Strategy formulation and implementation in zimbabwe food manufacturing industry

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STRATEGY FORMULATION AND IMPLEMENTATION IN
ZIMBABWE FOOD MANUFACTURING SECTOR (2006 -2013)
SYNOPSIS OF THE Ph. D THESIS
Submitted by:
EMMANUEL KATSVAMUTIMA
Scholar Registration Number: 1140016
FACULTY OF COMMERCE – CENTRE FOR RESEARCH
CHRIST UNIVERSITY, BANGALORE, INDIA
FEBRUARY 2014
GUIDE : Doctor Jeevananda (India)
Co-Guide :Doctor Silas Rusvingo (Zimbabwe)

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TABLE OF CONTENTS
1 Introduction 1
2 Need for the Study 2
3 Review of Literature 3
4 Overview of the Chapters 8
5 Title of the Study 9
6 Operational Definitions 9
7 Objectives of the Study 10
8 Conceptual Equations and
Hypothesis
14
9 Design of the Study 20
10 Tools use for Collection of
Data
23
11 Field Work Details 23
12 Statistical Techniques 25
13 Validation Procedures 26
14 Data Analysis 27
15 Major Findings 37
16 Structural Model Developed 46
17 Conclusion 48
18 Implications of the Study 52
19 Limitations of the Study 53
20 Suggestions for further
Research
57
21 Bibliography 58

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LIST OF FIGURES
Figure No Title Page No
Fig 9.1 Model with Path Coefficients 12
Fig 17.1 STRUCTURAL MODEL DEVELOPED 46
Fig 17.2 Conceptual Model 47
LIST OF TABLES
Table No Title Page
No
Table 8.1 The Variables Representing Different Constructs used in this Study 12
Table
10.1
Research Design at glance 20
Table
10.2
Analytical Techniques Used 21
Table12.1 Sample Cluster of the Study 23
Table
15.1
Reliability of the Scales 27
Table
15.2
KMO and Bartletts‘s Test for Variable 27
Table
15.3
Component Matrix for Cost- Related Variables 28
Table
15.18
Item-Total Statistics 33
Table
16.1
Summary of the Results Obtained by Testing the Hypotheses 40

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1. INTRODUCTION
A key preoccupation of strategic management for competitive advantage as a field of study is
the identification of sources of heterogeneous performance among food manufacturing firms
in Zimbabwe in terms of their competitiveness. The main theories of the study of strategy
formulation and implementation in the Zimbabwe‘s food manufacturing sector includes
contingency theory, Porter's positioning theory, resource-based view and its derivatives and
environmental theories and offer varying views explaining the potential reasons for deriving
superior rent.
Empirical studies in the field of strategic management have mainly focused on two main
streams of research:
(i) the relationship between how strategy is formulated in a firm and firm performance and
(ii) the relationship between the content of strategy and firm performance. A third area of
interest is strategy implementation, but unlike the other two areas, strategy implementation in
the food manufacturing organisations has not received much empirical interest.
The results of the previous studies examining the relationship between strategy formulation
and corporate performance and marketing strategy content and performance have been
inconclusive. Some studies have reported positive relationships, while others found no
relationship. The previous studies also suffered from a number of methodological
inadequacies such as inconsistent operationalization of the constructs, unclear definition of
industry sectors and small sample size. Only a few studies have focused on Zimbabwean
based organizations. In addition there is a dearth of empirical research using Zimbabwean
based food manufacturing organizations.
Based on the literature review a conceptual model of strategy formulation and
implementation in food manufacturing organizations in Zimbabwe was proposed and the
hypotheses to be tested were derived. These hypotheses were classified into two groups
namely (i) hypotheses for validating the findings of previous studies and (ii) hypotheses
which have not been tested in previous studies. Hypotheses in the first group have examined
the impact of strategy formulation, business-level strategy and strategy implementation on
organizational competitive performance in the manufacturing sector. Hypotheses in the

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second group have examined the interrelationships between strategy formulation, business-
level strategy and strategy implementation.
2. NEED FOR THE STUDY
Key reasons for the need to study the present study are stated here:
a) Study has Practical significance.
Variable like business strategy, objective fulfilment, competitive implementation
performance, implementation strategy, cost-related, differentiation variables, focus variables
and environment variables are increasingly recognised as important form of food
manufacturing industry in Zimbabwe as sources of competitive advantage.
b) To apply key strategic management concept to food manufacturing industry.
The issue of strategy formulation and implementation towards competitive advantage in the
food manufacturing industry in Zimbabwe has received considerable attention in the strategic
management literature. It is thought that some of these key strategy formulation and
implementation concepts could be applied to any sector of the economy for competitive
advantage.
c) Study addresses methodological shortcomings of the previous studies
This study also addresses some of the methodological shortcomings of the previous studies
by clearly defining the industry sectors, using a good sample size and by using properly
validated constructs. It gains significance mainly due to its focus on Zimbabwean based
organizations and helps theory development because a robust theory is crucially dependent on
empirical studies representing the food manufacturing industry in different geographical
regions.
d) Knowledge transfer to Zimbabwe’s food manufacturing sector
Knowledge transfer to Zimbabwe‘s food manufacturing sector from countries with best
practice such as Japan, India, China and the United States. This study helps in the promoting
of the industrialization drive and the promotion of import substitution, policy consistency, an
audit of the skills, innovation and development on technology and machinery to match
competition and value addition
e) To overview the performance of the manufacturing sector during 2006 and 2013 and
asses whether there are differences in strategy formulation and implementation in the

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food manufacturing sectors and whether the difference in constructs lead to superior
performance and competitive advantage.
f) To establish whether competitive performance heterogeneity in organisations in the
food manufacturing industries in Zimbabwe be explained in terms of their emphasis
on rational strategy formulation?
g) Does the environment have a moderating effect on the relationship between business-
level strategy implementation and competitive performance in the food manufacturing
industry in Zimbabwe?
h) Is there a relationship between the type of organisational structure and business
strategy? If strategic types are associated with structure types, then does this
association explain performance heterogeneity?
i) To evaluate government policy on provision of ground rules, to set directions and
strategy and support the activity of business and other institutions in their creative
endeavours.
The present study thus, endeavours to fill the gap in the strategy formulation and
implementation literature (and particularly in manufacturing industry literature) by reporting
insights obtained in an extensive investigation.
3. REVIEW OF LITERATURE
The concept of strategy formulation and implementation in the food manufacturing industries
in Zimbabwe is central to the competitiveness of this sector. The operationalisation of
strategy process requires multidimensional models because of the complexities associated
with the process. Rajagopalan, Rasheed & Datta (1993), Hart (1992) and Bailey, Johnson &
Daniels (2000) have made significant contributions to the literature by developing integrative
models of strategy making encompassing a multitude of factors which affect the strategy
process. Huff & Reger (1987) had identified nine different streams of strategy process
research. However, none of the strategy making models has taken into consideration the
theoretical roots of strategy process while defining the strategy making modes.
Gregory G. Dess and Nancy K. Origer (2009) conducted a study on (Environment,
Structure, and Consensus in Strategy Formulation: A Conceptual Integration) Their findings
suggested an integrative framework for research on consensus in strategy formulation—
performance relationships. Their proposed model has two components. First, a descriptive

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component explores the environment—consensus relationship in which the environment is
conceptualized along the dimensions of munificence, complexity, and dynamism. Second, a
normative component investigates the role that the match between environment, consensus,
and integrating structure plays in explaining differences in organizational performance.
Hannu Salmela, And Ton A.M. Spil et al (2010) conducted a study on ―Dynamic and
emergent information systems strategy formulation and implementation‖ The thrust of their
study was an early attempts to formulate information systems (IS) strategies concentrated on
the analytical task of deriving IS strategies from business plans. The limitations of the static
plans that often resulted from these formal studies were, however, soon discovered. The
critics suggested informal and incremental planning to ensure flexibility, creativity and
strategic thinking to comprise emergent strategies as well as planned strategies.
K.W. Platts et al., 2012 conducted a study on ―Characteristics of methodologies for
manufacturing strategy formulation‖ Findings were that although the need for companies to
develop competitive manufacturing strategies is widely accepted, the processes or
methodologies by which such strategies are developed are not well understood. The research
described identities and describes four common characteristics of methodologies used
successfully in the formulation of strategy. The results of this research can be applied by both
industrialists and academics. Industrialists thinking of reformulating their manufacturing
strategy could use the characteristics as a ‗checklist‘ to help them in determining the
methodology to be used; and academics could use the work as a framework to aid further
research into manufacturing strategy formulation.
Charles C. Snow and Donald C. Hambrick of Pennsylvania State University and
Columbia University (2008) respectively conducted a research on ―Measuring
Organizational Strategies: Some Theoretical and Methodological Problems‖ In their findings
they addressed the major theoretical and methodological problems encountered in attempts
to arrive at valid and reliable measures of organizational strategy. Their discussions were
based on a series of empirical studies of the strategic behaviors of nearly 200 organizations in
ten industries. In these studies, four different approaches for measuring strategy have been
employed and they described each approach and discussed the advantages and disadvantages.
Muhittin Oral et al., (2009) conducted a research on ―A methodology for competitiveness
analysis and strategy formulation in glass industry ‖ The study noted the increasingly
important role of global competition in shaping long-term strategies of industrial firms has
been recognized by managers, planners, politicians and academicians alike. This has
prompted recently an increase in the number of studies explicitly dealing with

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competitiveness analysis. The practice experience gained with this approach indicates that
mathematical models can provide an analytical framework for the analysis of industrial
competitiveness and can yield useful insight for competitive strategy formulation.
Rainer Feurer, Kazem Chaharbaghi, (1995) "Strategy formulation: a learning
methodology", Benchmarking for Quality Management & Technology noted that strategy
formulation can no longer be based on a process of conception, as the underlying conditions
change before a formulated strategy can be implemented. It should be based on a continuous
learning process which involves, inter alia, learning about the organization‘s goals, the effect
of different actions towards these goals and the way in which these actions should be
implemented. First, highlights the importance of an organization‘s knowledge base by
demonstrating the relationship that exists between strategy formulation and organization
learning. Then presents the role of performance measurement systems in stimulating
cognitive and behavioural learning. Places the concept of organization learning in a strategy
formulation context in order to show the effect of the nature and speed of environmental
changes on the organization‘s learning processes.
Petri Aaltonen, (Helsinki University of Technology, Helsinki, Finland), Heini Ikävalko,
(Helsinki University of Technology, Helsinki, Finland) (2012) conducted a study on
―Implementing strategies successfully‖ with the key findings of the study giving a qualitative
study of 298 interviews which was conducted in 12 service organizations. In the study, the
key findings were introduced, and the challenges of strategic communication and action, the
identification of and support for strategic actors, and structure and systems aligned with
strategy, are discussed.
Gregory G. Dess (2006) conducted a study on the ―Consensus on strategy formulation and
organizational performance: Competitors in a fragmented industry‖. This study examines the
relationship between organizational performance and consensus (or agreement) within top
management teams on company objectives and competitive methods for a sample of nineteen
firms competing within a highly fragmented industry—paints and allied products (SIC 2851).
It was hypothesized that intense competitive pressures and the resultant low industry
profitability would constrain organizational resources and augment the need for consensus on
both objectives and methods. However, findings indicate that consensus on either objectives
or methods is positively related to organizational performance.

