Environmental Dynamism On The Effectiveness Of Sisp Accounting Essay

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External environment and strategic information systems planning (SISP) have received significant scholarly attention in the past two decades. The previous researches identify the competitive pressure of the external environment as an important facilitator for SISP use (Teo and King, 1997).The importance of SISP has increased in relevance among information systems researchers and practitioner and it remains as one of the top issues in information systems area. In today's dynamic market environment, business success relies heavily on the effectiveness of SISP, which is the first stage of IS planning model. According to Bechor, Seev, Moshe and Glezer (2010) SISP refers to the process of strategic thinking that identifies the most desirable IS on which the firm can implement and enforce its long-term IT activities and policies. It is a mechanism for assuring that IS activities are aligned with the organisation's evolving needs and strategies (Bechor et al., 2010; Sabherwal and Chau, 2001).

There are many different ways of defining small, micro and medium enterprises (SMMEs), various from size to revenue. The present study has been conducted within the South African context, the appropriate strategy here would be to adopt the definition provided by the National Small Business Act of 1996, as amended by Act 26 of 2003, which defines SMME as: "Any entity, whether or not incorporated or registered under any law, consisting mainly of persons carrying on small enterprise concerns in any economic sector and established for the purpose of promoting the interests of or representing small enterprise concerns, and includes any federation consisting wholly or partly of such association and organisation". From that definition the South Africa SMME sector is classified in four categories respectively: survivalist enterprise, micro enterprise, small enterprise and medium enterprise.

Small, micro and medium enterprises (SMMEs) represent an important vehicle to address the challenges of job creation, economic growth and equity in South Africa. SMMEs play a critical role in absorbing labour, penetrating new markets and generally expanding economies in creative and innovative ways provided an appropriate enabling environment is created (South Africa, 1995). According to Le Roux (2006), South Africa's 2 million SMMEs represent 98% of the country's total number of firms, employ 55% of the labour force and contribute 42% of the country's wage bill. From these statistics manufacturing SMMEs remains an important sector contributing 18.6% to Gross Domestic Product (GDP), and employing more than one million people (South African, 2008).

The organisation target of the present study was the medium enterprises, it have been described as the largest of the SMMEs. It is owner controlled, the ownership and management structure is more complex and it employs a maximum of between 100 and 200 people (South Africa, 2008).

The purposes of this study are, firstly to investigate if environmental dynamism will be more influential to SISPP Phases in manufacturing enterprises compared with non-manufacturing enterprises. Secondly, to examine the relationship between strategic information systems planning process (SISPP) phases and the success of SISPS in manufacturing enterprises and in non-manufacturing enterprises. And thirdly, to examine empirically if the presence of dynamic environment can strongly moderate the relationship between strategic information systems planning process (SISPP) phases and strategic information systems planning success (SISPS) in both enterprises. To describe the outcomes of this research, this paper is organised in the following way. The next section, describe the theoretical foundations of research variables and research hypotheses. Following that, there is a section describing the research process and the methods employed. The analysis of the data together with a discussion of the results, conclusions and implications of this research are discussed in the last section.

THEORETICAL PERSPECTIVES, RESEARCH VARIABLES AND RESEARCH HYPOTHESES

Theoretical perspectives

Previous IS researchers have found out that external environment defy today's business managers. It forces them to be more careful strategic planners (Newkirk and Lederer, 2007). Many authors contend that it is under pressure of external environment that strategic planning could come to the fore. Supported by the information uncertainty perspective, they argue that external environment increases the need for information gathering and therefore SISP (Cohen, 2001). SISP can be used to reduce uncertainty, and is increasingly recognised as a necessity for organisations to survive and be able to tackle uncertainty quickly and robustly in order to sustain and enhance business competitiveness (Brown, 2008).

Sabherwal and King (1992) suggested that more extensive SISP would be more successful, because it would help planners understand the impact of the external environment and better respond to it. Teo and King (1997) identified the competitive pressure of the uncertain environment as an important facilitator for SISP use. Hopkins and Hopkins (1997) found that environmental factors emerged as a more influential determinant of SISP. Choe et al. (1998) empirically showed a positive relationship between perceived environmental uncertainty and SISP. Grover and Lederer (1999) studied the influence of environmental uncertainty on the strategic use of information systems and found out that environmental uncertainty is an important predictor of SISP practices.

