore extremely valuable for organizations looking to grow in a demanding, competitive environment.

Researchers in the field of industrial and organizational psychology (I-O psychology) have devoted a substantial amount of time and effort to increasing our understanding of and improving workers’ performance.
In fact, the topic of individual performance is so popular that more articles have been published on it than any other subject in the journal of Personnel Psychology and the Journal of Applied Psychology in the last 50 years (Wayne F. Cascio & Aguinis, 2008).
While the subject of employee productivity is of interest to other fields of research, such as industrial engineering, it is wise, when venturing into the study of such multi-disciplinary topics, to get familiarized with findings from other disciplines that have accumulated knowledge on the subject.

In that way, one can avoid the pitfall of re-inventing the wheel, and it also increases one’s ability to view the topic from a different angle and in a larger context.
It seems obvious that anyone exploring the topic of employee productivity, no matter the academic field, would gain from getting acquainted with what I-O psychologists have to say about the subject.

Findings in I-O psychology have identified different ways of improving employee productivity.
These include, but are not limited to, methods such as staffing and training to develop competent employees, and identifying different ways of motivating and affecting the wellbeing of these employees to turn them into effective workers.

These methods are, however, usually explored separately, thus forfeiting the opportunity to study how they 1 impact each other.

Different components can balance or reinforce each other’s effect, possibly affecting the desired outcome.
In order to understand the dynamics of the factors affecting productivity they need to be considered in context.

A systems approach therefore seems desirable.

One such method, system thinking, the framework used in this research, involves identifying the causal relationships and feedbacks of systems, thus highlighting their dynamics.
The objective of this research is to identify the causal relationships affecting employee productivity in an organizational setting with reference to findings from organizational and industrial psychology.

Instead of focusing on how one or several factors affect productivity the idea is to take a step back and look at the phenomena in a larger context.
By widening the focus, the aim of this study is to achieve a better understanding of the dynamics between the different components affecting productivity, that is, how they interact by reinforcing and balancing their respective impacts.

It is only when we thoroughly understand the dynamics of a system that we can properly control it to produce the desired result.

2 2 Method The work for this thesis was performed in three stages.
Figure 1 is a visual representation of the process, from the initial design of the research to the reflections on the results.

Each step in the process produces an outcome that is used in the steps that follow.

During the planning stage, the outline and scope of the research was defined and put forth in the form of a research objective.

The planning phase also entailed the gathering of source material through a systematic literature search.
The execution stage involved reviewing the literature, extracting relevant information and organizing it in a systematic way.

The review of the literature entails analysis and is thereby a part of the actual research conducted and results yielded.

In the second part of the execution stage the information gathered during the first stage was synthesized in two steps to form a single diagram describing the causal relationships affecting productivity.
The third and final stage, described in the discussion chapter, involved reflecting on the research results produced during stage two and speculating on opportunities for future research.

The three research stages are briefly described below.

Figure 1 The three stages of the research process.

2.1 Planning The actual research work of the execution stage was preceded by a planning phase.

During this stage, the scope of work was defined and the research material assembled.
2.1.1 Scope The purpose of this study is to identify the causal relationships of productivity in an organizational setting as presented in findings from I-O psychology.

Limiting the research material to this particular field is based on the assumption that it contains an abundance of knowledge on the subject that is of value when mapping up causal relationships using methods from industrial engineering.

3 The performance of an organization can be measured in different ways.
The terms efficiency, effectiveness and productivity are frequently used to describe performance in the organizational setting.

Despite their widespread use, a lack of consensus on the definition of these terms, or rather, how to distinguish between them, is apparent in the literature.

In this research, distinctions between definitions of productivity in the different articles are disregarded and it is presumed that all phenomena termed productivity are the same.
On the other hand, a distinction is made between the different levels of productivity, that is employee, group and company level productivity.

The current research work is, in essence, a form of inductive theory construction.

Scientific research has been described as either inductive or deductive, although both types are essential for the scientific process.

Handfield and Melnyk (1998) describe the theory- building process in five steps.

A part of a table from their article is presented in Table 1.
This process structure is based on the works of Wallace (1971) who put forth the so-called wheel of science that can be seen in Figure 2.

The wheel of science is a visual representation of the iterative process of scientific research.

The left side of the wheel shows the inductive part of the process while the deductive part is presented on the right side.
Inductive theory construction entails using particular cases to produce general theories while deductive hypothesis testing starts with general principles and theory and progresses to specific cases.

Figure 2 Wheel of science (Wallace, 1971).

Although Handfield and Melnyk (1998) present theory-building as numbered steps, the scientific process is essentially iterative, and, like the circular symbol representing it, infinite, that is, with no clear beginning or end.
Individual research efforts can start at any point in the theory-building process.

Figure 3 shows the five steps of theory-building as an iterative process.

Again, the inductive part of the process is on the left side of the diagram and the deductive part on the right.

This research is based on earlier work in I-O psychology.

With the observation phases of discovery and description already performed by others, the current work involves the mapping stage of generating empirical generalizations.
The following stages of relationship building, that is turning the empirical generalizations into theory, theory validation and theory extension are outside the scope of this research.

4 Table 1 Steps of the theory-building process (Handfield & Melnyk, 1998).

Purpose 1a.

Discovery - Uncover areas for research and theory development Research Question - What is going on here?

- Is there something interesting enough to justify research?

1b.

Description - Explore territory - What is there?


- What are the key issues?

- What is happening?

2.

Mapping Identify/describe key variables - - Draw maps of the territory - What are the key variables?

- What are the salient / critical themes, patterns, categories?

3.

Relationship building - What are the patterns or linkages - - Improve maps by identifying the linkages between variables Identify these relationships ‘why’ underlying the 4.
Theory validation - Test the theories developed in the previous stages - Predict future outcomes 5.

Theory Extension / Refinement - To expand the map of the theory - To structure better the theories in light of the observed results between variables?

- Can an order in the relationships be identified?

- Why should these relationships exist?

- Are the theories we have generated able to survive the test of empirical data?
- Did we get the behavior that was predicted by the theory or did we observe unanticipated behavior?

another - How widely applicable /generalizable that we have theories the are developed?

- Where do these theories apply?

- Where don’t these theories apply?

5 Figure 3 Wheel of science with the 5 steps of theory-building 2.1.2 Literature search A systematic literature search was conducted in accordance with the scope and research objective.
The ISI Web of Science database was used to search for articles.

The field of I-O psychology has contributed immensely to research on employee productivity so a relatively strict search criteria were used.
The search field was narrowed only to include articles with the word productivity in the title from five well known journals publishing research in the field of I-O psychology: Personnel Psychology, Journal of Applied Psychology, Journal of Occupational and Organizational Psychology, Journal of Organizational Behavior and Journal of Vocational Behavior.

The search returned 61 articles, of which 27, listed in Table 2, were deemed relevant for the research.
The criteria for relevance were: • The article should describe causal relationships leading to productivity either in its theoretical background chapter or results; • The article should focus on general organizational settings and employees as opposed to specific groups such as parents or shift workers; • The article should be available in full text.
The 27 relevant articles were further examined in the execution stage through a literature analysis producing information which was then synthesized in two steps.

6 2.2 Execution The execution consists of a thorough literature analysis using the method of system thinking, followed by a two-step synthesis of the analysis results.
2.2.1 Literature analysis The selected literature was reviewed using a systems approach, with the specific aim of identifying descriptions of causal relationships affecting productivity.

These causalities were found in the theoretical background sections of the articles, in their results or both.

The results of the literature analysis were presented as causal-loop-diagrams (CLDs).
Most of the articles produced two diagrams, one from the theoretical background and one from the results, but a few only contained information on causal relationships in one of two sections.

The result of this stage of the research was 45 distinct CLDs.

It should be noted that all information used to construct the 45 CLDs comes from the selected 27 articles.
The CLDs made from the theoretical background chapter of these 27 articles contain causal relationships described in over 200 articles from journals and books from various fields of research.

These sources were not read for this research and the presumptions made about causalities are based on how the authors of the selected articles described them.

However, reference is made to the source articles.

System analysis The method used to identify causal relationships in the literature was system analysis.
System analysis is a practical application of system thinking.

The objective of system thinking is to obtain an understanding of the connections and interactions of the distinct parts of a system, recognize patterns and thus identify causes and effects of complex problems within the system.

System analysis involves identifying the components of a system, building a mental model of how they relate to one another and presenting it as a causal loop diagram.
Once a mental model has been constructed, the dynamics of the system can be recreated using mathematical simulation models.

Such models can then be used to explain past behavior of the system and predict and influence future outcomes (Haraldsson, 2000).
2.2.2 Synthesis The CLDs from the different articles were used as building blocks for the construction of a single mental model containing all the different factors that contribute to or discourage employee productivity according to the selected literature.

Similar items, and their respective causal relationships, were joined and items that were considered less important for the big picture were discarded.
As stated in the introduction, the purpose of this research was to get a macro rather than micro view of employee productivity.

One way of consolidating the information extracted from the literature would be simply to join the different CLDs together, only uniting identical items, and thereby preserving the original level of detail.

This produces a highly complex model that is difficult to understand and therefore does not add much to the information in the isolated CLDs.
The route taken here was therefore to simplify the big picture just enough so that the human mind can grasp its dynamics without losing sight of the essential elements.

The synthesis was performed in two steps; the first step produced three CLDs with 84 individual items and the second step resulted in a single CLD with 36 items.

7 Table 2 The 27 articles used in the research, in descending order, based on publication date.
Year Title 2016 Unraveling the impact of workforce age diversity on labor productivity: The moderating role of firm size.

2014 The effects of staffing and training on firm productivity and profit growth before, during, and after the great recession.

2012 Environmental standards and labor productivity: Understanding the mechanisms that sustain sustainability.

2008 The impact of human resource and operational management practices on company productivity: A longitudinal study.
2008 Does intrinsic motivation fuel the prosocial fire?

Motivational synergy in predicting persistence, performance, and productivity.