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Philip James, Abby Ghobadian, Howard Viney, Jonathan Liu, (1999) conducted a study
on "Addressing the divergence between environmental strategy formulation and
implementation". The findings concluded that, despite growing evidence that large UK
organisations are increasingly incorporating the environment into corporate strategy, there
continues to be considerable scepticism as to whether this is leading to any meaningful action
to reduce industry‘s environmental impact. One possible explanation is the existence of a
―gap‖ between policy formulation and implementation, and the authors suggest that this may
be due to a failure on the part of business to ensure congruence between organisational
context, values and capability. Utilising data drawn from a recent survey of corporate
environmental policies and practices, the authors explore the interaction of external and
internal factors with regard to policy development, and search for evidence of congruence.
They conclude that very often policy formulation takes little consideration of the
organisation‘s capability to implement environmental strategies, and suggest that until this
question is taken seriously, a gulf will always exist between what companies aim to do, and
what they actually achieve.
Paul M. Swamidass of Graduate School of Business, Indiana University, Bloomington,
Indiana 47405 and William T. Newell of Graduate School of Business Administration,
University of Washington, Seattle, Washington 98195, (1987) conducted a study on
―Manufacturing Strategy, Environmental Uncertainty and Performance: A Path Analytic
Model‖. The study concluded that in recent years, researchers and practitioners are paying
increasing attention to the phenomenon of manufacturing strategy. However, there exists no
formal theory of manufacturing strategy to explain the phenomenon. There is a real need for
empirical studies for the development of such a theory. Findings of the study takes a step in
that direction by clarifying, organizing and integrating terms and concepts relevant to
manufacturing strategy in the process of conducting an empirical investigation of key
manufacturing strategy variables. The empirical section of the study based on data gathered
from 35 manufacturers found that environmental uncertainty influenced manufacturing
strategy variables such as Manufacturing Flexibility, and the Role of Manufacturing
Managers in Strategic Decision Making. The manufacturing strategy variables, in turn,
influenced business performance.

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Ann Marucheck, Ronald Pannesi, Carl Anderson (2007) conducted a study on ―An
exploratory study of the manufacturing strategy process in practice‖. This study presents an
exploratory empirical study of the process of formulating and implementing manufacturing
strategy within the framework of overall corporate strategy, as practiced by a cross-sectional
representation of leading-edge firms. The study shows that these firms' processes of
formulating manufacturing strategy seem to follow the general conceptual models developed
in the academic literature. However, the executives indicated that the real benefits of strategy
come from implementation, which is a less structured and behaviorally oriented process.
Future research must address infrastructural issues including culture, performance
measurement, and managerial style.
Ireland, R. D., Hitt, M. A., Bettis, R. A. and De Porras, D. A. (1987), conducted a study
on ―Strategy formulation processes: Differences in perceptions of strength and weaknesses
indicators and environmental uncertainty by managerial level‖. The conclusion of the study
noted that some literature suggests that managers' perceptions of strengths and weaknesses
indicators vary by management level. Differences likely result because of individuals'
cognitive schemes, which include their cognitive biases. In turn, systematic errors may occur
in managerial decisions. Results from the research reported herein support the notion that
managers' perceptions of the indicators of a firm's strengths and weaknesses, and of
environmental uncertainty, vary by managerial level. Differences in these perceptions were
discovered to be more significant within each firm. Implications of these results are
examined, including the impact on the deployment of firms' strategy formulation processes.
Xavier Gimbert, Josep Bisbe, and Xavier Mendoza (2010) conducted a study on ―The
Role of Performance Measurement Systems in Strategy Formulation Processes‖ and
concluded that most studies have focused on the role of strategic performance measurement
systems (SPMSs) in communicating the firm's strategy and facilitating its execution and
control, little is known about the role they might potentially play in shaping strategy
(re)formulation processes. Findings suggest that the use of SPMSs (as opposed to other forms
of PMS) by an organisation's top management team translates into a more comprehensive
strategic agenda. Prior studies have shown that strategic agendas shape the extent and
direction of corporate strategic change.
M.K. Nandakumar, Abby Ghobadian, Nicholas O'Regan, (2010) conducted a study on
"Business-level strategy and performance: The moderating effects of environment and
structure".

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Findings indicate that environmental dynamism and hostility act as moderators in the
relationship between business-level strategy and relative competitive performance. In low-
hostility environments a cost-leadership strategy and in high-hostility environments a
differentiation strategy lead to better performance compared with competitors. In highly
dynamic environments a cost-leadership strategy and in low dynamism environments a
differentiation strategy are more helpful in improving financial performance. Organisational
structure moderates the relationship of both the strategic types with ROS. However, in the
case of ROA, the moderating effect of structure was found only in its relationship with cost-
leadership strategy. A mechanistic structure is helpful in improving the financial performance
of organisations adopting either a cost-leadership or a differentiation strategy.
4. OVERVIEW OF CHAPTERS
Chapter scheme for the study is given below.
Chapter 1: Introduction- Chapter 1 contains a brief about the food manufacturing sector in
Zimbabwe for period between 2006 and 2013 and an introduction to the concepts and
variables investigated in the study. After the topic is introduced, the need and scope for the
present study is put forward.
Chapter 2: Literature Review- In this section, selected strategy formulation and
implementation literature related to rationality of strategy formulation, cost-related,
differentiation, degree of emphasis given to strategy formulation while implementing
strategies, dynamism, hostility organic structure, mechanistic structure, objective fulfilment
and relative competitive implementation performance are cited.
Chapter 3: Methodology – Chapter 3 details the methodology adopted for the present study.
Operational definitions, statement of the problem, variables under investigations, research
model adopted, hypotheses,, sample size, sampling techniques, tools employed for data
collection, description of the tools, pilot study results, administration of the questionnaire and
statistical techniques employed are discussed.
Chapter 4: Analysis of Data and Interpretation – Chapter 4 provides the analysis of data
which was subjected to certain statistical tools. Further, the research findings and its
interpretation are explained.
Chapter 5: Conclusion and Summary – Chapter 5 contains the summary of the findings,
conclusions and implications of the study. In this chapter, limitations of this research are
highlighted and recommendations for future research are made.
Finally, the thesis ends with detailed bibliography and appendices.

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5. TITLE OF THE STUDY
Strategy Formulation and Implementation in Zimbabwe Food Manufacturing Sector
(2006 -2013).
6. OPERATIONAL DEFINATIONS
Competitive advantage refers to an organization acquires or develops an attribute or
combination of attributes that allows it to outperform its competitors. It is the combination of
elements in the business model which enables a business to better satisfy the needs in its
environment, earning economic rents in the process.
Food Manufacturing is the transformation of raw ingredients into food, or of food into other
forms. Manufactured foods have been altered from their natural state for safety reasons and
for convenience. The methods used for processing foods include canning, freezing,
refrigeration, dehydration and aseptic processing
A strategy in this study means a business' road map or a broad plan developed by an
organization to take it from where it is to where it wants to be. A well-designed strategy will
help an organization reach its maximum level of effectiveness in reaching its goals while
constantly allowing it to monitor its environment to adapt the strategy as necessary.
Strategy Formulation involves answering a key question from a portfolio perspective:
"What business should a manufacturing firm be in and what creativity of unique and valuable
market position can the same firm have?". Strategic Formulation provides overall direction to
the enterprise and involves specifying the organization's objectives, developing policies and
plans designed to achieve these objectives, and then allocating resources to implement the
plans.
Strategy Implementation involves answering the question: "How shall we compete in this
business making trade-offs by choosing "what not to do", and creating "fit" by aligning
company activities to with one another to support the chosen strategy.? In implementation
theory and practice, a further distinction is often made primarily with improving efficiency
and controlling costs within the boundaries set by the organization's strategy. Strategic
implementation in the context of this study means the process that puts plans and strategies

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into action to reach goals. A strategic plan is a written document that lays out the plans of the
business to reach goals, but will sit forgotten without strategic implementation. The
implementation makes the company‘s plans happen. Considering manufacturing strategy in
its larger strategic context has been thematic in conceptual literature in operations but
relatively neglected in empirical studies, thus leaving predominant conceptual models of
manufacturing strategy largely untested. The contextual meaning of this research,
implementation of strategy involves developing a conceptual model of manufacturing
strategy from the literature and tests the model using data from a sample of manufacturers in
Zimbabwe.
Objective fulfillment: The nature of the multivariate relationship between six characteristics
of strategy formulation an implementation systems in the food manufacturing industries and
three different conceptualizations of planning effectiveness using canonical correlation
analysis while linking to the set targets.
Competitive Implementation Performance: This study examines the performance
implications of implementing generic competitive strategies, and whether the implementation
of a combination competitive strategy yields an incremental performance benefit over a
single generic competitive strategy using data from the food manufacturing industry in
Zimbabwe.
7. OBJECTIVES OF THE STUDY
The main objectives of the study are:
1) To test a proposed structural model of the relationship among the nine variables:
business strategy, objective fulfilment, competitive implementation performance,
implementation strategy, cost-related, differentiation variables, focus variables and
environment variables in strategy formulation and implementation.
2) To examine the influence of external and internal environment dynamism on strategy
formulation and implementation in the food manufacturing industry.
3) To test whether performance heterogeneity in food manufacturing organisations in
Zimbabwe can be explained in terms of their emphasis on rational strategy
formulation and implementation?