The present research contained one independent variable: Strategic Information Systems Planning Process (SISPP) with five phases namely: strategic awareness, situation analysis, strategy conception, strategy formulation and strategy implementation. One dependent variable: Strategic Information Systems Planning Success (SISPS) with four dimensions, namely: alignment, analysis, cooperation and improvement in capabilities. And one moderated variable: external environment characterised on the purpose of the present study by the environmental dynamism.

2.2. Research variables

Strategic Information Systems Planning Process (SISPP)

SISPP has been the core of much interest in the previous SISP literature but there is no agreement about what the formal methodology is. Mirchandani and Lederer (2008) stated that there was no industry standard for SISP approaches, as organisations, possibly with the help of external consultants, developed their own in-house approaches. Whatever approach or combination of approaches is chosen, it will then have to be adapted to suit the environment, culture, experience and skills existing within the organisation.

SISPP, has been defined in the context of the current research as a process of investigating external and internal organisation's environments for the aim of positioning information systems in relation to the business. Issues and opportunities identified in this assessment should result in generating strategic directions of future information systems investments (Zijad, 2007).

Previous studies have developed and used SISPP model which aim to increase the practical usefulness of information systems (IS) planning within organisations. This SISPP model contained three process elements, namely: phases, stages, and modules. The phases are generic strategy formulation steps that can be applied to any corporate strategy development process. There are five phases in SISPP model which are: strategic awareness, situation analysis, strategy conception, strategy formulation and strategy implementation. Each phase is divided into stages. Stages are considered to be semi-autonomous components of work which can be planned relatively independently. Stages are further divided into modules. Modules can either be units of work or collections of activities (Musangu and Kekwaletswe, 2011; Newkirk and Lederer, 2006; Menzas, 1997).

The first phase of SISPP model called strategic awareness has for purpose to formulate major questions and provide answers relatively to the organisation and its competition. The situation analysis is the second phase its goal is to examine the existing business and IS situation in the organisation and identifies the specific strengths and weaknesses. The third phase is strategy conception, in this phase the IT purposes, opportunities for improvement and the important IT strategies are identified. The fourth phase, strategy formulation clarifies new business processes, new IT architectures, specific new projects and the priorities for the new projects in term of the functions, hierarchies and responsibilities. Final phase is called strategy implementation, in this phase the management approach, action plan, follow-up and control procedure are describing in order to monitor and control the cost and to manage the implementation process (Newkirk and Lederer, 2007; Mentzas, 1997).

The extent to which an organisation can carry out each phase and task have used to assess the SISPP.

Strategic Information Systems Planning Success (SISPS)

The success of SISP has been operationalised in terms of the achievement of organization planning objectives as either a single or multi-factor construct (Mirchandani and Lederer, 2008; Segars and Grover, 1999; Raghunathan and Raghunathan, 1994).

According to Segars and Grover (1998) the assessment of SISPS cannot be reduced to such simple financial measures as return on investment, payback or internal rate of return. In this context, they built an instrument and empirically verified a second-order model based on these two perspectives for SISP success. Their instrument used four dimensions to measure SISPS, namely: alignment, analysis, cooperation and improvement in capabilities.

Alignment dimension was described as the linkage between IS strategy and business strategy. Its make easy purchasing and deployment of information technology that is in accordance with the organisation' competitive rather than existing patterns of usage within the organisation (Grover and Segars, 2005). Analysis dimension has been described as the understanding of internal operations of the organisation in terms of processes, procedures and technologies (Newkirk, Lederer and Srinivasan, 2003). Cooperation dimension has been identified as the agreement between managers and users concerning development priorities, implementation schedules and managerial responsibilities. The purpose of cooperation is to avoid conflict which may destroy the implementation of strategic IS plan (Newkirk and Lederer, 2007; Grover and Segars, 2005). The last dimension was capabilities its has been described as the improvement in the potential of the planning system. An effective SISP should have a high perceived level of contribution to various aspects of organisational effectiveness (Newkirk and Lederer, 2007; Grover and Segars, 2005; Newkirk, Lederer and Srinivasan, 2003).

These four SISPS dimensions have been used to assess the SISPS in this research.