2007 Productivity, counter productivity and creativity: The ups and downs of job insecurity.

2004 Organizational climate and company productivity: The role of employee affect and employee level.

2000 Psychosocial job strain and productivity in human service workers: A test of the demand-control-support model.
1997 Moderating effects of goal acceptance on the relationship between group cohesiveness and productivity.

1995 Electronic performance monitoring and social-context – Impact on productivity and stress 1993 Productivity and extra-role behavior – The effects of goals and incentives on spontaneous helping.

1991 Familiarity and group productivity.

1991 1991 Effects of productivity goals, creativity goals, and personal discretion on individual creativity.
1990 Performance monitoring – How it affects work productivity.

1986 A field experimental test of the moderating effects of growth need strength on productivity.

1986 The economic-impact of job selection methods on size, productivity, and payroll costs of the federal work force – an empirically based demonstration.

1985 The effects of psychologically based intervention programs on worker productivity – a meta-analysis.
1982 The importance of union acceptance for productivity improvement through goal setting.

1979 1978 Relationship of job satisfaction and productivity to work values of vocational education graduates.

1977 1976 Effect of performance feedback and goal setting on productivity and satisfaction in an organizational setting.

1976 Effects of job enrichment and task goals on satisfaction and productivity – implications for job design.
1975 1973 1970 Output rates among welders – productivity and consistency following removal of a financial incentive system.

Increasing productivity with decreasing time limits.

A field replication of Parkinson’s law.

Impact of individual differences, reward distribution, and task structure on productivity in a simulated work environment.

Impact of Management by Objectives on organizational productivity.

Impact of valid selection procedures on work-force productivity.
Impact of flexible working hours on productivity.

Author De Meulenaere et al.

Kim and Ployhart Delmas and Pekovic Birdi et al.

Grant Probst et al.

Patterson et al.

Dollard et al.

Podsakoff et al.

Aiello and Kolb Wright et al.

Goodman and Leyden Rodgers and Hunter Shalley Larson and Callahan Graen et al.

Schmidt et al.

Guzzo et al.

Latham and Saari Schmidt et al.

Kazanas Schein et al.

Kim and Hamner Umstot et al.


Latham and Locke Weinstein and Hozbach Rothe 8 3 Literature analysis The 27 articles deemed relevant for the research presented in this thesis were analyzed using system analysis.

Each article was examined in search of descriptions of causal relationships relating to productivity.

The search was focused, on one hand, on the theoretical background or literature review of each article, and, on the other hand, on its results.
Identified causal relationships are presented below in the form of causal loop diagrams, each accompanied by a brief description.

For every article, there are, therefore, typically two sets of analysis results: first, a set of one diagram, and an associated description from the theoretical background, and, second, a similar set from the results.

There are exceptions, however, as some articles did not demonstrate identifiable causal relationships, either in the background section or in the results.
All causal relationships identified in the theoretical background chapter of an article are marked with a reference.

References for the causal relationships identified in the results chapters of the articles are not marked in the results CLDs as their source is always the article in question.

Similar or even identical items in separate articles go by different names.

Such items were joined under one item name, representing the whole group.
A list of the 115 distinctive items found on the initial 45 CLDs and their denotations in every article in which they were identified, was recorded in a working document.

In addition to the 115 items already mentioned there are eight items that were defined as “effect items”.

They are used to be able to present the mediating role of certain factors on the impact of other components.
For example, the items goal commitment, goal difficulty and goal specificity all increase the effect of goal setting, but do not increase goal setting per se.

An “effect item”, the effect of goal setting, therefore needs to be added as a link between goal setting and the components it affects.
It is presumed that the “effect items” are closely related to, or even integral parts of the items whose effect they are to present (e.g., goal setting is a necessary prerequisite for the existence of the effect of goal setting).

They are therefore not considered as proper items and are not included in the total sum of 115 items although they are present in the CLDs.

A list of all items referred to in this research, including the “effect items” can be found in Table 8 in Appendix A.
Below, brief descriptions of the causal relationships identified in each of the 27 articles are presented, along with their respective CLDs.

The articles are introduced in order of publication year with the latest publications first.

3.1 De Meulenaere et al.

(2016) Causal relationships from the literature (Figure 4) De Meulenaere, Boone, and Buyl (2016) based their research design on earlier findings on the effect of age diversity on labor productivity.
They reference results indicating that age variety, that is, the heterogeneity of ages within the firm, causes the manifestation of age specific knowledge differences (Horn & Cattell, 1967), and that age polarization, or the segmentation of the workforce into homogeneous groups, leads to age related value differences (Cherrington, Condie, & England, 1979; Parry & Urwin, 2011; Wagner, 2007).
9 Further, they state that age specific knowledge differences have been found to have a positive effect on knowledge transfer within the firm (Carton & Cummings, 2012; Hambrick & Mason, 1984; D. A. Harrison & Klein, 2007; Horwitz & Horwitz, 2007; Katherine J. Klein & Harrison, 2007; Pelled, 1996; Williams & O'Reilly, 1998), while age related value differences have a negative effect on knowledge transfer.
They argue that the latter increases group formation amongst employees (Carton & Cummings, 2012; Tajfel & Turner, 1979) which leads to less cohesion, cooperation and communication (Bell, Villado, Lukasik, Belau, & Briggs, 2011; Pelled, 1996), thus negatively affecting knowledge transfer (Grund & Westergaard-Nielsen, 2008; Katherine J. Klein, Knight, Ziegert, Lim, & Saltz, 2011; Kunze, Boehm, & Bruch, 2011; Pelled, 1996).
Furthermore, they found that the transfer of knowledge between employees within the firm had been found to positively affect the quality of decisions made, creativity and individual employee efficiency and effectiveness, ultimately affecting firm productivity (Carton & Cummings, 2012; Hambrick & Mason, 1984; D. A. Harrison & Klein, 2007; Horwitz & Horwitz, 2007; Katherine J. Klein & Harrison, 2007; Pelled, 1996; Williams & O'Reilly, 1998).
De Meulenaere, Boone and Buyl’s research findings also indicate that firm size affects both the effect of age related value differences and of age specific knowledge differences.

In bigger firms, distinct age groups should be larger, which intensifies the effect of its members’ value differences (Boehm et al., 2014).
When it comes to knowledge differences, however, a larger firm size enables the matching of employees with appropriate jobs, thus making it easier to take advantage of age specific knowledge differences (Pfeffer & Cohen, 1984).

Job security has, according to De Meulenaere et al.

(2016) been found positively to impact extra role behavior (Galunic & Anderson, 2000; Leana & Van Buren, 1999; Sun, Aryee, & Law, 2007).
Such employee behaviors make the flow of knowledge between employees more prominent, thereby intensifing the positive effect of age variety and diminishing the negative effect of age polarization on labor productivity (J.

B. Arthur, 1994; Rosemary Batt & Colvin, 2011; Delery & Doty, 1996; Oreilly & Chatman, 1986; Tsui, Pearce, Porter, & Tripoli, 1997; Zacharatos, Barling, & Iverson, 2005).

10 Figure 4 Causal relationships from the literature of De Meulanere et al.
(2016) Causal relationships from the results (Figure 5) De Meulenaere et al.

(2016) researched the impact of age variety and age polarization on labor productivity and concluded that age variety increases productivity, while age polarization decreases it.

They also investigated the moderating effects of firm size and job security.

Firm size intensified the impact of both age variety and age polarization but job security only affected the impact of age variety.
11 Figure 5 Causal relationships from the results of De Meulenaere et al.

(2016) 3.2 Kim and Ployhart (2014) Causal relationships from the literature (Figure 6) The purpose of Y. Kim and Ployhart (2014)’s research was to investigate how selective staffing methods and internal training affect firm performance, with firm performance defined as both internal performance or productivity and financial performance or profit.
They expected productivity to be highly affected by the human capital resources that staffing and training generate, which in turn would lead to more profit through increased revenues and decreased employee turnover (W.F.

Cascio & Boudreau, 2008; Lepak, Liao, Chung, & Harden, 2006; Robert E Ployhart & Schneider, 2002; N. P. Podsakoff, Whiting, Podsakoff, & Blume, 2009).
Regarding the effect of staffing, they reference research results indicating that selective staffing has a positive effect on the accumulation of a firm’s generic human capital resources in the form of skilled employees (Guion, 2011; Schmitt & Chan, 1998).

A skilled workforce has been found to perform tasks more effectively (Robert E. Ployhart, Weekley, & Ramsey, 2009; Van Iddekinge et al., 2009) and efficiently (Evans & Davis, 2005), thus increasing productivity.
Training, on the other hand, mainly adds to a firm’s specific human capital resources (Aguinis & Kraiger, 2009; Noe, 2008; Tharenou, Saks, & Moore, 2007).

These resources have an even stronger positive effect on employee productivity and subsequent financial performance (Aguinis & Kraiger, 2009; W. Arthur, Bennett, Edens, & Bell, 2003; Katherine J Klein & Kozlowski, 2000; Tharenou et al., 2007).
Some research findings have connected this increase in productivity to employees’ shared and mental models (DeChurch & Mesmer-Magnus, 2010; Evans & Davis, 2005), their transactive memories (Ren & Argote, 2011) or the establishment of organizational routines and subsequent knowledge sharing (Argote, 1999; Feldman & Pentland, 2003; March, 1991).

Higher quality general human capital resources have also been found to have a positive effect on knowledge sharing (Felin, Zenger, & Tomsik, 2009).
12 Figure 6 Causal relationships from the literature in Kim and Ployhart (2014) Causal relationships from the results (Figure 7) From their own research Y. Kim and Ployhart (2014) concluded that both internal training and selective staffing have a direct effect on company profit, hence performance, and an indirect effect through labor productivity.
Figure 7 Causal relationships from the results of Kim and Ployhart (2014) 13 3.3 Delmas and Pekovic (2013) Causal relationships from the literature (Figure 8) Magali A Delmas and Pekovic (2013) set out to research the relationship between environmental standards, here defined as firm greenness, and company performance, mainly as mediated through training and teamwork.
They reference environmental standard literature stating that the adoption of such standards entails increased focus on employee training (Blunch & Castro, 2007; M. Delmas, 2001; Khanna & Anton, 2002; Ramus & Steger, 2000; Sammalisto & Brorson, 2008) and teamwork (Arimura, Darnall, & Katayama, 2011).
They further reference literature on training, stating that training employees has a positive effect on employee productivity (Conti, 2005; Dearden, Reed, & Van Reenen, 2006; Koch & McGrath, 1996; Zwick, 2004) through an effect on firm specific human capital resources (Jennings & Moore, 1995; Koch & McGrath, 1996; M. E. Porter, 1985).
Teamwork, on the other hand, they connect with increased employee productivity and thereby organizational productivity, through job satisfaction and motivation (R. D. Banker, Field, Schroeder, & Sinha, 1996; R. Batt, 2004; Huselid, 1995).