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4) To find out on factors which affect the success of strategy formulation and
implementation
5) To examine on whether the environment have a moderating effect on the relationship
between business-level strategy and whether there is a relationship between the type
of organisational structure and business strategy? If strategic types are associated with
structure types, then does this association explain performance heterogeneity?
6) To expose and evaluate government policy which provides ground rules, to set
directions and strategy and support the activity of business and other institutions in
their creative endeavours.
7) To recommend a model which lays bare the rationale behind strategy formulation and
implementation in the food manufacturing industry in Zimbabwe.
8. VARIABLES OF THE STUDY
The variables under investigation in this study are:
(i) Business Strategy –Dependent Variable (Endogenous Variables)
(ii) Objective Fulfilment - Dependent Variable (Endogenous Variables)
(iii)Competitive Implementation Performance - Dependent Variable (Endogenous
Variables)
(iv)Implementation Strategy - Dependent Variable (Endogenous Variables)
Independent Variables –(Cost-Related, Differentiation Variables, Focus Variables and
Environment Variables)
a) Cost –Related Variables
(i) Production capacity utilisation - Independent Variable (Exogenous Variable)
(ii) Operating efficiency - Independent Variable (Exogenous Variable)
(iii)Cost reduction - Independent Variable (Exogenous Variable)
(iv)Efficiency of securing raw materials- Independent Variable (Exogenous Variable)
(v) Administrative expenses - Independent Variable (Exogenous Variable)
(vi)Price competition - Independent Variable (Exogenous Variable)
b) Differentiation Variables
(vii) Rate of new product introduction to market- Independent Variable (Exogenous
Variable)
(viii) Emphasis on the number of new products offered to the market- Independent
Variable (Exogenous Variable)

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(ix)Emphasis on new product development or existing product adaptation to better serve
customers- Independent Variable (Exogenous Variable)
(x) Intensity of a business‘s advertising and marketing- Independent Variable (Exogenous
Variable)
(xi)Emphasis on building strong brand identification- Independent Variable (Exogenous
Variable)
(xii) Developing and utilising sales force- Independent Variable (Exogenous
Variable)
(xiii) Emphasis on producing high quality products - Independent Variable
(Exogenous Variable)
(xiv) Prompt response to customer enquiries and orders - Independent Variable
(Exogenous Variable)
c) Focus Variables
(xv) Targeting identified segments in the food manufacturing sector - Independent
(xvi) Offering specialty products - Independent Variable (Exogenous Variable)
(xvii) Uniqueness of the form‘s products - Independent Variable (Exogenous
Variable)
d) Environment Variables
(xviii) Rate of innovation - Independent Variable (Exogenous Variable)
(xix) Research and development (R&D) activity in the food manufacturing industry
- Independent Variable (Exogenous Variable)
(xx) Competitor activity in the market - Independent Variable (Exogenous
Variable)
(xxi) Growth opportunities in the overall food manufacturing industry - Independent
(xxii) Legal, political and economic constraints - Independent Variable (Exogenous
Variable)
Table 8.1: The Variables Representing Different Constructs used in this Study
Section in the
Questionnair
e
Constructs Variables Used Cronbach's
Alpha
Composite
Reliability
AVE
Business-level
Strategy
1.
Differentiatio
n
1. Mean of the summated
scale
consisting of diff 2,
diff 1, diff 4, diff 6 and
diff 7.
0.754 0.841 0.517
2. Cost-
related
2. Mean of the
summated scale
consisting of all cost related
0.823 0.866 0.525

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variables
External
Business
Environment
1. Dynamism 1. Mean of the summated
scale
consisting of the
variables namely
dyn2, dyn3, dyn4
and hct2
0.725 0.839 0.567
2. Hostility 2. Mean of the two
variables namely host 2 and
host 3
0.773 0.899 0.816
Strategy
Formulation
Extent of
Rationality in
Strategy
Formulation
Mean of the Summarized
scale consisting of the
variables namely sf1, sf3,
sf4, sf5, sf6, sf7,and sf8
0.839 0.884 0.525
Strategy
Implementatio
n
Degree of
emphasis
given to
planning
while
implementin
g strategies
Mean of the Summarised
scale consisting of the first
eight items in the scale
0.908 0.926 0.609
Structure Organic
Structure and
Mechanic
Structure
Mean of Summarised scale
consisting all of the variables
excluding st5 and st7
0.660
Organizationa
l Performance
1. Objective
fulfilment
scale consisting of variables
namely
Performance of 3,
performance of 4,
Performance of 6 and
performance of 7
0.693 0.814 0.523
2.Relative
Competitive
Performance
scale consisting of all the
variables used to measure
relative competitive
performance
0.916 0.929 0.594
According to Sharma, Durand and Gur-Arie (1981) there are two types of moderator
variables. One type of moderator variable influences the strength of relationship between the
predictor variables and the criterion variable and the other type modifies the form of
relationship (e.g. changing the sign of the slope). Sharma et al (1981) developed a typology

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of specification variables using two dimensions namely the relationship with the criterion
variable and interaction with the predictor variable. If the specification variable is related to
the criterion or predictor variable or both but does not interact with the predictor variable, the
variable is referred to as an intervening, exogenous, antecedent, suppressor or additional
predictor variable depending on its other characteristics.
9. CONCEPTUAL EQUATION AND HYPOTHESIS
 Dimension of Findings by Testing the Hypotheses
The hypotheses presented in chapter 1 were tested using various statistical techniques as
explained in chapter 3. These hypotheses are grouped into three categories. Hypotheses
concerning the relationship between strategy formulation and implementation belong to the
first group (sub-section 4.3.1) and those examining the relationship between business-level
strategy and other variables belong to the second group (sub-section 4.3.2). The third group
(sub-section 4.3.3) includes hypotheses inquiring into the relationship between strategy
implementation and other variables.
 Strategy Formulation and Implementation
The following hypotheses examining the relationship between strategy formulation and
implementation in the Zimbabwe food manufacturing industries were tested:
H1a: Rational-comprehensive strategy formulation will lead to superioror competitive
implementation performance in food manufacturing organisations.
H1b: Environmental dynamism and hostility moderate the relationship between
Strategy formulation and competitive implementation.
It was found that strategy formulation is significantly related to both the competitive
implementation measures and hence hypothesis H l a is supported. This finding agrees with
the findings of many previous studies discussed in chapter 1. While strategy formulation is
strongly related to objective fulfilment, its relationship with relative competitive
implementation performance is not very strong. This indicates that even though strategy
formulation helps organisations in the food manufacturing to achieve its set objectives, it
does not make a huge contribution towards improving organisational implementation
performance in comparison to its main competitors. This is an interesting finding and there
are a number of explanations for this observation. It shows that strategy formulation does not

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result in the establishment of market "sweet spots". There could be some other factors which
make a sizable contribution towards improving relative competitive implementation.
Hypothesis Hlb tested using moderated regression analysis, indicated that environmental
dynamism and hostility moderate the relationship between strategy formulation and relative
competitive performance. However, they do not moderate its relationship with objective
fulfilment. Hence hypothesis Hlb is partially supported. It was found that strategy
formulation helps organisations to improve its relative competitive implementation
performance in highly dynamic environments like in Zimbabwe (2006- 2013). This finding
confirms the findings of some previous studies (e.g. Miller & Friesen, 1983; Eisenhardt,
1989; Judge & Miller, 1991; Göll & Rasheed, 1997) which suggested that strategy
formulation is helpful in dynamic environments. It contradicts the findings of other studies
(e.g. Fredrickson, 1984; Fredrickson & Mitchell, 1984) which found that strategy formulation
is harmful in dynamic environments. The results of the analysis also indicated that strategy
formulation is strongly associated with relative competitive performance in highly hostile
environments. Göll & Rasheed (1997) had found that strategy formulation is helpful in highly
munificent environments and harmful in environments with low munificence.
Environments with low munificence are characterised as highly hostile environments and
hence there is a disagreement between the findings of this study and that of Göll & Rasheed
(1997).
The results taken together indicate that strategy formulation and implementation helps
organisations to improve their performance. Even though scholars like Mintzberg (1994)
have argued that strategy formulation has lost its relevance, the findings of this study
indicates a significant positive relationship between strategy formulation and organisational
implantation performance. It was also found that strategy formulation is helpful in dynamic
as well as hostile environments and this provides further support for strategy formulation.
Dynamic environments emphasise growth through technology development and innovation.
In such environments there is an overload of information and conflict between situations.
Strategy formulation helps organisations to process information using analytical tools and
arrive at consensus through participative decision-making. In hostile environments, the
surrounding factors are less favourable and the activities of competitors are belligerent.
Strategy formulation helps firms to identify the threats arising out of these unfavourable
factors through systematic analysis resulting in improved implementation performance.
 Other Conclusions