They also reference articles stating that teamwork increases knowledge transfer within the firm, paving the way for more innovation activity, which in turn leads to organizational productivity (Hamilton, Nickerson, & Owan, 2003; Mohrman & Novelli, 1985).
Magali A Delmas and Pekovic (2013) also mention the effect that adopting environmental standards can have on employees’ perception of the company’s corporate social responsibility or “greenness” (M. Delmas & Montiel, 2009; M. A. Delmas, 2002).
Furthermore, they state that such a perception has been found to have a positive effect on organizational productivity (Hess, Rogovsky, & Dunfee, 2002; Koh & Boo, 2001; Viswesvaran, Deshpande, & Joseph, 1998) through for example an increase in employee citizenship behavior (Dutton, Dukerich, & Harquail, 1994; Frank, 2003; Jones & Volpe, 2011) and commitment to the company (Brammer, Millington, & Rayton, 2007; M. Patterson, Warr, & West, 2004).
14 Figure 8 Causal relationships from the literature of Delmas and Pekovic (2013) Causal relationships from the results (Figure 9) In their own results, Magali A Delmas and Pekovic (2013) argued that firms which have adopted an environmental standard are indeed more productive than those that have not.

They also confirmed the notion that adopting such standards leads to increased employee training and interpersonal contact, which in turn affects productivity.
The effect that “firm greenness” has on productivity, therefore, seems to be at least partly mediated by training and teamwork.

Figure 9 Causal relationships from the results of Delmas and Pekovic (2013) 15 3.4 Birdi et al.

(2008) Causal relationships from the literature (Figure 10) Birdi et al.

(2008) studied the impact of human resource and operational management practices on performance.

They hypothesized, based on earlier that empowerment, training and teamwork would positively affect productivity.
findings, With regards to empowerment, they built their assumptions on research indicating that autonomy affects company performance by motivating employees (Hackman & Oldham, 1976), encouraging them to use initiative (Frese, Kring, Soose, & Zempel, 1996), or be more proactive (Parker, Williams, & Turner, 2006).
The granting of autonomy also encourages employees to develop and use new knowledge and skills (Leach, Wall, & Jackson, 2003) and minimizes need for supervision, thus lowering payroll costs (R. Batt, 2001; Parker & Wall, 1998).

From the literature, Birdi et al.


(2008) found evidence of the important impact that training has on employees’ knowledge and skills, particularly firm specific knowledge (Pfeffer, 1998) and that such knowledge has a positive effect on employee productivity (Harvey & Denton, 1999; Power & Waddell, 2004; Senge, 1990).
Finally, according to their study of the literature, teamwork affected performance by motivating team members, reducing the need for supervision and thereby lowering payroll costs, and by providing growth opportunities for employees by means of knowledge sharing (Allen & Hecht, 2004; Leach et al., 2003; Leach, Wall, Rogelberg, & Jackson, 2005; Orsburn & Moran, 2000).

Based on earlier findings, Birdi et al.

(2008) also expected the three human resource management practices to affect each other.
Autonomy, they suspected, was important for training (M. G. Patterson, West, & Wall, 2004) and teamwork (Cherns, 1987) to be effective, and that without the knowledge and skills provided by training employees, empowering them would be of little use (Bailey, 1983).

16 Figure 10 Causal relationships from the literature of Birdi et al.

(2008) Causal relationships from the results (Figure 11) In their own research, Birdi et al.
(2008) found evidence for the substantial impact of training and empowerment on company productivity.

Their research did, however, not support their hypothesis about the direct effect of teamwork on productivity.

Teamwork was, however, found to have an indirect effect by increasing the effect of the other two human resource management practices.

17 Figure 11 Causal relationships from the results of Birdi et al.
(2008) 3.5 Grant (2008) Causal relationships from the literature (Figure 12) A. M. Grant (2008) speculated on the part intrinsic motivation plays in the impact prosocial motivation has on persistence, performance and productivity.
He makes reference to several studies which indicate that prosocial motivation affects persistence, performance and productivity positively (Bing & Burroughs, 2001; Brewer & Selden, 1998; Adam M. Grant, 2007; Korsgaard, Meglino, & Lester, 1997; Naff & Crum, 1999; Rioux & Penner, 2001), although he states that other studies have had less promising results.
Figure 12 Causal relationships from the literature of Grant (2008) Causal relationships from the results (Figure 13) In an effort to address the contradicting research results on the impact prosocial motivation has on persistence, performance and productivity, A. M. Grant (2008) studied the same effect with or without intrinsic motivation, and he came to the conclusion that intrinsic motivation strengthened the association between prosocial motivation and persistence, performance and productivity.
18 Figure 13 Causal relationships from the results of Grant (2008) 3.6 Probst et al.

(2007) Causal relationships from the literature (Figure 14) In their research Probst, Stewart, Gruys, and Tierney (2007) focused on job insecurity and its effect on productivity and creativity.
They base their enquiry on earlier findings that show that threats of downsizing or actual downsizing increases job insecurity amongst employees (Ashford, Lee, & Bobko, 1989; Probst, 2003; Roskies & Louisguerin, 1990), causing on-the-job stress (Brockner et al., 1994; Ironson, 1992; Jacobson, 1987).
They further make reference to research that links stress to loss of creativity (Baron, 1986; Farr & Ford, 1990; Higgins, Qualls, & Couger, 1992; Sanders & Baron, 1975; Van Dyne, Jehn, & Cummings, 2002), which affects entrepreneurial activities within the company and thereby long term economic growth (T. M. Amabile, 1997; Simonton, 1999; Wise, 1992).
This negative effect of the loss of creativity is to some degree compensated for by an increase in employee focus on specific jobs, that is jobs that are either routine or rewarded (Farr & Ford, 1990; Probst & Brubaker, 2001).

Figure 14 Causal relationships from the literature of Probst et al.

(2007) 19 Causal relationships from the results (Figure 15) In their own research, conducted both in a simulated organizational environment and in the field, Probst et al.
(2007) found that job insecurity certainly had a negative effect on creativity and a positive effect on productivity.

After pointing out contradictions in previous research findings on the affect of stress on counterproductive behaviors, they also concluded that job insecurity decreases counterproductive behavior.

Figure 15 Causal relationships from the results of Probst et al.

(2007) 3.7 Patterson et al.

(2004) Causal relationships from the literature (Figure 16) In their research, M. Patterson et al.
(2004) cover organizational climate and its potential effect on company productivity, focusing specifically on the economic aspects of organizational performance, that is productivity, profitability etc.

(as opposed to technological, commercial and social performance).

Organizational climate is an umbrella term used to describe influencing environmental factors in work settings.

Climate is measured through employees’ perceptions of their organization’s policies and practices.
In their article, M. Patterson et al.

(2004) discuss the affective state of overall job satisfaction, making a reference to Kopelman, Brief, and Guzzo (1990), who consider it a central variable linking organizational climate with salient behaviors and performance outcomes.

According to Kopelman et al.

(1990) these states influence three kinds of employee behaviors affecting productivity: attachment behaviors, role-prescribed behaviors, and citizenship behavior.
They describe attachment behavior as a form of commitment to the firm, that is, attending and staying with the company.

Role-prescribed behaviors are defined as performing tasks according to one’s organizational role, here put under the item of employee productivity.

The third type of salient behaviors are citizenship behaviors or extra-role behaviors that Kopelman et al.

(1990) define as non-mandatory helpful contributions made by employees.

M. Patterson et al.
M. Patterson et al.

(2004) further ground their research design on the findings of R. L. Payne, Fineman, and Wall (1976) who linked company climate with employee job 20 satisfaction and on other research results indicating the effect of job satisfaction on extra- role behaviors (Gechman & Wiener, 1975; P. M. Podsakoff, MacKenzie, Paine, & Bachrach, 2000) and employee productivity (Jamal, 1984; Judge, Thoresen, Bono, & Patton, 2001; Staw, Sutton, & Pelled, 1994).
They also state that Griffeth, Hom, and Gaertner (2000) found evidence for the effect of commitment on employee turnover.

The authors also mention research by Judge and Bono (2001) which indicated that certain personality traits such as self-esteem, self-efficacy, locus of control and emotional stability were predictors of both job satisfaction and performance.

Figure 16 Causal relationships from the literature of Patterson et al.
(2004) Causal relationships from the results (Figure 17) In their own research, M. Patterson et al.

(2004) measured a number of company climate indicators, their effect on job satisfaction and the consequent effect on company productivity.

The results were that eight climate indicators had a significant effect on subsequent company productivity.
They were: perceived supervisory support, perceived effort, perceived innovation and flexibility, perceived quality, perceived performance feedback, perceived formalization, perceived concern for employee welfare and perceived skill development.

All of these indicators – except for the last two – seem to be mediated by job satisfaction.

21 Figure 17 Causal relationships from the results of Paterson et al.

(2004) 3.8 Dollard et al.


(2000) Causal relationships from the results (Figure 18) The aim of the research presented in Dollard, Winefield, Winefield, and de Jonge (2000) was to test ideas from the demand-control-support model (Karasek, 1979) about the effect of job demands, social support and job control on job satisfaction and employee productivity.

Their results indicated that job demands increase employee productivity, as intended, but, at the same time, have a negative effect on job satisfaction.
Their results also showed that social support and employee autonomy have a positive effect on job satisfaction.

Autonomy also had significant positive effect on productivity.