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(i) Business-level Strategy
Hypotheses H2a, H2b, H2c and H2d examining the relationship between business-level
strategy and implementation and hypothesis H3 examining the relationship between strategy
formulation and business-level strategy are discussed in this section.
H2a: Organisations in the food manufacturing industry having a clear business-level strategy
by adopting one of the strategies namely cost-related, differentiation or integrated strategies
will perform better than those organisations which are stuck-in-the-middle.
H2b: Organisations in the food manufacturing industry following integrated strategies will
perform better than those pursuing either a cost-related strategy or a differentiation strategy.
(ii)The Moderating Effect of Environment
H2c: Environmental dynamism and hostility moderate the relationship between business-
level strategy and organisational competitive implementation performance.
The moderating effect of environmental dynamism and hostility on the relationship between
business-level strategy and performance was assessed. It was found that there is a moderating
effect to some extent. Environmental hostility acts as a moderator in the following
relationships:
• Cost-related Strategy - Objective Fulfilment;
• Cost-related Strategy - Relative Competitive Performance; and
• Differentiation - Relative Competitive Performance.
It was found that in environments with low levels of hostility, cost-related strategy leads to
better strategy implementation performance. However, a differentiation strategy can help
organisations in improving their relative competitive performance in highly hostile
environments.
(iii)The Role of Organisational Structure
H2d: Organisational structure moderates the relationship between business-level strategy
and organisational competitive implementation performance.
The evidence does not support the proposition that organisational structure moderates the
relationship between business-level strategy and implementation. However, the results
indicated a significant role played by organic structure in this relationship. It was found that
within the group of organisations in the food manufacturing industry in Zimbabwe adopting a
clear strategy (cost-related, differentiation or integrated strategy); those having organic
structure implement better than those firms which nave a mechanistic structure.
(iv)Strategy Formulation and Business-level Strategy

20
H3: Organisationsin the food manufacturing industry in Zimbabwe placing a strong
emphasis on strategy formulation will develop a clear business-level strategy by adopting
one of the strategies namely cost-related, differentiation or integrated strategies.
The relationship between strategy formulation and business-level strategy was examined by
testing hypothesis H3. The findings of the logistic regression analysis indicated that strategy
formulation significantly increased the probability of having a clear strategy for an
organisation in the food manufacturing industry. This finding establishes the link between
strategy formulation and business-level strategy. This relationship has not been examined in
the previous studies and hence this finding is important. The findings of H l a and H2a
suggest that both strategy formulation and clarity in business-level strategy help organisations
to improve their implementation performance.
.
(v)Strategy Implementation
The results obtained by testing hypotheses H4, H5a and H5b are examined. H4 examines the
impact of formulation of strategy implementation on competitive performance, H5a looks
into the relationship between strategy formulation and strategy implementation and H5b
assesses the relationship between clarity in business-level strategy and formulation of
strategy implementation.
(vi)Strategy Implementation and Competitive Implementation Performance
H4: The degree of formulation of strategy implementation has a significant positive impact
on organisational competitive strategy implementation performance
The relationship between planning of strategy implementation and both the competitive
strategy implementation performance measures were statistically significant. However, the
strength of this relationship is much higher in the case of objective fulfilment. Even though
its relationship with relative competitive performance is statistically significant, the
regression results indicate that the R value is very low. Hence hypothesis H4 is partially
supported indicating that emphasis on strategy implementation helps organisations to
improve their competitive performance.
(vii) Strategy Formulation and Strategy Implementation
H5a; Organisations in the food manufacturing industry in Zimbabwe placing a strong
emphasis on strategy formulation will also place a strong emphasis on the formulation of
strategy implementation

21
H5b: Organisations in the food manufacturing industry in Zimbabwe having a clear strategy
by adopting one of the strategies namely cost-related, differentiation or integrated strategies
will give more emphasis to the formulation of strategy implementation than those
organisations which are stuck-in-the middle
The results of the ANOVA indicated that organisations in the food manufacturing sector in
Zimbabwe which have clearly defined their strategy by adopting a dominant strategic
orientation (cost-related, differentiation or integrated strategy) give greater emphasis to the
formulation of strategy implementation than stuck-in-the-middle companies.
Fig 9.1 Model with Path Coefficients, 't' Values and R 2 Values
The path names, path coefficients and 't ' values are shown for each path. For significant
paths, the path coefficients are shown in bold letters. The significance levels (one-tailed) are
interpreted as: t>64, significant at p<0.05 level (*); t>.96, significant at p<0.025 level (**);
t>58, significant at p<0.005
The variable representing clarity in business-level strategy is defined as:

22
If business strategy type = Cost-related OR Differentiation OR Integrated Strategy, then
clarity in strategy = l (Clear strategy) ff business strategy type = Stuck-in-the-middle, then
clarity in strategy = 0 (Unclear strategy) The path names, path coefficients and 't ' values are
shown for each path. For significant paths, the path coefficients are shown in bold letters. The
significance levels (one-tailed) are interpreted as: t>64, significant at p<0.05 level (*); t>96,
significant at p<0.025 level (**); t>.58, significant at p<0.005 level (***).
The composite scale reliabilities and the AVE values of each construct and the factor
loadings and the t' values of the indicators representing each construct in model as indicated
below:
 Strategic Formulation (Composite Reliability = 0.884, AVE = 0.524)
 Formulation of Strategy for Implementation (Composite Reliability = 0.925, AVE =
0.609)
 Performance - Objective Fulfilment (Composite Reliability = 0.813, AVE = 0.522)
 Performance -Relative Competitive Performance (Comp Reliability = 0.930, AVE = 0
 Clarity in Business-level Strategy (Composite Reliability = 1.000, AVE = 1.000)
Factor loadings of all the items are above 0.5 and most of them are either above 0.7 or very
dose to 0.7. The 't' values of all the items are significant and the composite reliability values
of all the constructs are above 0.7. The AVE values of all measures are above 0.5 and this
indicates that the measures have convergent validity.
For assessing the discriminant validity of the model, the AVE values are plotted as diagonal
items and Squares of the correlations obtained from the PLS output are plotted as off-
diagonal items.
The results obtained by testing the structural model confirm the findings of the hypotheses
H3 and H5a. For H1a and H4, the results match when Performance - Objective Fulfilment is
the dependent variable and they do not match when Relative Competitive Performance is the
dependent variable. However, the two results do not match for the hypotheses H2a and H5b.
The model indicates that relative competitive performance cannot be effectively predicted by
using the variables involved in this study. However objective fulfilment can be effectively
predicted using strategy formulation and planning of strategy implementation. The model
also indicates that strategy formulation has significant positive relationships with clarity in
business-level strategy and planning of strategy implementation. However clarity in business-
level strategy does not predict either of the performance indicators or the planning of strategy
implementation.
10. DESIGN OF THE STUDY
10.1 Research Design
The present study is designed as an explanatory study using survey method. The study is
quantitative in nature and the primary data was collected from eligible respondents using

23
validated instruments through structured questionnaire. Research design at glance is
presented in table10.1
Table 10.1: Research Design at glance
Design of Data Explanatory
Sources of Data Collection Primary Quantitative data collected using self administered
structured questionnaire using Likert scale
Population All CEO and Business Executives representing companies
affiliated to CZI (Confederation of Zimbabwe Industries)
Sampling element Individual company representatives (CEO and Business
Executives) in the manufacturing sector in Zimbabwe
Sampling technique Probability sampling technique: Single stage cluster random
sampling technique
Sampling Unit Individual companies in the food manufacturing industries
affiliated to the Confederation of Zimbabwe Industries.
Sampling frame List of C.E.O and Business Executives in the manufacturing
sector in Zimbabwe according to the Business Directory
Sample size Actual realized sample -120
Statistical Analysis  Descriptive statistics-Mean/Standard deviation
 Reliability Analysis-Cronbach‘s alpha
 Correlation Analysis
 Test for normality-Skewness Kurtosis Test
 Exploratory factor analysis
 Structural Equation Model- Confirmatory factor
analysis, Competitive Model of fit measures, Path
analysis
Statistical Software package  SPSS (Statistical Package for Social Science)
Version 17
 AMOS (Analysis of Moments Structures) Version 18
 PLS (Partial Least Squares) structural equation
modelling technique

24
Table 10.2: Analytical Techniques used
Analytical Technique No. of times used
Correlation Analysis 24
Regression Analysis 14
Logistic Regression 1
Moderated Regression Analysis 1
t-test 23
Chi-Square test 15
Percentage Comparisons 8
Cross Tabulations 4
ANOVA 13
MANOVA 4
ANCOVA 1
Discriminant Analysis 6
Canonical Correlation Analysis 4
Kendall Tau Rank Correlation 2
Wilcoxon Test 1
Structural Equation Modelling 2
As indicated in Table 10.2 the most widely used analytical methods in examining the
relationship between strategy formulation and implementation are correlation analysis,
regression analysis, t-test, Chi-Square test and ANOVA. Regression analysis and correlation
analysis were used to determine the relationship between strategy formulation on
implementation. The t-test, ANOVA and Chi-Square test are mainly used to compare the
implementation of strategy formulators and non-formulators. Most of the studies have
examined bivariate relationships and this could be one of the main drawbacks of the studies.
The relationships may change if more variables are studied together. Structural equation
modelling technique which could be used to examine multivariate causal relationships was
used only twice. In this study, multivariate relationships are examined using partial least
squares (PLS) which is a structural equation modelling technique.
10.2 Population
The target population was all CEOs and Business Executives representing companies
affiliated to CZI (Confederation of Zimbabwe Industries). The target population of 180 was
computed by collecting the data from official website of the Food Manufacturing –Zimbabwe
Business Directory (www.zimbabweyp.com>Categories>food and drink), Zimtrade Food
Processing (www.zimtrade.co.zw/pdf/sector%20right-ups/Processed%20Foods), Zimbabwe
Food Processing Industry (www.yellowpagesofafrica.com/companies/zimbabwe/food-

25
processing-in), Food Manufacturing in Zimbabwe
(www.mbendi.com/indy/fdbt/food/af/zi/index.htm) and the Confederation of Zimbabwe
Industries (www.czi.co.zw, www.keycontacts.info/zimbabwe). The researcher also
personally visited the various food manufacturing firms or get information on the phone
10.3 Sampling Technique
Single stage cluster random sampling; a probality sampling technique, was undertaken for
selection of the sample from the population, in order to obtain a representative sample. The
population (180 C.E.O and Business Executive) was divided into sub population of 32
individual industries and the cluster were numbered from 1-32. The next step was to
determine the sample size by using the rule of thump found in the literature. Sample size (N)
formular suggested by Tabachnick and Fidell (2001) was used. Tabachnick and Fidell (2001)
explained that the adequate sample size should be: N> (Number of items in the Questionaire
x8)+50.
Using the Excel application RANDBETWEEN (.) function, random numbers were generated
to select the clusters. Sequence of random numbers obtained in ascending order were: 2,
3,4,5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,, 24, 25, 26,
27,28,29,30,31,32). Once the random sample of clusters was selected, all the members of the
clusters (sampling elements) were surveyed. All C.E.Os and Business Executives in all the
manufacturing sectors were selected randomly for data collection and sureveyed and as such
the sample size requirement was met for the study.
11. TOOLS USED FOR COLLECTION OF DATA
Reliable and valid tools were used to measure the nine latent constructs under investigations.
All measurement scales used in the present study were adopted from the standardized
(reliable and valid) existing scales with limited modifications to suit the Zimbabwean
context. Since the original scales were developed in a foreign environment, semantic and
cultural transportability issues were examined and changes were incorporated wherever
necessary. In all cases the study used a 5-point Likert scale with anchors at ―strongly agree –
strongly disagree‖.
Tools used in the present study are:
12. FIELD WORK DETAILS
Pilot studies was conducted on a sample of 150 respondents. Tools were checked for face
validity and reliability. Questionnaire was revised and administered in 30 food manufacturing
firms in Zimbabwe between July 2013 to November 2013. Data was collected from a sample
of 120 Chief Executive Officers from a population of 160. To collect the data, the researcher
first took the permission from the different food manufacturing company. The researcher

26
personally e-mailed, posted and distributed the questionnaires to all respective respondents.
This ―personal touch‖ was successful in eliciting a good response. The respondents took three
(3) –five (5) working days to complete the entire questionnaire. Participation in the survey
was voluntary. All Chief Executive Officers, Business Executives and Captains of the Food
Manufacturing Industries affiliated to the Confederations of Zimbabwe Industries were
considered for the purpose of the study, however, some respondents were not always
available in the country from time to time as they were also overseeing their foreign
subsidiaries. Thus actual realised sample is less than target sample. The target sample size
was 180 and the actual realised sample was 120.
Table 12.1 Sample clusters(individual company) included in the present study
Serial No Cluster
No
Name of the Company Target Sample Actual
Realised
Sample
1 2 Victoria Foods 6 2
2 29 United Refineries 5 3
3 4 Straitia Beverages 3 3
4 27 Alpha & Omega Industries 5 4
5 6 Delta Beverages 25 10
6 25 African Distributors 8 6
7 8 Schweppes 9 8
8 23 Cairns Foods 5 5
9 10 Colcom 6 4
10 21 Premier Milling 2 1
11 12 Olivine Industries 8 5
12 19 Anchor Yeast 5 3
13 14 Lake harvest 3 1
14 17 Crystal candy 3 2
15 16 Dandy Zimbabwe 3 1

27
16 15 M E Charhons 2 1
17 18 Arenel sweets 6 3
18 13 Lebena Biscuits 3 2
19 20 Iris Manufacturing 5 2
20 9 Innscor 12 5
21 22 Dairibord Zimbabwe 11 13
22 7 Nestle Zimbabwe(Pvt) Ltd 10 8
23 24 Lyons Zimbabwe 5 3
24 5 National Foods 5 5
25 26 Four seasons foods 2 2
26 3 Tanganda Tea Co 3 3
27 28 Zimbabwe Sugar Refineries 5 3
28 31 ARDA Katiyo 4 4
29 30 Lobels bread 5 3
30 32 Unilever 6 5
Total 180 120
Note:
*Target sample 180 Chief Executive Officers, Business Excutives and Captains of the
industry affliliated to the Confederations of Zimbabwe Industries (CZI)
*Actual realised sample 120 participants composed of Chief Executive Officers (CEO),
Business Executives and Captains of the industry.
13. STATISTICAL TECHNIQUES
The following statistical techniques were used to find meaning in the data:
Descriptive statistics: Measures: Measures of Central tendency and dispersion of the data
(mean and standard deviation) were used to describe the distribution of the responses to
different items.

28
Reliability test: Reliability test using Cronbach‘s coefficient alpha was used to test the
reliability of the scales.
Correlation Analysis: Correlation Analysis was performed to assess the strength of the
linear relationship between the variables.
Exploratory factor analysis: There are different methods of extracting factors using EFA.
Widely used methods is Principal Componebt Analysis (PCA). PCA is a variance based on
extraction method of factor analysis. PCA using varimax rotation was employed to extract the
underlying latent structure and to prepare the data for further analysis (structural equation
modeling).
Skewness kurtosis Test: Skewness kurtosis test was employed for testing normality of the
data.
Confirmatory Factor Analysis (CFA); CFA was used to test ―the overall competitive model
of strategy formulation and implementation‖ and the measurement of the model
Path Analysis a part of structural equation modelling was employed to test the significance
of the hypothesized casual relationships
14. VALIDATION PROCEDURES
Tools used to measure the nine constructs under investigation were adopted from existing
validating scales. Furthermore these tools were checked for reliability and validity:
14.1 Face validity: Face validity was done to assess the psychometric soundness of the scale.
Pilot study questionnaire was given to the Chief Executive Officers, Business Executives and
Captain of the industry (initial focus group of 18 in number) to get the expert opinion and
check the content validity. Feedback from this initial focus group who reviewed the
questionnaire confirmed that the questionnaire- with minor word changes in a few items- had
face validity.
14.2 Reliability test (Inter-item reliability): Cronbachs‘ alpha was used in this study to
evaluate the internal consistency of the survey items. The reliability test showed that the
Cronbachs alpha for all the scales and factors were above the acceptable range of .70
indicating internal consistency (Cronbach & Shavelson, 2004; Nunnally & Bernstein 1994)
14.3 Average Variance Extracted –Convergent Validity: Construct validity of the scale
was assessed using output measures of factor analysis. The key output in factor analysis is
Average Variance Extracted (AVE) by indicators of hypothesized construct. As a rule of
thumb, the minimum recommendation level of AVE is 0.50 (Fornell &Larcker, 1981a) The
factor analysis performed for all the study constructs reported AVE of above .60 confirming
the construct validity of the scales used. The AVE confirms the convergent validity of the
scales used in the study.

29
14.4 Factor Structure –Divergent Validity: The simple factor structure extracted from
principal component analysis confirms the divergent validity of the scales used in the study.
Straub (1989) posit that, constructs are different if their respective indicators load mostly
heavily on different factors in principal components factor analysis.
14.5 Confirmatory Factor Analysis- Convergent and Discriminant Validity:
Confirmatory factor analysis shows that all the key fit indices of measurement model are at
acceptable level indicating that the data fits the model well and further suggests convergent
validity and discriminant validity (Anderson and Gerbing, 1988).
15. DATA ANALYSIS
Once data was collected, data was analysed so as to find meaning in the data. The data
analysis is presented in this section:
The procedures for reducing the data by conducting reliability and factor analyses and for
assessing the composite reliability and convergent validity are explained in this chapter.
Cronbach's alpha values of the scales measuring each construct were computed in order to
ascertain whether these values are within the acceptable limits. Subsequently exploratory
factor analysis was performed using the methods of Principal Components Analysis (PCA)
and Factor Analysis (FA) to determine the factor loadings.
Factor analysis was conducted on the variables in order to facilitate data reduction. Both PCA
and FA were used for conducting the factor analysis on the variables. As a result the variables
which should be used as measures for each construct were identified.
15.2 Reliability and Factor Analyses
Reliability assesses the degree of consistency between multiple measurements of a variable
(Hair et al, 2006). Generally two different methods namely test-retest reliability and internal
consistency are used to assess the reliability of the measures used in empirical research.
Cronbach's alpha (Cronbach, 1951; Nunnally, 1979; Churchill, 1979; Peter, 1979) is the most
widely used reliability coefficient to measure internal consistency. In this study Cronbach's
alpha was used to assess the reliability of the scales. Even though many authors have
suggested that the lower limit of acceptability for Cronbach's alpha value is 0.7, in
exploratory research 0.6 is also acceptable (Robinson, Shaver and Wrightsman, 1991).
Factor analysis is an interdependence oriented technique whose main purpose is to define the
underlying structure among the variables in the analysis. Unlike dependence oriented
techniques like regression analysis and ANOVA, factor analysis provides the tools for
analysing the structure of the interrelationships among a large number of variables by
defining sets of variables that are highly interrelated, known as factors (Hair et al, 2006).
The means, standard deviations, skewness and kurtosis values of the final set of variables
representing each construct obtained after the data reduction process and these values of the
overall constructs are presented.
15.3 Reliability Analyses of the Scales
The Cronbach's alpha values obtained for each of the scales and the values reported in
the studies from which these scales were adapted are shown in Table 4.1.