They thus concluded that productive work conditions are characterized by high demands accompanied by high control and social support.

Figure 18 Causal relationships from the results of Dollard et al.

(2000) 22 3.9 Podsakoff et al.


(1997) Causal relationships from the literature (Figure 19) P. M. Podsakoff, MacKenzie, and Ahearne (1997) reviewed contradicting research results on the positive effect of group cohesiveness on performance, and they subsequently set out to determine whether group goal acceptance could serve as a moderator of such an effect.
They make reference to earlier research findings stating that cohesive groups that accept goals that are in line with the organization’s objectives perform superior to those that do not accept such goals (Greene, 1989; Gully, Devine, & Whitney, 1995; Reitz, 1987; Schermerhorn, Hunt, & Osborn, 1988; Shaw, 1981).

Figure 19 Causal relationships from the literature of Podsakoff et al.

(1997) Causal relationships from the results (Figure 20) P. M. Podsakoff et al.
(1997) conducted two studies themselves to analyze the relationship between group cohesiveness, group goal acceptance and group productivity and, additionally, whether leadership could affect such a relationship.

Their results confirmed that goal acceptance moderates the relationship between group cohesiveness and performance, and that such a relationship can be influenced by leaders who encourage and facilitate goal acceptance.

23 Figure 20 Causal relationships from the resutlts of Podsakoff et al.
(1997) 3.10 Aiello and Kolb (1995) Causal relationships from the literature (Figure 21) In their study, Aiello and Kolb (1995) examined the effect of electronic performance monitoring (EPM) on stress and productivity, and how employee skill level and social context mediates these effects.
They built their research on earlier findings which suggested that performance monitoring has a negative effect on employee overall job satisfaction (Cahill & Landsbergis, 1989; R. Grant & Higgins, 1989; Irving, Higgins, & Safayeni, 1986) and causes increased feelings of stress amongst employees (Aiello & Shao, 1992; Amick & Smith, 1992; Gallatin, 1989; Irving et al., 1986; M. J. Smith, Carayon, Sanders, Lim, & Legrande, 1992).
Higher stress levels have been contributed to more workload, with increased productivity demand and loss of autonomy (M. J. Smith et al., 1992), which, according to (Karasek, 1979), adds to on-the-job stress.

Performance monitoring was, in the literature, also connected to diminishing opportunities to socialize at work (Aiello, 1993; Amick & Celentano, 1991; Amick & Smith, 1992; Cahill & Landsbergis, 1989), leading to less social support (Amick & Smith, 1992).
Lack of social support has widely been found to be a stressor in work environments (Amick & Smith, 1992; Cobb, 1976; Cohen & Wills, 1985; House, Landis, & Umberson, 1988; Manning & Fullerton, 1988).

Furthermore, previous findings indicate that performance monitoring leads to employees perceiving that quantity is more important than quality (Gallatin, 1989; Shell & Allgeier, 1992).
Moreover (Aiello & Kolb, 1995), based their research on research results indicating the positive impact that being a member of a cohesive work group has on employee job satisfaction (Janssens & Nuttin, 1976; Manning & Fullerton, 1988; Vanzelst, 1952) and employee stress level through increased social support (Manning & Fullerton, 1988).
Successful teamwork also has the added benefit of a more positive employee perception of their work climate (Janssens & Nuttin, 1976) and decreased turnover (Vanzelst, 1952).
24 Figure 21 Causal relationships from the literature in Aiello and Kolb (1995) Causal relationships from results (Figure 22) Aiello and Kolb (1995)’s results indicated that performance monitoring does indeed increase stress, although the size of the monitoring group seems to have an impact as, when monitored in a larger group, individuals don’t report as high a level of stress as when monitored alone.
Performance monitoring also had an effect on individual productivity, measured as performance on a data entry task.

The effect was positive for skilled participants but negative for employees with limited abilities.

The capable ones became more productive when monitored, but those lacking abilities became less productive.

The mediating effects of social context were not prominent.
While the size of the group being monitored did increase the effect performance monitoring has on stress no indication was found of group size affecting productivity.

Group cohesiveness did not increase productivity but seemed to prevent stress to some degree.

25 Figure 22 Causal relationships from the results of Aiello and Kolb (1995) 3.11 Wright et al.
(1993) Causal relationships from the literature (Figure 23) Wright, George, Farnsworth, and McMahan (1993) based their study of productivity and extra-role behavior on earlier findings on goal setting and monetary incentives.

They referenced research by E. A. Locke, Saari, Shaw, and Latham (1981) and Latham and Locke (1984) stating that goal setting has a positive effect on performance through increased employee effort, persistence, focus and strategy development.
Further, they made reference to findings of Guzzo, Jette, and Katzell (1985) and E. A. Locke, Feren, McCaleb, Shaw, and Denny (1980) on how monetary incentives result in better performance and how this effect is due to the positive effect incentives have on goal setting initiatives (Latham & Locke, 1984; Edwin A Locke, 1968; E. A. Locke et al., 1981).

Wright et al.
Wright et al.

(1993) furthermore built on theories about extra-role behavior, making reference to research indicating that goal setting, while positively affecting goal-prescribed behavior, has decrementing effects on non-goal behaviors (Bavelas & Lee, 1978; C. E. Shalley, 1991; Staw & Boettger, 1990) such as extra-role or citizenship behaviors (George & Brief, 1992; D. Katz, 1964) that had been found to be an important factor of company performance (George & Brief, 1992; D. Katz, 1964; Organ, 1988).
Regarding this trade-off between the effect of goal setting on goal-prescribed tasks and on non-goal tasks, Wright et al.

(1993), mention earlier findings stating that the effect of goal setting, both positive and negative, is intensified by goal difficulty (Mento, Steel, & Karren, 1987; Tubbs, 1986) which in turn is affected by employees’ commitment to set goals (Hollenbeck & Klein, 1987; Edwin A Locke, 1968).
Goal difficulty and commitment thereby affect both goal-related, role-prescribed behavior, and extra-role behavior.

26 Figure 23 Causal relationships from the literature of Wright et al.

(1993) Causal relationships from the results (Figure 24) In their own research, Wright et al.

(1993) hypothesized that goal commitment would increase the affect that goal difficulty has on task performance and extra-role behavior.
Furthermore, they hypothesized that this effect would be further moderated by a financial incentive in the form of bonus payments.

The results indicated, however, that goal commitment only moderated the effect goal difficulty has on extra-role behavior, not the effect on task performance, and that the presence of a financial initiative had no apparent effect.

Goal difficulty and goal commitment certainly had an effect on task performance, but they were found to be mutually exclusive.
27 Figure 24 Causal relationships from the results of Wright et al.

(1993) 3.12 Goodman and Leyden (1991) Causal relationships from the literature (Figure 25) In their article about familiarity and group productivity, Goodman and Leyden (1991) referenced literature on absenteeism, work experience and specific knowledge.
They said that absenteeism has been linked to decreased firm productivity (H. C. Katz, Kochan, & Gobeille, 1982; H. C. Katz, Kochan, & Weber, 1982; Moch & Fitzgibbons, 1982) and less familiarity or firm specific knowledge as more experienced workers are replaced with less experienced ones (Goodman, 1984).
Work experience and familiarity are closely related terms and according to Goodman and Leyden (1991) more experience has been associated with an increase in firm specific knowledge and familiarity (Goodman, 1984; Schmidt, Hunter, & Outerbridge, 1986) which in turn leads to better performance (Rajiv D Banker & Kemerer, 1987; R. Katz, 1982; Schmidt, Hunter, & Outerbridge, 1986).
28 Figure 25 Causal relationships from the literature of Goodman and Leyden (1991) Causal relationships from the results (Figure 26) The results of Goodman and Leyden (1991)’s own research was that a work group’s familiarity or specific knowledge positively affects productivity.
Figure 26 Causal relationships from the results of Goodman and Leyden (1991) 3.13 Rodgers and Hunter (1991) Causal relationships from the literature (Figure 27) Rodgers and Hunter (1991) analyzed the effect of the implementation of a Management by Objectives program on productivity within organizations, with special focus on the role of management.
They make reference to the MBO literature, where it is stated that MBO increases productivity through goal setting, employee participation in decision making and objective feedback on performance (Barnard, 1938; Peter F Drucker, 1954; Peter F. Drucker, 1976; Odiorne, 1976, 1986).

They presume that goal setting should increase productivity by focusing employees’ attention (Barnard, 1938; Schleh, 1959) and effort (Edwin A Locke, 1968; E. A. Locke & Latham, 1990) on the desired outcome.
Employees’ participation in decision making – on the other hand – adds to information flow up and down the hierarchy within the organization (Peter F. Drucker, 1976), so that decisions made are based on more 29 comprehensive information (Tannenbaum & Massarik, 1950), thus promoting process and work method improvements (Jamieson, 1973).
Objective feedback on performance positively affects the progress towards the objectives by clarifying uncertainties and encouraging a reflection on what could be done differently (Nadler, 1979).

Figure 27 Causal relationships from the literature of Rodgers and Hunter (1991) Causal relationships from the results (Figure 28) The results of Rodgers and Hunter (1991)’s meta-analysis was that Management by Objectives certainly has a positive effect on productivity.
This effect is further strengthened when management commitment to the initiative is strong.

30 Figure 28 Causal relationships from the results of Rodgers and Hunter (1991) 3.14 Shalley (1991) Causal relationships from the literature (Figure 29) The C. E. Shalley (1991) article is based on theories on motivation and creativity.
Regarding creativity, reference is made to findings suggesting that the conditions for a successful creative process are employees’ creative abilities (T. M. Amabile, 1983; Rokeach, 1965; C. E. Shalley, 1989; Simon, 1985), their intrinsic motivation (Teresa M Amabile, 1979; T. M. Amabile, 1983; T. M. Amabile & Gryskiewicz, 1987; Smeltz & Cross, 1984; Steiner, 1965) and that the individual performs certain cognitive activities (e.g.
problem definition, environmental scanning, data gathering) (Rokeach, 1965; Steiner, 1965).