30
Table 15.1 Reliability of the Scales
Section in the
Questionnaire
Constructs
Measured
Value of
Cronbach's Alpha
in this Study
Value of
Cronbach's Alpha
in the Original
Study
Business-level
Strategy
Cost-related
Differentiation
Focus
0.823
0.732
0.532
0.75
0.72
0.73
External Business
Environment
Dynamism Hostility
Heterogeneity
0.680
0.433
0.283
Not
available
Strategy
Formulation
Extent of Rationality
in Strategy
Formulation
0.836 0.85
Strategy
implementation
Planned Option
Prioritised Option
0.867
0.817
Not
available
Structure Organic and
Mechanistic
Structure
0.587 0.82
Organisational
Implementation
Performance
Objective Fulfilment
Relative
Competitive
Implementation
Performance
0.750
0.916
0.748
0.953
AU the measures except focus, hostility, heterogeneity and structure have acceptable
Cronbach's alpha values. The data reduction process carried out for those measures which do
not have acceptable levels of Cronbach's alpha are explained in the
subsequent sections. It can also be noted that the Cronbach's alpha values of cost related,
differentiation, strategy formulation and the two measures of organisational performance are
very close to the values reported in studies from which these scales were selected.
15.4.1 Formulating Business-level Strategy
The results of the KMO measure of sampling adequacy and Bartlett's Test of Sphericity for
all the three constructs are shown in Table 4.2. The results indicate that the variables used to
measure all the three constructs can be factor analysed, Principal Components analysis was
carried out separately on all the three formulated business-level strategy constructs namely
Cost-related, differentiation and focus.
Table 15.2: KMO and Bartlett's Test Results for Strategy Variables
Variable KMO Measure of
Sampling Adequacy
Bartlett's Test of Sphericity
Cost-related 0.855 Significant
Differentiation 0.729 Significant
Focus 0.593 Significant
* Significant at P<0.001 level

31
The correlations between the variables corresponding to the three constructs are presented in
tables H . l , H.2 and H.3 in Appendix H. A number of correlations shown in these three
tables are significant and this indicates that they could be factor analysed. A principal
components analysis was conducted on the cost-related strategy variables and the component
loadings are shown in Table 15.3.
Table 15.3: Component Matrix for Cost-related Strategy Variables
Items in the Scale Component
1
Emphasis on production capacity utilisation (Cost-related4) .807
Emphasis on operating efficiency (e.g. productivity in production or
efficiency in outbound logistics) (Cost-retated3)
.788
Emphasis on finding ways to reduce costs
(e.g. standardising the product or increasing the economy of scale)
(Cost-related2)
.780
Emphasis on efficiency of securing raw materials or components ^ ^
(e.g. bargaining down the purchase price) (Cost-related 1)
.710
Emphasis on tight control of selling/general/
administrative expenses (Cost-related6)
.649
Emphasis on price competition (i.e. offering competitive prices) (Cost-
related5)
.630
Extraction Method: Principal Component Analysis.
All the variables are strongly loaded on the first component indicating that these variables
measure the cost-related strategy construct. This was ascertained by examining the composite
reliability (.867) and average variance extracted (.525) using PLS. It was decided to take the
mean of the summated scale of all these variables as a measure of the cost-related strategy
construct.
The communality estimates of two variables namely diff1 and diff9 are .315 and .373
respectively indicating that the two variables do not make a significant contribution towards
measuring the factors. The first factor consisting of three variables (diff 3, diff4 and diff 3)
represent the innovation dimension of differentiation and the second factor consisting of
another three variables (diff 5, diff7 and diff6) represent the marketing dimension of
differentiation. This finding is consistent with the operationalisation of differentiation
strategy by Miller (1991) using two constructs namely innovative differentiation and
marketing differentiation. However the third factor consisting of diff 8, diff 9 and diff 1
collectively do not represent any particular dimension. Even though the rotated component
matrix indicates that three factors could be formed with these variables, when Cronbach's
alpha values were calculated for the variables belonging to these factors, it was found that
only the first factor had a satisfactory value (0.799). Hence a common factor analysis with
varimax rotation was conducted and the factor matrix is presented in Table 15.7.

32
Table 15.4: Rotated Factor Matrix for Differentiation Variables
Factor
1 2 3
Differentiatton3 .886
Differentiation4 .677 .403
Differentiation2 .615 .323
Differentiation 5 727
Differentiation7 .578
Differentiation 1 .321
Extraction Method: Principal Axis Factoring.
Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 4 iterations.
The results are similar to the results of the principal components analysis and hence do not
give a clear indication about summarising the variables. A second order factor analysis was
conducted to find out whether these three factors load on one factor and it was found that all
the three factors loaded on one factor. This shows that the variables loaded on the three
factors could be effectively combined to form a single factor which represents the construct.
In order to identify the variables which could be used to form this single factor the composite
reliability and convergent validity of the variables were examined using PLS.
The variables namely diff 1, diff 5, diff 8 and diff 9 had to be excluded in order to achieve
acceptable levels of composite reliability and convergent validity. The Conbach's alpha value
for these five variables is .754 which is acceptable. It was decided to compute the mean of the
summated scale of these five variables for use in further analysis.
The Cronbach's alpha values for these two combinations were calculated and these values
were 0.45 for focus2 and focus4 and 0.502 for focus 1 and focus3. Both these values are
below the acceptable levels. Due to the limited number of variables it was not possible to find
an effective combination of variables which would satisfy the requirements of reliability and
validity hence the focus strategy variable was excluded from the analysis.
15.4.2 External Business Environment in the Food Manufacturing Industry in
Zimbabwe
Miller (1987) had used dynamism, hostility and heterogeneity as three separate measures of
the external business environment. The reliabilities of these constructs were assessed and
found to have Cronbach's alpha values of 0.680, 0.283 and 0.433 respectively. Because of the
low Cronbach's alpha values, all the eleven items used to measure these three constructs were
pooled and a factor analysis was performed with the view to identify the underlying
dimensions.
A number of correlations are significant indicating that the variables can be factor analysed.
The KMO measure of sampling adequacy is acceptable (.644) and Bartlett's test of sphericity
produced significant result. Hence factor analysis can be conducted on the environment
variables.

33
A principal components analysis with varimax rotation was conducted and the communality
estimates and percentage variances are shown in tables H.6 and H.7 in Appendix H. The
factor loadings are shown in Table 15.11. The communality estimates of a few items are
below 0.5. Three factors have Eigen values greater than 1 indicating that three factors could
be extracted and the three factor solution explains a total of 58.43% variance.
Table 15.5: Rotated Component Matrix for Environment Variables
1 2 3
The rate of innovation of new operating processes and new
products or
services in your principal industry has (decreased / increased
dramatically)
(Env. - Dynamism)
.806
Research and development (R&D) activity in your principal
industry has
(decreased / increased dramatically) (Env. - Dynamism4)
.762
Required variety in your production methods to cater to your
different
customers has (decreased / increased dramatically) (Env. -
Heterogeneity 2)
.670
Production technology in your principal industry has (remained
the same /
changed very much) (Env. – Dynamism 2)
.666
Required variety in your marketing tactics to cater to your
different customers
(has decreased / increased dramatically) (Env. – Heterogeneity l)
.501
Market activities of our key competitors now affect our firm in
many more
areas (e.g. pricing, marketing, delivery, service, production,
quality) than before
(Env. - Hostility3)
.889
Market activities of our key competitors have become far more
hostile (Env. -
HostiIity 2)
.874
Market activities of our key competitors have become far more
predictable
(This item was reverse coded) (Env. – Hostility l)
.774
Growth opportunities in the overall business environment have
(decreased /
increased dramatically) (Env. – Dynamism l)
.443 -.723
Legal, political and economic constraints
(e.g. Government regulations) have (Not changed / Increased
dramatically)
.516

34
(Env. - Hostitity4)
15.4.3 Strategy Formulation
A reliability analysis was conducted on the scale used to measure strategy formulation and
it had a Cronbach's alpha of 0.836. The correlation matrix of ail the variables used to measure
this construct is shown in table H.8 in Appendix H. Most of the correlations are significant
indicating that the variables can be factor analysed. The KMO measure of sampling adequacy
is .829 and Bartlett's test of sphericity produced significant result. A principal components
analysis with varimax rotation was conducted and the communality estimates and percentage
variances are shown in tables H.9 and H. 10 in Appendix H. The factor loadings are shown in
Table 15.6.
Table 15.6: Rotated Component Matrix for Strategy Formulation Variables
Items in the Scale
Component
1 2
Open channels of communication (Strategy Formulation 7) .871
Participative consensus-seeking decision-making with feedback (Strategy
Formulation 6)
.836
The explanation of proposed organisational changes to those affected by
them (Strategy Formulation 5)
.721
The strategic and long-term importance of participative decision-making
at management
levels (Strategy Formulation 3)
.708 .443
Written strategic plan(s) (Strategy Formulation 8) .604 .368
A systematic consideration of costs and benefits when planning (Strategy
Formulation2)
.811
A systematic search for opportunities and problems when planning
(Strategy Formulation l)
.360 .794
The application of operations research techniques (Strategy Formulation
4)
.671
The first factor consisting of variables namely sp7, sp6, sp5, sp3 and sp8 represents the
process involved and the second factor consisting of three variables (sp2, sp1 and sp4)
represents the analysis. Miller & Friesen (1983) had used "analysis" as one of the dimensions
for operationalising strategy-making in their study. A common factor analysis was conducted
on these variables and the loadings are shown in Table 15.7.
Table 15.7: Rotated Factor Matrix for Strategy Formulation Variables
Factor
1 2
Strategy Formulation 7 .842
Strategy Formulation 3 .657 .464

35
Strategy Formulation 8 .510 .371
The results are similar to the ones obtained from PCA. However Göll & Rasheed (1997) who
had used this scale to measure strategy formulation used the summated scale consisting of all
the items for analysis. In order to keep the measures parsimonious, a second order factor
analysis was conducted and it was found that both these factors loaded on one factor.
15.4.4 Strategy Implementation
Strategy implementation was measured in terms of the degree of emphasis given to
formulation and prioritisation while implementing strategies. The strategy formulation
emphasis was measured using five items in the scale and the prioritisation emphasis was
measured using three items. The sub-scale used to measure the planning emphasis had a
Cronbach's alpha value of 0.867 and the sub-scale used to measure prioritisation emphasis
had a Cronbach's alpha value of 0.817. However, a factor analysis was conducted to find out
whether these two sub-scales were measuring two constructs or not.
The communality estimates and percentage variances are shown in tables H. 12 and H. 13 in
Appendix H. Ali the communality estimates are above 0.5 indicating that the entire eight
variables can be retained in the analysis. Only one factor has an Eigen value greater than 1
explaining 61% of variance, indicating that this construct could possibly be represented by
one factor.
Table 15.8: Component Matrix for Strategy Implementation Variables
1
The tasks to be performed were specified beforehand to ensure effective
strategy
implementation (Imp. - Specificity)
.828
Organisational structure facilitated the strategy implementation process
through
appropriate allocation of responsibilities and roles (Imp. - Structural
Facilitation)
.824
Resources (including people, money and time) were available during the
strategy implementation process (Imp. - Resourcing)
.795
The criteria for success of strategy implementation were clear (Imp. -
Assessability)
.794
Strategy implementation had a receptive context at the outset due to the
conditions within
and/or external to your organisation (Imp. - Receptivity)
.767
What was done during the implementation process was acceptable to those
involved (Imp.
- Acceptability)
.748
Strategy implementation was given priority over other commitments (Imp. -
Priority)
.746
Relevant experience was available (either in-house, outsourced, or bought-in) .737

36
to implement strategies in your organisation (Imp. - Familiarity)
1 component extracted.
The factor loadings obtained from Principal Component analysis, common factor analysis
and maximum likelihood factoring are shown in successive tables. In all the cases the
variables are strongly loaded on one factor, giving a strong indication that only one single
factor will represent the construct. This shows that these variables are not measuring the two
options for strategy implementation namely planned option and prioritised option, but they ail
measure the degree of emphasis given to planning while implementing strategies.
Table 15.9: Factor Matrix for Strategy Implementation Variables -
Principal Axis Factoring
Factor
1
Imp. - Specificity .805
Imp. – Structural Facilitation .801
Imp. - Resourcing .762
Imp. - Assessability .760
Imp. - Receptivity .727
Imp. - Acceptability .703
Imp. - Priority .702
Imp. - Familiarity .690
1 factor extracted. 5 iterations required.
Table 15.10: Factor Matrix for Strategy Implementation Variables -
Maximum Likelihood Factoring
Factor
1
Imp. - Specificity .802
Imp. – Structural Facilitation .798
Imp. - Resourcing .759
Imp. - Assessability .759
Imp. - Receptivity .728
Imp. - Acceptability .709
Imp. - Priority .703
Imp. - Familiarity .692
Extraction Method: Maximum Likelihood.
1 factor extracted. 4 iterations required.
A reliability analysis was conducted with all these eight variables produced a Cronbach's
alpha value of 0.908. As shown in Table 15.18, all items have high corrected item - total
correlation values indicating that there are strong correlations between each item and the
overall score from the scale.
Table 15.11 : Item-Total Statistics - Strategy Implementation
Scale Scale Corrected Squared Cronbach's

37
Mean if
Item
Deleted
Variance
if
Item
Deleted
Item-Total
Correlation
Multiple
Correlation
Alpha if
Item
Deleted
Imp. - Familiarity 32.4839 54.236 .655 .467 .900
Imp.-Assessability 32.4355 53.288 .718 .566 .895
Imp. - Specificity 32.4677 51.405 .761 .646 .891
Imp. - Resourcing 32.7258 52.054 .721 .549 .894
Imp. - Acceptability 32.4839 56.089 .665 .532 .900
Imp. - Receptivity 32.6210 53.977 .686 .634 .897
Imp. – Structural
Facilitation
32.6290 50.772 .759 .666 .891
Imp. - Priority 32.8468 52.830 .669 .511 .899
The measure of planning of strategy implementation has a good composite reliability and
convergent validity. Hence, a summated scale comprising of all these eight variables was
computed and its mean was calculated. This new variable represents the degree of emphasis
given to planning while implementing strategies.
15.4.5 Organisational Strategy Implementation Performance
Organisational strategy implementation performance was measured using two constructs
namely objective fulfilment and relative competitive performance. The scale used to measure
objective fulfilment had a Cronbach's alpha value of 0.750 and the scale used to measure
relative competitive performance had a Cronbach's alpha value of 0.916. The correlation
matrices of the variables representing these two constructs are shown in tables H. 17 and
H.20 in Appendix H and a number of these correlations are significant.
The KMO measure of sampling adequacy for the objective fulfilment measures is .751 and
for relative competitive performance measures is ,869.The Bartlett's test of sphericity is
significant for both the performance measures. Hence the variables corresponding to both the
measures can be factor analysed. A principal components analysis with varimax rotation was
carried out on objective fulfilment measures and the communality estimates and the
percentage variances are shown in tables H. 18 and H. 19 in Appendix H. The factor loadings
are shown in 15.12.
Table 15.12: Rotated Component Matrix for Performance - Objective Fulfilment
Variables
1 2
Predicting future trends (Perf. - Obj. Fulfilment3) .838
Evaluating alternatives based on relevant information (Perf. - Obj.
Fulfilment 4)
.830
Avoiding problem areas (Perf. - Obj. Fulfilment 5) .489 .372
Improvement in short-term performance (Perf. - Obj. Fulfilment l) .791
Improvement in long-term performance (Perf. - Obj. Fulfilment 2) .713
Resolving Problems (Perf. - Obj. Fulfilment 6) .318 .587

38
Enhancing management development (Perf. - Obj. Fulfilment 7) .479 .555
The factor loadings obtained from principal components analysis do not provide a clear
indication about the number of factors which can be extracted. Hence, factor analysis was
conducted using the principal axis factoring and maximum likelihood methods and the factor
loadings are shown in Table 15.12 and 15.13 respectively.
Table 15.13: Rotated Factor Matrix for Objective Fulfilment - Principal Axis Factoring
FACTOR
1 2
Perf. - Obj. Fulfilment 2 .594
Perf. - Obj. Fulfilment 7 .585 .334
Table 15.14: Rotated Factor Matrix for Objective Fulfilment- Maximum Likelihood
Factoring
FACTOR
1 2
Extraction Method: Maximum Likelihood.
The composite reliability value is very high and AVE is above 0.5. Hence the items
measuring relative competitive performance have both composite reliability and convergent
validity. A new variable was computed by taking the mean of the summated scale consisting
of all the above variables and it was used in the analysis as a measure of relative competitive
performance.
Factor analysis was conducted on the variables in order to facilitate data reduction. Both PCA
and FA were used for conducting the factor analysis on the variables. As a result the variables
which should be used as measures for each construct were identified.
The results obtained by testing the structural model confirms the findings of the hypotheses
H3 and H5a. For H1a and H4, the results match when Performance - Objective Fulfilment is
the dependent variable and they do not match when Relative Competitive Performance is the
dependent variable. However, the two results do not match for the hypotheses H2a and H5b.

39
The model indicates that relative competitive performance cannot be effectively predicted by
using the variables involved in this study. However objective fulfilment can be effectively
predicted using strategy formulation and strategy implementation. The model also indicates
that strategy formulation has significant positive relationships with clarity in business-level
strategy and strategy implementation. However clarity in business-level strategy does not
predict either of the performance indicator or the strategy implementation.
Summary of Variables assessed using Partial Least Squares as shown below:
Cost-related Strategy Composite Reliability = 0.872, A V E = 0.534)
Differentiation Composite Reliability = 0.841, A V E = 0.520)
Strategy Formulation in the Food Manufacturing Industry Composite Reliability = 0.884,
AVE = 0.526)
Strategy Implementation Composite Reliability = 0.926, A V E = 0.609
Relative Competitive Performance Composite Reliability = 0.930, A V E = 0.602
Objective Fulfilment Composite Reliability = 0.815, A V E = 0.527
16. MAJOR FINDINGS
Path analysis and Partial Least Squares (PLS) was used to test the hypotheses. Summary and
results from testing the hypotheses are presented in Table 16.1.
Table 16.1: Summary of the Results Obtained by Testing the Hypotheses
Hypotheses Result
H1a: Rational-comprehensive strategy formulation will lead to superior
performance in food manufacturing organisations in Zimbabwe.
Supported
H1b: Environmental dynamism and hostility moderate the relationship
between strategy formulation and organisational competitive
implementation performance
Partially
supported
H2a: Organisations in the food manufacturing industry having a clear
business-level strategy by adopting one of the strategies namely cost-
related, differentiation or integrated strategies will perform better than
Supported

40
those organisations which are stuck-in-the-middle
H2b: Organisations in the food manufacturing industries in Zimbabwe
following integrated strategies will perform better than those pursuing
either a cost-related strategy or a differentiation strategy
Partially
supported
H2c: Environmental dynamism and hostility moderate the relationship
between business-level strategy and strategy implementation performance
Partially
supported
H2d: Organisational structure moderates the relationship
between business-level strategy and competitive strategy implementation
performance
Not supported
H3: Organisations in the food manufacturing industries placing a strong
emphasis on strategy formulation will develop a clear business-level
strategy by adopting one of the strategies namely cost-related,
differentiation or integrated strategies
Supported
H4: The degree of formulation of strategy implementation has a
significant positive impact on organisational competitive performance in
the food manufacturing industry in Zimbabwe
Partially
supported
H5a: Organisations in the food manufacturing industries in Zimbabwe
placing a strong emphasis on strategy formulation will also place a strong
emphasis on the formulation of competitive strategy implementation
Supported
H5b: Organisations in the food manufacturing industries in Zimbabwe
having a clear strategy by adopting one of the business-level strategies
namely cost-related, differentiation or integrated strategies will give more
emphasis to
strategy implementation than those organisations which are stuck in-
the-middle
Supported
Summary of the Findings by Testing the Hypotheses

41
The hypotheses presented in chapter 1 were tested using various statistical techniques as
explained in successive chapters. To aid discussion of the results here, these hypotheses are
grouped into three categories. Hypotheses concerning the relationship between strategy
formulation and performance belong to the food manufacturing industries in Zimbabwe and
those examining the relationship between business-level strategy and other variables belong
to the food manufacturing industry in the SADC region. The third group includes hypotheses
inquiring into the relationship between strategy implementation and other variables.
16.1a Strategy Formulation and Implementation
The following hypotheses examining the relationship between strategy formulation and
implementation in the food manufacturing industry in Zimbabwe were tested:
H1a: Rational-comprehensive strategy formulation will lead to superior implementation in
organisations.
H1b: Environmental dynamism and hostility moderate the relationship between
Strategy formulation and implementation.
i) It was found that strategy formulation in the food manufacturing industry in
Zimbabwe is significantly related to both the strategy implementation measures and
hence hypothesis H l a is supported. This finding agrees with the findings of many
previous studies by first mover scholars acknowledged. While strategy formulation in
Zimbabwe‘s food manufacturing industries is strongly related to objective fulfilment,
its relationship with relative competitive strategy implementation is not very strong.
This indicates that even though strategy formulation helps organisations to achieve its
set objectives, it does not make a huge contribution towards improving organisational
strategy implementation in comparison to its main competitors.
ii) Hypothesis H1b tested using moderated regression analysis, indicated that
environmental dynamism and hostility moderate the relationship between strategy
formulation in the food manufacturing industries in Zimbabwe and relative
competitive strategy implementation. However, they do not moderate its relationship
with objective fulfilment. Hence hypothesis Hlb is partially supported.
iii) It was found that strategy formulation helps organisations to improve its relative
competitive strategy implementation in highly dynamic environments. This finding
confirms the findings of some previous studies (e.g. Miller & Friesen, 1983;
Eisenhardt, 1989; Judge & Miller, 1991; Göll & Rasheed, 1997) which suggested that
strategy formulation is helpful in dynamic environments. It contradicts the findings of