Additionally, abundant research has indicated that personal discretion or autonomy is an important facilitator of employee creativity (T. M. Amabile, 1983; Crosby, 1968; Guetzkow, 1965).

Creativity is an important predictor of subsequent company productivity as it supports innovation activity (Galbraith, 1982; Smeltz & Cross, 1984).
C. E. Shalley (1991) further references goal setting theory, supported by many research findings, stating that setting specific, difficult goals that are accepted by employees has a substantial effect on performance (Jackson & Zedeck, 1982; E. A. Locke, 1976; E. A. Locke et al., 1981; C. E. Shalley, Oldham, & Porac, 1987).
This performance gain has, however, been found to have negative consequences as although a productivity goal focuses the employees’ efforts on reaching that goal (Edwin A. Locke & Bryan, 1969; Rothkopf & Billington, 1979), that means that they are not capable of focusing as much time and energy on other non-goal tasks (Tversky & Kahneman, 1973) like the cognitive activities needed for creative output (Rokeach, 1965; Steiner, 1965).
Productivity goal setting has also been found to have a negative effect on intrinsic motivation (Mossholder, 1980; Christina E Shalley & Oldham, 1985) thus hindering the creative process.
Research shows, however, that setting creativity goals can increase creativity and, therefore, counteract the possible negative effect of productivity on goal setting (Harrington, 1975; Manske & Davis, 1968; Speller & Schumacher, 1975) 31 Figure 29 Causal relationships from the literature of Shalley (1991) Causal relationships from the results (Figure 30) In her own results, C. E. Shalley (1991) concluded that, in line with other studies of goal setting theory, setting goals has a positive effect on productivity, and that more difficult goals have a stronger effect than easier ones.
She also found evidence of the negative effect that setting productivity goals has on creative work and that, like before, the effect is stronger as the goals get more difficult.

Setting creativity goals and providing employees with job autonomy had, on the other hand, a positive effect on creativity.
Figure 30 Causal relationships from the results of Shalley (1991) 32 3.15 Larson and Callahan (1990) Causal relationships from the literature (Figure 31) Larson and Callahan (1990) base their research on how performance monitoring affects work productivity on earlier findings on performance feedback and employee motivation.

They summarize other researchers’ conclusions that the information about employee performance provided by monitoring leads to more contingent performance consequences (Komaki, 1986).
Furthermore, presenting employees with these consequences has been known to increase performance (Honig & Stadden, 1977; Kazdin, 1980; Komaki, Desselles, & Schepman, 1988; Luthans, 1979; Scott & Podsakoff, 1985).

(Larson & Callahan)’s experiment was also inspired by research on employee attitudes (Pfeffer, 1980; Salancik & Pfeffer, 1977, 1978) and work motivation (Naylor, Pritchard, & Ilgen, 1980; L. W. Porter & Lawler, 1968; Vroom, 1964).
Referring to these, they suggest that performance monitoring can affect the employee’s perception of the importance of the monitored task and the rewards to expect for performance, and thus the effort he or she applies to their task.
Figure 31 Causal relationships from the literature of Larson and Callahan (1990) Causal relationships from the results (Figure 32) The results of Larson and Callahan (1990)’s research indicate that performance monitoring has a positive effect on task performance and that this effect is mediated by perceived task importance.

Additionally, this positive effect, is intensified by consequential contingent performance rewards.
33 Figure 32 Causal relationships from the results of Larson and Callahan (1990) 3.16 Graen et al.

(1986) Causal relationships from the literature (Figure 33) Graen, Scandura, and Graen (1986) based their research on the Hackman and Oldham (1976) job characteristics model stating that motivating job characteristics have a positive effect on internal motivation, job satisfaction and performance, and that this impact is moderated by individuals’ growth need strength.
They reference contradictive findings in job characteristics research and imply that the moderating effects of growth need strength were yet to be proven.

Figure 33 Causal relationships from the literature of Graen et al.

(1986) Causal relationships from the results (Figure 34) Graen et al.
(1986) tested the moderating effects of growth need strength on productivity and concluded that employees with high growth need strength respond more positively to growth opportunities resulting in increased productivity.

34 Figure 34 Causal relationships from the results of Graen et al.

(1986) 3.17 Schmidt et al.


(1986) Causal relationships from the results (Figure 35) In their study Schmidt, Hunter, Outerbridge, and Trattner (1986) focused their attention on selection validity and its effect on productivity and costs.

Their results indicated that new employees hired using valid selection methods produced more output than new hires chosen using more traditional selection methods.
This increased output then made possible a reduction in new hires and possibly the total work force (if total output was to be held constant), thus decreasing payroll costs.

Figure 35 Causal relationships from the results of Schmidt et al.

(1986) 3.18 Guzzo et al.

(1985) Causal relationships from the results (Figure 36) Guzzo et al.

(1985) presented results of a meta-analysis of the effects of different types of psychologically-based organizational interventions on employee productivity.
On average, such interventions had a positive effect, but the selection method of job previews and financial incentives had failed to provide significant proof.

The largest positive effect on productivity was connected to training and goal setting.

Also prominent were the effects of large scale socio-technical interventions, work redesign and appraisal and feedback.

Less 35 powerful, yet significant, effects had been confirmed for work rescheduling, supervisory methods and Management by Objectives.
Figure 36 Causal relationships from the results of Guzzo et al.

(1985) 3.19 Latham and Saari (1982) Causal relationships from the results (Figure 37) Latham and Saari (1982) built on findings from motivation theory in their study of the effects of goal setting on the productivity of unionized truck drivers.

Their results supported earlier findings on goal setting as the productivity of the truck drivers increased substantially.
In this case, an acceptance of the goal setting initiative from the union was a prerequisite for its success.

In addition to the proven productivity increase, the authors noticed a change in the truck drivers’ behavior following the implementation, reflected in an increased coordination between them.

Latham and Saari (1982) link this with the findings of E. A. Locke et al.

(1981) which stated that goal setting resulted in strategy development.
Figure 37 Causal relationships from the results of Latham and Saari (1982) 3.20 Schmidt et al.

(1979) Causal relationships from the results (Figure 38) In their article Schmidt, Hunter, McKenzie, and Muldrow (1979) presented results on their research into how selection validity affects productivity.

They concluded that valid selection methods have a positive effect on productivity and that this effect is larger when 36 the selection ratio is lower.
The selection ratio is the number of those hired divided by the number of applicants.

They presume that the number of those that will be hired is fixed so that the firm can control the selection ratio by increasing the applicant pool size.

Figure 38 Causal relationships from the results of Schmidt et al.
(1979) 3.21 Kazanas (1978) Causal relationships from the literature (Figure 39) Kazanas (1978) set out to find more conclusive evidence for findings in earlier research (Centers & Bugental, 1966; Lyman, 1955; Myers, 1964; Wernimont, 1966) on work values and their effect on job satisfaction and productivity.
Figure 39 Causal relationships from the literature of Kazanas (1978) Causal relationships from the results The results of Kazanas (1978) were conclusive with earlier findings showing that workers with intrinsically oriented work values seemed to be more satisfied with their job and more productive than those with a more extrinsic orientation.

The causal relationship is therefore the same as in Figure 39.

37 3.22 Schein et al.


(1977) Causal relationships from the results (Figure 40) Schein, Maurer, and Novak (1977) researched the impact of flexible working hours on productivity and found no proof of significant effects.

Figure 40 Causal relationships from the results of Schein et al.

(1977) 3.23 Kim and Hamner (1976) Causal relationships from the literature (Figure 41) J. S. Kim and Hamner (1976) based their research on the literature on goal setting and knowledge of results.
They referenced findings on the positive effects of goal setting on satisfaction and performance (Hamner & Harnett, 1974; Ilgen & Hamstra, 1972; Latham & Kinne, 1974; Edwin A Locke, 1968; E. A. Locke, Cartledge, & Knerr, 1970).

They further reference research on the positive effect of feedback on goal directed behavior, effort (R. B. Payne & Hauty, 1955) and performance (Braunstein, Klein, & Pachla, 1973; W. Harrison, 1970; Hundal, 1969; E. E. Smith & Kight, 1959; Weitz, Antoinetti, & Wallace, 1954).
Figure 41 Causal relationships from the literature of Kim and Hamner (1976) 38 Causal relationships from the results (Figure 42) In their own research, J. S. Kim and Hamner (1976) confirmed the positive effects of goal setting on performance and furthermore found proof that feedback increases that effect.

They also concluded that goal setting increased job satisfaction but that effect was not found to be mediated by feedback.
Figure 42 Causal relationships from the results of Kim and Hamner (1976) 3.24 Umstot et al.

(1976) Causal relationships from the literature (Figure 43) Umstot, Bell, and Mitchell (1976) studied the effects of job enrichment and goal setting on job satisfaction and productivity, based on Hackman and Oldham (1976)’s theory of job design and Edwin A Locke (1968)’s theory of goal setting.
They maintain that according to Hackman and Oldham (1976), a job enrichment initiative has a positive effect on employees’ experienced meaningfulness of work through increased task significance, more skill variety and task identity.

In addition to increased autonomy and feedback, this meaningfulness leads to increased job satisfaction that is evident in lower cost, less absenteeism and turnover, better quality and more positive attitudes amongst employees.
The effect that job enrichment has on job satisfaction is mediated by growth need strength, organizational climate and subcultural predisposition Umstot et al.

(1976) also reference Edwin A Locke (1968)’s theory on goal setting where it is stated that specific, difficult goals, that provide employees with clarity of expectations and a challenge, have a positive effect on productivity, especially if they are accepted by the employees.

39 Figure 43 Causal relationships from the literature of Umstot et al.
(1976) Causal relationships from the results (Figure 44) In their own research Umstot et al.

(1976) tested the above mentioned theories and how they interact to affect job satisfaction and productivity.

Their results confirmed that job enrichment has a positive effect on job satisfaction which is mediated by growth need strength, but did not find any proof for its impact on productivity.
They also confirmed the positive impact goal setting has on productivity but did not discover significant effect on job satisfaction.

Figure 44 Causal relationships from the results of Umstot et al.

(1976) 40 3.25 Latham and Locke (1975) Causal relationships from the literature (Figure 45) Latham and Locke (1975) set out to confirm the test results of Bryan and Locke (1967)’s laboratory study of the effect of perceived task difficulty on effort by doing a real-life work study.
They based their research design on Bryan and Locke (1967)’s statement that perceived task difficulty has an effect on the effort used to perform the task.

Figure 45 Causal relationships from the literature of Latham and Locke (1975) Causal relationships from the results (Figure 46) In their own real-life study, Latham and Locke (1975) came to the conclusion that when individuals work under time pressure – and thereby need to produce more in less time – they will be more productive.
More importantly, those under less pressure will produce less.

Figure 46 Causal relationships from the results of Latham and Locke (1975) 3.26 Weinstein and Holzbach (1973) Causal relationships from the results (Figure 47) Intragroup competition was the focus of Weinstein and Holzbach (1973)’s study.

Their conclusions state that when a financial reward system is in place within a group of people, differential rewards will lead to more productivity than equal rewards.
Similarly, more interdependence between group members yields more individual productivity than self- dependence.

41 Figure 47 Causal relationships from the results of Weinstein and Holzbach (1973) 3.27 Rothe (1970) Causal relationships from the results (Figure 48) Rothe (1970) analyzed data on the productivity of welders for 48 weeks, following the removal of a financial incentive system.

At the same time, a new initiative was started where the welders were informed of their performance each week.
Following a sharp decline in productivity after the removal of the incentive system, the performance improved again and after 48 weeks it was level with the performance shown with the incentives.

Rothe (1970) credits this turnaround to the effect of feedback or knowledge of results although he states that there is no proof for this notion.
Figure 48 Causal relationships from the results of Rothe (1970) So far, all identified causal relationships relating to productivity, from the theoretical background and the results of the 27 articles have been presented.

The resulting 45 CLDs will, in the next section, be synthesized in two steps in an effort to yield a single diagram describing the causal relationships of productivity.
42 4 Synthesis The 45 CLDs resulting from the analysis of the literature were synthesized in two steps, thus creating a single CLD for productivity.

In the first step, an attempt was made to join the 45 individual CLDs by identifying identical items in different diagrams and creating a link between them.

The outcome of the first synthesis was three separate CLDs constructed around common themes from the literature, namely employee wellbeing, employee motivation and human resource management.
The second synthesis step was a more significant attempt to decrease the complexity of the CLDs to be able to create a single one.

4.1 Synthesis: Step 1 In the first synthesis step, the 45 CLDs were combined to make three diagrams.

First, the CLDs were roughly divided into three groups by common themes in the IO-psychology literature; employee wellbeing, employee motivation and human resource management.
Next, items and causal relationships found in more than one CLD were identified and a link created between the respective diagrams.

When all such common items and causal relationships had been spotted and connected, the result was three separate CLDs.

Most of the articles consider topics relating to a single theme (e.g., job satisfaction and wellbeing or goal setting and motivation) but in some cases, when applicable, different causal relationships from an article were presented in separate CLDs.
The 45 CLDs resulting from the literature analysis contained 115 distinct items.

In synthesis 1, this number was decreased to 84 as 22 items were discarded and nine items were joined with other items.

The main goal of this synthesis step was to link the different CLDs without losing too much of the information they contain.

There were, however, items that increased the complexity of the synthesized diagrams but were not considered to add much value to the bigger picture.
In the first synthesis step, 22 items were discarded for various reasons.

These items are listed in Table 3.

Age-related items: age variety, age specific knowledge differences, age polarization, age related value differences, age group size and three other items from the De Meulenaere et al.
(2016) article; in-group-bias, firm size and employee and job match were discarded as they describe very specific causal relationships which cannot easily be synthesized with relationships and items from other articles.

Three items from different sources: level of interdependence of group members, performance monitoring group size and equality of reward systems were discarded as they focus on the interrelations within groups and how they affect group productivity.
To simplify the synthesized models, it was decided to focus on productivity on the employee and firm level.

Two items, intrinsic orientation of work values and prosocial motivation, and their causal relationships, from two articles, A. M. Grant (2008) and Kazanas (1978), were discarded as their findings concerned specific types of employee abilities or characteristics.
For 43 simplicity, this research does not go into detail of different types of employee abilities but does acknowledge – through causal relationships – that employee abilities affect productivity directly and indirectly.

Items and causal relationships from the Rodgers and Hunter (1991) article about Management by Objectives were discarded.
Management by Objectives (MBO) is a system that incorporates three different motivational initiatives, namely goal setting, objective feedback and employee participation in decision-making.

In the research presented in this thesis, these three elements are considered separately.

The item socio-technical interventions was discarded for the same reason as it is an umbrella term for several different interventions with different effects and therefore is ill suited for use in the synthesized diagram.
Firm greenness, which describes the adoption of an environmental standard and thereby incorporates different initiatives, was also discarded for the same reasons.

The research results presented in articles on the effect of work rescheduling or flextime on performance were not conclusive.

These items are therefore discarded from the synthesized diagram.

The items discarded in synthesis step 1 are listed in Table 3.
Table 3 Items discarded in synthesis step 1 Discarded items in synthesis step 1 Age group size Age polarization Age related value differences Age specific knowledge differences Age variety Employee and job match Equality of reward system Firm greenness Firm size Flextime In-group-bias Information Intrinsic orientation of work values Level of interdependence of group members Management by Objectives Management commitment Participation Performance monitoring group size Prosocial motivation Quality of work methods and processes Socio-technical interventions Work rescheduling Nine items were joined with other items in this synthesis step.
They are listed in Table 4.

Six items, cognitive activities (for creativity), organizational routines, shared knowledge and mental models, transactive memory, perceived clarity of expectations and goals and perceived job challenge, serve as intermediaries in the original CLDs.

They are affected by 44 a single item and only affect one item.

They therefore increase complexity without adding much information about the dynamics of the system.

These items were joined with their immediate successors.
The items costs and payroll cost were combined into the more general term, costs.

Group items, describing the inner workings of groups, were, as was mentioned earlier, discarded in this step, but in order to preserve the effect that groups have on the system, the item group cohesiveness was joined with teamwork and group productivity with employee productivity.

The joined items are listed in Table 4.
Table 4 Items joined with other items in synthesis step 1 Previous item name Cognitive activities (for creativity) Group cohesiveness Group productivity Payroll costs Organizational routines Shared knowledge and mental models Transactive memory Perceived clarity of expectations and goals Goal specificity Goal difficulty Perceived job challenge Joined item name Effort used on creativity Teamwork Employee productivity Costs Firm-specific knowledge Firm-specific knowledge Firm-specific knowledge Following the item reductions, the causal relationships from the literature analysis were joined into three separate CLDs; motivation (see Figure 49), wellbeing (see Figure 50) and human resource management (see Figure 51).
These figures are presented in larger format in Appendix B.

All causal relationships are marked with a reference to the relevant articles.

The bold references are to the 27 articles that were read as a part of this research.

The complexity of these three diagrams is relatively high, making it difficult to use them to generate information about the dynamics of the system.

The aim of this research is to take a step back and look at these relationships in a wider context.
To be able to do that, the complexity of the system needs to be reduced by more aggressive measures.

This is done in step two of the synthesis.

45 Figure 49 Motivation CLD from synthesis step 1 47 Figure 50 Wellbeing CLD from synthesis step 1 49 Figure 51 HR management CLD from synthesis 2 51 4.2 Synthesis: Step 2 In an effort to make it easier to synthesize the diagrams further, in step two, the number of items was decreased from the 84 items at the end of step 1 to 36 items.
The item reductions were again done either by joining similar items into one or by the discarding of items that were considered to have little relevance to the bigger picture.

The list of 84 items was scanned in search of items that could be joined for various reasons.

Some had similar meaning or could be expected to have similar effects, and others only affected or were influenced by one other item and could therefore usually be joined with that item without forsaking any important causalities.
Some causal relationships are presented both as direct and indirect effects.

In such cases, an effort was made to simplify the picture by removing the link that has less relevance to the bigger picture.

A link cannot be removed, however, if its removal affects other important causalities.

The list was also scanned for items that add little or non-relevant information to the bigger picture and could therefore be discarded.
The item reductions are summarized below, but a total of 11 items were discarded while 38 items were joined with other items.

The effects of selection ratio and applicant pool size on other items materialize in the effect of selective staffing.

Selection ratio, which is affected by applicant pool size, has in numerous research been found to influence the validity of selection methods.
Selective staffing is therefore a consequence of an appropriate selection ratio and a suitable applicant pool size and thus I have chosen selective staffing as the item representing these factors and their effect.

The items perceived relative importance of task and information about employee performance, describe how the effect of performance monitoring materializes and are not affected by nor do they affect other items.

They are therefore discarded from the final CLD.


In this second synthesis, the exclusion of items describing employee abilities was expanded to include growth need strength and the general term employee abilities.

It is presumed that the company’s current workforce is adequate and that abilities, as opposed to skills that can be learned, are outside the scope of this research.

The article by Schmidt, Hunter, Outerbridge, et al.
(1986) states that by increasing employee productivity the company can get by with fewer employees or less input, thereby decreasing costs and increasing profit.

In this thesis, the focus is on measures to increase the amount and quality of output while input is fixed.

The items employee need and employees are therefore discarded in this final step along with the related terms employee turnover, replacements and commitment.

All the items discarded in synthesis step 2 are listed in Table 5.
53 Table 5 List of discarded items in synthesis step 2 Discarded items in synthesis step 2 Applicant pool size Commitment Employee abilities Employee need Employee turnover Employees Growth need strength Information about employee performance Perceived relative importance of task Replacements Selection ratio In this step, 38 items were consolidated with other items and one new item was created.
The items creative environment, perceived corporate social responsibility and subcultural predisposition all describe the environment in which employees find themselves within the firm and how they experience it.

They therefore harmonize well with the item company climate and were, along with items describing company climate from M. Patterson et al.

(2004), put under the umbrella term company climate.
The term company performance encompasses financial performance or profit and therefore the term long-term economic growth can be added to it.