42
other studies (e.g. Fredrickson, 1984; Fredrickson & Mitchell, 1984) which found that
strategy formulation is harmful in dynamic environments. The results of the analysis
also indicated that strategy formulation in food manufacturing industries is strongly
associated with relative competitive strategy implementation in highly hostile
environments such as in Zimbabwe.
iv) Göll & Rasheed (1997) had found that strategy formulation is helpful in highly
munificent environments and harmful in environments with low munificence.
Environments with low munificence are characterised as highly hostile environments
and hence there is a disagreement between the findings of this study and that of Göll
& Rasheed (1997). The results taken together indicate that strategy formulation helps
organisations to improve their implementation performance. Even though scholars
like Mintzberg (1994) have argued that strategy formulation has lost its relevance, the
findings of this study indicates a significant positive relationship between strategy
formulation and organizational
v) Implementation performance. It was also found that strategy formulation is helpful in
dynamic as well as hostile environments and this provides further support for strategy
formulation. Dynamic environments emphasise growth through technology
development and innovation as depicted in the conceptual formulation in Chapter 1.
In such environments there is an overload of information and conflict between
situations. Strategy formulation helps organisations to process information using
analytical tools and arrive at consensus through participative decision-making. In
hostile environments like what has prevailed in Zimbabwe, particularly in affecting
the food manufacturing industry in the period between 2006 and 2013, the
surrounding factors are less favourable and the activities of competitors are
belligerent. Strategy formulation helps firms to identify the threats arising out of these
unfavourable factors through systematic analysis resulting in improved strategy
implementation performance.
16.2 Business-level Strategy
 Hypotheses H2a, H2b, H2c and H2d examining the relationship between business-
level strategy formulation and implementation performance and hypothesis H3
examining the relationship between strategy formulation and business-level strategy
implementation are discussed in this section.
16.3.1 Business-level Strategy and Performance

43
H2a: Organisations in the Zimbabwe’s food manufacturing industry having a clear business-
level strategy formulated by adopting one of the strategies namely cost-related,
differentiation or integrated strategies will perform better than those organisations which are
stuck-in-the-middle.
H2b: Organisations following integrated strategies will perform better than those pursuing
either a cost-related strategy or a differentiation strategy.
i) It was found that organisations in the food manufacturing industries in Zimbabwe
having a clear business-level strategy (cost-related, differentiation or integrated
strategies) performed better than stuck-in-the-middle companies both in terms of
objective fulfilment and relative competitive implementation performance.
ii) As indicated earlier stuck-in-the-middle companies are defined as those firms which
do not have a dominant strategy formulation orientation. Hence hypothesis H2a is
supported. This finding conforms to the findings of many other studies (e.g. Dess &
Davis, 1984; O'Farrell, Hitchens & Moffat, 1992) which have examined this
relationship in previous studies.
iii) It was found that organisations in the food manufacturing industries in Zimbabwe
adopting an integrated strategy formulation and implementation performed better than
those firms using only one type of strategy, both in terms of objective fulfilment and
relative competitive strategy implementation performance. However, this difference
was not statistically significant. Hence hypothesis H2b is partially supported. This
finding conforms to the findings of some other studies (e.g. Wright et al, 1991; Chan
& Wong, 1999) and contradicts with some others (e.g. Kumar, Subramanian &
Yauger, 1997) which found that firms using integrated strategies performed poorly.
iv) The findings of this study indicate the relevance of Porter's (1980) typologies for
explaining implementation performance heterogeneity among food manufacturing
firms. Moreover, it highlights the importance of having a clear strategy for
organisations. The effectiveness of combination strategies in enhancing organisational
performance in the food manufacturing industries has been proved in this study. The
findings remind the practicing managers about the dangers associated with a stuck-in-
the-middle state. For achieving superior performance, organisations in the food
manufacturing industries in Zimbabwe need to give emphasis to one of the following
tasks while carrying out the activities in the value chain: (i) minimise the operational
costs to achieve a low-cost position in their industry OR (ii) produce a product with

44
differentiated features and give emphasis to innovation, marketing and customer
service OR (iii) carry out the activities outlined in both (i) and (ii).
16.3.2 The Moderating Effect of Environment in Zimbabwe’s Food Manufacturing
Industry
H2c: Environmental dynamism and hostility moderate the relationship between
business-level strategy formulation and organisational implementation performance.
i) The moderating effect of environmental dynamism and hostility on the relationship
between business-level strategy formulation and implementation performance was
assessed. It was found that there is a moderating effect to some extent. Environmental
hostility in Zimbabwe‘s food manufacturing industry acts as a moderator in the
following relationships:
• Cost-related Strategy - Objective Fulfilment;
• Cost-related Strategy - Relative Competitive Performance; and
• Differentiation - Relative Competitive Performance.
ii) It was found that in environments with low levels of hostility, cost-related strategy
leads to better strategy implementation performance. However, a differentiation
strategy formulation can help organisations in the food manufacturing industries in
improving their relative competitive strategy implementation performance in highly
hostile environments like in Zimbabwe (2006 - 2013. It was also found that
environmental dynamism moderates the relationship between differentiation and
relative competitive implementation performance. In highly dynamic environments a
differentiation strategy helps organisations to improve their relative competitive
performance. The findings provide support for contingency theory, that is to say,
superior implementation performance is the result of aligning strategy with
environmental conditions.
iii) The results support the findings of some previous studies which have found the
moderating effect of environment on the relationship between business-level strategy
formulation in the manufacturing industries and implementation performance (e.g.
Prescott, 1986; Lee & Miller, 1996). This finding is important to practicing managers.
It indicates the usefulness of a cost-related strategy in environments with low levels of
hostility. However in highly hostile environments, this strategy may not be helpful
and a differentiation strategy seems to be appropriate for improving relative

45
competitive implementation performance. Similarly in highly dynamic environments
a differentiation strategy is useful for improving relative competitive performance.
16.3.3 The Role of Organisational Structure in Zimbabwe’s Food Manufacturing
Industry
H2d: Organisational structure moderates the relationship between business-level strategy
formulation and organisational strategy implementation performance.
i) The evidence does not support the proposition that organisational structure moderates
the relationship between business-level strategy formulation and implementation
performance. However, the results indicated a significant role played by organic
structure in this relationship. It was found that within the group of organisations in the
food manufacturing industry in Zimbabwe adopting a clear strategy formulation (cost-
related, differentiation or integrated strategy); those having organic structure perform
better than those firms which have a mechanistic structure. It was also found that
firms employing integrated strategies and having an organic structure had the highest
level of implementation performance.
ii) This finding is interesting and practicing managers will find it useful. Organisations
adopting either a differentiation strategy or an integrated strategy will need to promote
innovation to a great extent. Implementation of an integrated strategy demands
facilitation of two key operational activities within the organisation: (i) striving for
controlling the operational costs while carrying out the primary and supporting
activities in the value chain and (ii) endeavouring to produce a high quality product
with differentiated features and giving high emphasis to innovation, marketing and
customer service. Focussing on these two activities simultaneously requires a
tremendous amount of flexibility within the organisation. A mechanistic structure
giving emphasis to formal rules and procedures may not be helpful for carrying out
these two activities simultaneously. Similarly a mechanistic structure does not
promote innovation. The results of this study confirm that an organic structure is
appropriate for implementing either a differentiation strategy or an integrated strategy.
16.3.4 Strategy Formulation and Business-level Strategy Implementation
H3: Organisations placing a strong emphasis on strategy formulation will develop a clear
business-level strategy implementation by adopting one of the strategies namely cost-related,
differentiation or integrated strategies.

46
i) The relationship between strategy formulation and business-level strategy
implementation was examined by testing hypothesis H3. The findings of the logistic
regression analysis indicated that strategy formulation significantly increased the
probability of having a clear implementation strategy for an organisation. This finding
establishes the link between strategy formulation and business-level implementation
strategy. This relationship has not been examined in the previous studies and hence
this finding is important. The findings of H l a and H2a suggest that both strategy
formulation and clarity in business-level implementation strategy help organisations
to improve their performance. Since strategy formulation helps organisations to
clearly define their business-level strategy CEOs and senior managers need to give
proper emphasis to strategy formulation in their organisations.
16.4 Strategy Implementation
 The results obtained by testing hypotheses H4, H5a and H5b are examined in this
section. H4 examines the impact of formulation of strategy implementation on
performance, H5a looks into the relationship between strategy formulation and
strategy implementation and H5b assesses the relationship between clarity in
business-level strategy formulation and planning of strategy implementation.
16.4.1 Strategy Implementation and Competitive Performance in the Food
Manufacturing Industry
H4: The degree of formulation of strategy implementation has a significant positive impact
on food manufacturing industry performance
 The relationship between formulation of strategy implementation and both the
competitive performance measures were statistically significant. However, the
strength of this relationship is much higher in the case of objective fulfilment. Even
though its relationship with relative competitive performance is statistically
significant, the regression results indicate that the R value is very low. Hence
hypothesis H4 is partially supported indicating that emphasis on strategy
implementation helps organisations in the food manufacturing industries to improve
their performance. This finding is important because this relationship has not been
examined by previous studies. Some of the previous studies have found that many
strategic decisions failed because of ineffective implementation. They emphasised the
need to properly plan and prioritise strategy implementation. The result obtained by

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