The items growth opportunities and training both entail the opportunities presented to employees to develop and use their skills.

These two items were therefore unified under one term, training.
Growth opportunities could be considered a more general and therefore appropriate term to use for consolidating these items but it seems that the absence of the traditional human resource term “training”, would be odd and could possibly raise questions.

The term training is therefore used for these two items.

With greater experience, employees acquire expertise in the form of firm specific knowledge.

Work experience and firm specific knowledge were therefore joined into the term firm specific knowledge.
Three items from the De Meulenaere et al.

(2016) article – cohesion, cooperation and communication – all describe the effects of employees working together and are therefore united under the term teamwork.

Two items, feelings of social isolation and social support have similar, but opposite, meanings and can readily be joined.

They were further combined with teamwork as their effects are of similar nature, i.e., rooted in the relationships between people at work.
The items autonomy and responsibility were joined into one, on the grounds that, arguably, with more autonomy comes more responsibility for results.

For simplicity, the item need for supervision, which increases costs and is positively affected by teamwork was put under autonomy.

The positive effect of teamwork on need for supervision is dependent on the team being autonomous and thus not needing as much guidance as otherwise.
One can 54 therefore argue that the effect of the item need for supervision on costs is based on autonomy.

It can be argued that employee initiative use is a form of employee proactivity.

These items both describe the effect that autonomy has on employee productivity.

They are joined under the term employee proactivity.

The items absenteeism and counter-productive behavior both describe negative employee conduct.
Absenteeism, that is, when employees stay away from work for no legitimate reason, can be described as counter-productive behavior.

Counter-productive behavior can further be considered as bad employee attitude, thus allowing for the item attitudes to be added to this group.

In an effort further to simplify, counter-productive behavior will be considered as negative employee productivity.

The item quality from Hackman and Oldham (1976) is supposed to increase with job satisfaction.
This term is very general and, for simplicity, it is also joined with employee productivity.

The item actual or threats of downsizing is joined with the term job insecurity on the grounds that it is insecurity about ones job that causes the effect that actual or threats of downsizing has.

If the word “goal” is considered in a more general term as the ultimate purpose of an employee’s work effort, whether it is well defined or not, the difficulty of an employee’s job can be defined as goal difficulty.
Perceived job challenge can then be joined with goal difficulty.

Additionally, the perceived clarity of expectations and goals must depend on how specific the goal is and, therefore, these items can be joined under goal specificity.

If we continue to consider the term “goal” in more general terms, the item focus on specific tasks (routine or rewarded) may be put under the term effort used to reach goal.
One can describe financial incentives as contingent consequences; the effect of these two items is considered to be rooted in the fact that the employee expects consequences of his actions and that the consequences are contingent to these actions.

These items are therefore unified under the more general term performance consequences along with perceived likelihood of performance rewards.
Skill variety, task identity and task significance are all intermediaries in the effect that job enrichment has on employees’ perceived meaningfulness of work and do not affect other items.

For simplicity, these three items are therefore put under the term perceived meaningfulness of work.

To simplify, creativity will be categorized as a non-goal task and thereby the item effort used on creativity will be put under the item effort used on non-goal tasks.
Non-goal task performance, a consequence of directing effort towards non-goal tasks, is also put under this term.

Persistence and strategy development describe different ways in which goal setting affects employee productivity.

These items are not affected by nor do they affect other items in the different CLDs and are therefore here considered as employee productivity.
Performance monitoring affects employee productivity, job satisfaction and stress through different causal relationships including work demands.

Work demands do not affect nor 55 are they affected by other items in the CLDs, so, in order to trim the final CLD, work demands are simply considered as the effect of performance monitoring.

The items joined in synthesis step 2 are listed in Table 6.
Table 6 List of the items joined in synthesis step 2 Joined item name Previous item name Job insecurity Actual or threats of downsizing Employee proactivity Employee initiative use Effort used on non-goal tasks Effort used on creativity Effort used on non-goal tasks Non-goal task performance Teamwork Cohesion Teamwork Communication Teamwork Cooperation Teamwork Feelings of social isolation Teamwork Social support Performance consequences Contingency of performance consequences Performance consequences Financial incentive Perceived likelihood of performance reward Performance consequences Employee productivity Counterproductive behavior Employee productivity Absenteeism Employee productivity Attitudes Employee productivity Persistence Employee productivity Quality Employee productivity Strategy development Company climate Creative environment Company climate Perceived concern for employee welfare Company climate Perceived corporate social responsibility Company climate Perceived effort Company climate Perceived innovation and flexibility Company climate Perceived performance feedback Company climate Perceived quality Company climate Perceived skill development Company climate Perceived supervisory support Company climate Subcultural predisposition Work experience Firm-specific knowledge Focus on specific tasks (routine or rewarded) Effort used to reach goal Growth opportunities Long-term economic growth Need for supervision Responsibility Skill variety Task identity Task significance Work demands Training Company performance Autonomy Autonomy Perceived meaningfulness of work Perceived meaningfulness of work Perceived meaningfulness of work The effect of performance monitoring A list of the final 34 items can be seen in Table 7 and the resulting CLD in Figure 52.
The complexity of this CLD is reasonable and it presents an opportunity to get a bird’s eye 56 view of the causal relationships of productivity.

A comprehensive list of all items referred to in any of the steps of this research (literature analysis, synthesis step 1 and synthesis step 2) can be found in Table 8 in Appendix A.
Table 7 List of items in the synthesized CLD Item names Autonomy Company climate Company performance Company productivity Costs Creativity Creativity goal setting Effort used on non-goal tasks Goal specificity Effort used to reach goal Employee proactivity Employee productivity Entrepreneurial activities Intrinsic motivation Job enrichment Job insecurity Job satisfaction Extra-role behavior Feedback Firm-specific knowledge Generic human capital resources Perceived meaningfulness of work Goal commitment Goal difficulty Goal setting Knowledge sharing Leadership Perceived focus on quality Performance consequences Performance monitoring Quality of decision making Revenues Selective staffing Stress Teamwork Training At this stage, information from the I-O psychology literature has been used to construct a single diagram describing the causal relationships of productivity.
A literature analysis using the method of systems analysis was used to identify relevant components according to the selected literature, how they interact and thereupon affect productivity.

The result of this literature analysis was multiple CLDs based on causal relationships as described in the articles.
Through two synthesis steps, the information from these CLDs was further the synthesis process, empirical consolidated generalizations are made that can at a later stage be turned into theories that can be tested on different data.

Although these steps in the theory building process are outside the scope of this research, it is interesting briefly to reflect on the results and speculate about opportunities for future research.

That is the matter of the discussion chapter that follows.
to create a single CLD.

During 57 Figure 52 The synthesis step 2 CLD 58 5 Discussion “Theory is the vehicle that links data to knowledge” (Handfield & Melnyk, 1998).

Although the purpose of scientific research is not to construct theory, but rather to produce knowledge, theory plays a vital role in the process as a point of reference.

It gives structure to research efforts and makes it easier to understand and communicate results (Handfield & Melnyk, 1998).
In the research presented in this thesis, referring again to the “wheel of science” (Figure 2 and Figure 3), we entered the theory-building process in the mapping phase.

Building on previous observations found in the literature, we made empirical generalizations as to the causalities of productivity in an organizational setting.

The next step in the process would be to turn these empirical generalizations into theories that can eventually be tested and validated.
The first step in that direction is to further analyze the results of the current research.

The two synthesis steps resulted in a single CLD of productivity, based on the information gathered in the literature analysis.

This final CLD is considerably less complex than the three CLDs resulting from synthesis step 1, and it is therefore more suitable for further analysis of the dynamics of the system.
The final CLD can be roughly divided into the three themes used in synthesis step 1; human resource management, motivation and wellbeing (see Figure 53).

It is not surprising that a model of productivity incorporates these themes, as they are common motives in the human resource and performance management literature.

Figure 54, which is adapted from a diagram in the textbook Fundamentals of Management, shows the process of producing effective workers.
It describes how human resource management, mainly in the form of selection and training, is used to recruit and further develop employees competent enough to meet the personnel specification, created from the job description.

To make these competent workers effective, they further need to be motivated and led in a corporate environment which fosters teamwork and a good company culture (M. Smith, 2011).
59 Figure 53 The final CLD roughly divided by themes Figure 54 The process of producing effective workers (M. Smith, 2011) 60 The CLD resulting from the synthesis corresponds well to this process description.

Selective staffing provides generic human capital, which is further developed by adding knowledge specific to the firm through training.

Employees are then motivated to reach their potential through goal setting and performance monitoring.
The wellbeing of employees is not specified in the process diagram, but it is incorporated in the culture and team working item, thus adding to worker effectiveness.

This corresponds well with the CLD, as the items from the wellbeing CLD from synthesis step 1 are spread out in the final CLD version, affecting and being affected by factors of motivation and human resource management.

The culture and team working item also responds to the teamwork and company climate items in the CLD.
The corresponding items in the CLD, however, also affect the human resource management process of making competent workers – unlike the culture and team working item in the process diagram – which seems only to affect the worker’s progress from competency to effectiveness.

Figure 55 shows an adapted version of the process of producing effective workers with reference to the results of this research.
Here, the teamwork and company climate factors envelop the whole process to signal the multifactorial effect they have.

Although the final CLD, describing productivity, corresponds well with the known process of producing effective workers, it has one clear advantage: it displays causal relationships and feedbacks.

This makes it easier to track the overall effects of initiatives such as goal setting or training, and trace the contributing factors of outcomes such as productivity.
Mapping these causal relationships also helps in identifying the trade-offs in the system, which makes it easier to prioritize and choose the best initiative in each situation.

An example of such a trade-off is the application of performance monitoring to motivate employees.
Performance monitoring has been found to yield gains in terms of increased employee productivity but at the cost of increased stress levels and less job satisfaction amongst employees, thus potentially having negative effect in the long run.

Figure 55 The adapted process of producing effective workers 61 The result of this research, in the form of a CLD describing the causal relationships of productivity, is obviously limited by its literature foundation.
The literature was selected using a systematic search only providing 27 relevant articles that nowhere near encompasses the abundance of research on the topic.

The result, however, seems to cover most of the major themes in the field, with some exceptions.

One example of a major theme missing from the literature is the limited presence of leadership and management.

Management commitment was mentioned in one article and leadership in another.
The effect of this otherwise thoroughly researched topic is absent in most of the selected literature on productivity, with these two exceptions.

Strictly speaking, leadership and management are two different things.

In general terms, management is about dealing with complexity and managing things, while leadership is about coping with change and influencing people’s behavior (M. Smith, 2011).
Ignoring this distinction, it seems apparent that both management and leadership play an important role in the productivity of employees.

Management is, in fact, the leading agent when it comes to setting standards for performance, measuring against these standards and reacting to the results.
The different methodologies present in the model, such as training, goal setting and job enrichment all have their documented effect, but something must set their use in motion and someone must make the decision to do so.

These decision chains are rarely mentioned in the literature.

That probably means that they are not considered relevant when these measures are examined in isolation, but they certainly matter if you want to look at the bigger picture.
Another factor scarcely represented in the model is economic realities.

Although delivering profit is not the only purpose of an organization, being profitable is absolutely vital for its survival.

Indeed, the purpose of raising productivity, by applying measures such as goal setting and training, must be to increase profit by positively affecting the top line results, and, according to the literature, these measures certainly have this effect.
What is less apparent from the literature, however, is the fact that their application also costs money and thereby negatively affects profit.

When viewing the causalities of productivity as a whole, and, especially when intending to use that information to make decisions, it is therefore important to take the financials into consideration.
Usually, there is a limit to the amount of funds that can be allocated to human resource and performance management initiatives, so prioritizing and tailoring to circumstances becomes important.

It is therefore necessary to take into account the cost of raising productivity, not least to ensure the efficiency and effectiveness of such efforts.

Following this reflection on the results, an extended view of employee productivity is presented in Figure 56.
The model resulting from this research (see Figure 52) is displayed in this figure as a distinct system, an employee productivity system.

Inputs in the form of initiatives such as training and goal setting are fed into this system and the output is level of productivity.

This output is measured against a standard of performance, generally set in line with the strategic plan put forth by management.

As the gap between performance and standard increases, so, too, does the need for action.
A change in inputs, increase or decrease, is controlled by this need, but also limited by means to act, which, in turn, are limited by profit.

More inputs into the employee productivity system increase output in the form of productivity, but, at the same time, result in higher costs that decrease profit and thereby the means to act.
This alternate, or rather, expanded, view of productivity introduces the elements that were missing in the final CLD result: management, decision chains and economic realities.

Also important for consideration are factors external to firm, 62 such as the economic environment, the political landscape and rules and regulations that can have a positive or limiting effect on the company’s efforts to increase productivity.
Figure 56 An extended view of employee productivity The objective of this research was to identify the causal relationships affecting productivity and view them in a larger context than previously had been done.

Through two synthesis steps, causal relationships identified in the literature were used to build a mental model of productivity, presented as a single CLD.

In addition, potential missing links in the system of productivity were pinpointed and an effort made to position them within the system.
Future research can be built on the foundation laid by the one presented here.

The current results were produced by making empirical generalizations that could serve as a basis for a theory of productivity in an organizational setting.

From such a theory, hypotheses could be generated and tested.

System dynamics is a tool that, using simulation models, is used to validate assumptions about the workings of a system, and, in continuation, predict future outcomes.
A system dynamics model of productivity would certainly contribute profoundly to our knowledge of the topic by creating conditions for theory development and testing; thus, developing such a model will have positive implications in practice, that is, on the operation of organizations.

There is, however, a long way to go before such a model can be put into service.

An extended literature analysis with focus on the missing elements that were identified is needed to finalize the CLD of productivity.
Additionally, 63 to be able to simulate the system, it is necessary to quantify the causal relationships.

For some relationships in the model, statistical data is available, but, for others, further research is needed.

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Table 8 List of all items at every step of the research Item name in literature analysis Absenteeism Actual or threats of downsizing Age group size Age polarization Age related value differences Age specific knowledge differences Age variety Applicant pool size Attitudes Autonomy Cognitive activities (for creativity) Cohesion Commitment Communication Company climate Company performance Company productivity Contingency of performance consequences Cooperation Costs Counter-productive behavior Creative environment Creativity Creativity goal setting Item name after synthesis step 1 Absenteeism Actual or threats of downsizing - - - - - Applicant pool size Attitudes Autonomy Effort used on creativity Cohesion Commitment Communication Company climate Company performance Company productivity Contingency of performance consequences Cooperation Costs Counter-productive behavior Creative environment Creativity Creativity goal setting Item name after synthesis step 2 Employee productivity Job insecurity - - - - - - Employee productivity Autonomy Effort used on non-goal tasks Teamwork - Teamwork Company climate Company performance Company productivity Performance consequences Teamwork Costs Employee productivity Company climate Creativity Creativity goal setting 87 Item name in literature analysis Effort used on creativity Effort used on non-goal tasks Effort used to reach goal Employee abilities Employee and job match Employee initiative use Employee need Employee proactivity Employee productivity Employee turnover Employees Entrepreneurial activities Equality of reward system Extra-role behavior Feedback Feelings of social isolation Financial incentive Firm greenness Firm size Firm-specific knowledge Flextime Focus on specific tasks (routine or rewarded) Generic human capital resources Goal commitment Goal difficulty Goal setting Goal specificity Group cohesiveness Group productivity Growth need strength Growth opportunities In-group bias Information Information about employee performance Intrinsic motivation Intrinsic
 orientation of work values Job enrichment Item name after synthesis step 1 Effort used on creativity Effort used on non-goal tasks Effort used to reach goal Employee abilities - Employee initiative use Employee need Employee proactivity Employee productivity Employee turnover Employees Entrepreneurial activities - Extra-role behavior Feedback Feelings of social isolation Financial incentive - - Firm-specific knowledge - Focus on specific tasks (routine or rewarded) Generic human capital resources Goal commitment Goal difficulty Goal setting Goal specificity Teamwork Employee productivity Growth need strength Growth opportunities - - Information about employee performance Intrinsic motivation - Job enrichment Item name after synthesis step 2 Effort used on non-goal tasks Effort used on non-goal tasks Effort used to reach goal - - Employee proactivity - Employee proactivity Employee productivity - - Entrepreneurial activities - Extra-role behavior Feedback Teamwork Performance consequences - - Firm-specific knowledge - Effort used to reach goal Generic human capital resources Goal commitment Goal difficulty Goal setting Goal specificity Teamwork Employee productivity - Training - - - Intrinsic motivation - Job enrichment 88 Item name in literature analysis Job insecurity Job satisfaction Knowledge sharing Leadership Level of interdependence of group members Long-term economic growth Management by Objectives Management commitment Need for supervision Non-goal task performance Organizational routines Participation Payroll costs Perceived clarity of expectations and goals Perceived concern for employee welfare Perceived corporate social responsibility Perceived effort Perceived focus on quality Perceived innovation and flexibility Perceived job challenge Perceived likelihood of performance reward Perceived meaningfulness of work Perceived performance feedback Perceived quality Perceived relative importance of task Perceived skill development Perceived supervisory support
 Performance monitoring Performance monitoring group size Persistence Prosocial motivation Quality Quality of decision making Quality of work methods and processes Replacements Responsibility Revenues Item name after synthesis step 1 Job insecurity Job satisfaction Knowledge sharing Leadership - Long-term economic growth - - Need for supervision Non-goal task performance Firm-specific knowledge - Costs Goal specificity Perceived concern for employee welfare Perceived corporate social responsibility Perceived effort Perceived focus on quality Perceived innovation and flexibility Goal difficulty Perceived likelihood of performance reward Perceived meaningfulness of work Perceived performance feedback Perceived quality Perceived relative importance of task Perceived skill development Perceived supervisory support Performance monitoring - Persistence - Quality Quality of decision making - Replacements Responsibility Revenues Item name after synthesis step 2 Job insecurity Job satisfaction Knowledge sharing Leadership - Company performance - - Autonomy Effort used on non-goal tasks Firm-specific knowledge - Costs Goal specificity Company climate Company climate Company climate Perceived focus on quality Company climate Goal difficulty Performance consequences Company climate Company climate Company climate - Company climate Company climate Performance monitoring - Employee productivity - Employee productivity Quality of decision making - - Autonomy Revenues 89 Item name in literature analysis Selection ratio Selective staffing Shared knowledge and mental models Skill variety Social support Socio-technical interventions Strategy development Stress Subcultural predisposition Task identity Task significance Teamwork Training Transactive memory Work demands Work experience Work rescheduling The effect of age related value differences The effect of age specific knowledge differences The effect of goal difficulty The effect of goal setting The effect of growth opportunities
 The effect of job enrichment The effect of performance monitoring The effect of prosocial motivation Item name after synthesis step 1 Selection ratio Selective staffing Firm-specific knowledge Skill variety Social support - Strategy development Stress Subcultural predisposition Task identity Task significance Teamwork Training Firm-specific knowledge Work demands Work experience - - - The effect of goal difficulty The effect of goal setting - The effect of job enrichment The effect of performance monitoring - Item name after synthesis step 2 - - Firm-specific knowledge Perceived meaningfulness of work Teamwork - Employee productivity Stress Company climate Perceived meaningfulness of work Perceived meaningfulness of work Teamwork Training Firm-specific knowledge Performance monitoring (effect) Firm-specific knowledge - - - The effect of goal difficulty The effect of goal setting - The effect of job enrichment The effect of performance monitoring - 90 Appendix B The three CLDs resulting from synthesis steps one and two are presented in larger format on the next four pages.
91 Figure 57 The motivation CLD resulting from synthesis step 1 in a larger format 93 Figure 58 The wellbeing CLD resulting from synthesis step 1 in a larger format 95 Figure 59 The HR management CLD resulting from synthesis step 1 in a larger format 97 Figure 60 The CLD resulting from synthesis step 2 in a larger format 99 100