External Environment

External environment has been defined as physical and social determinants outside the boundaries of the organisation those are taken directly into consideration (Chi, Jones, Lederer, Li, Newkirk and Sethi, 2005). External environment is an important concept in the SISP research but only little study has been conducted to investigate the influence of external environment on SISP (Brown, 2008). Almost of previous external environment and SISP study have integrated it stability aspect or environment uncertainty

Environmental uncertainty is defined as the frequent and unpredictable changes in customer preference, technological development and competitive behaviour perceived by managers (Lin and Ho, 2010). It has regarded as the most important factor influencing manager decision making. Teo and King (1997) characterised environmental uncertainty by the presence of environmental dynamism, environmental heterogeneity and environmental hostility.

For the purpose of this paper external environment is characterised by the presence of environmental dynamism. All organisations operate in dynamic market and in most of time the markets realities are quickly become obsolete (Cohen, 2008). Taking into account of that dynamic aspect the environmental dynamism has been characterised by the rate of change and innovation in the industry, as well as the unpredictability of the actions of competitors and customers (Lederer and Sethi, 1998). Teo and King (1997) found out that environmental dynamism was associated with greater levels of integration between business planning and SISP. Greater dynamism requires higher levels of cooperation and coordination between business and IS (Brown, 2008; Grover and Segars, 2005).

Sabherwal and King (1992) view dynamism as the unpredictability of the external business environment, as evidenced by change and obsolescence. Dynamism affects the importance of information processing because as environmental dynamism increases, successful firms must make strategic decisions more quickly. Dynamic environments increase the firm's need for information resources which can facilitate inter-organisational linkage by improving information processing capabilities such as the building of a knowledge base, the seeking out of new business opportunities, and the development and management of competitive initiatives (Grover, 1997).

The questionnaire developed and used previously by Teo and King (1997) has been used in this study to measure environmental dynamism.

Hypotheses

It is well known that the unpredictability of environment change create uncertainty, taking in account of fact that environmental uncertainty challenge manager in decision making. Analysis in environmental dynamism might be expected to help manager in getting more knowledge about environmental change. This would make it possible to understand and developed plans that are less vulnerable to consequences of that change (Newkirk and Lederer, 2006).

2.3.1 Environmental dynamism and SISPP

Environmental uncertainty can be measured by the presence of dynamism. Environmental dynamism is characterised by two factors represent two separate constructs. The first factor is mainly concerned with frequent changes in the environment and the second is mainly concerned with the predictability of the environment (Teo, 1994). In environmental dynamism context the manager decision making can be influenced negatively. The competitive market force manufacturing SMMEs to offer an array of new products for purpose to stay competitive in the market. Thus, the use of planning process will be more prevalent in the manufacturing enterprises because of unpredictability of market change than non-manufacturing enterprises. These arguments support the first set of hypotheses:

H1: Environment dynamism will be more strongly influential to SISPP Phases……

H1A: Strategy awareness

H1B: Situation analysis

H1C: Strategic conception

H1D: Strategic formulation

H1E: Strategic implementation

…..in manufacturing SMMEs than in other industries.

2.3.2 SISPP and SISPS

In the context of environmental uncertainty, planning process can cope to the environmental dynamism consequence and lead to the organization success. Thus, the use of planning process can strongly relative to success in manufacturing enterprises than in non-manufacturing enterprises. These arguments support the second set of hypotheses:

H2: Strategy awareness will be strongly relative to SISPS in manufacturing enterprises than in

non-manufacturing enterprises.

H3: Situation analysis will be strongly relative to SISPS in manufacturing enterprises than in

non-manufacturing enterprises.

H4: Strategic conception will be strongly relative to SISPS in manufacturing enterprises than in

non-manufacturing enterprises.

H5: Strategic formulation will be strongly relative to SISPS with in manufacturing enterprises than

in non-manufacturing enterprises.

H6: Strategic implementation will be strongly relative to SISPS in manufacturing enterprises than

in non-manufacturing enterprises.

2.3.3 SISPP and SISPS under Environmental dynamism

In dynamism environment context, manager can use SISP to reduce the rate and unpredictability of environment change. High level of environmental dynamism can increase the likelihood that SMMEs will identify opportunities for using SISP resources (Grover and Lederer, 1999).

According to Newkirk and Lederer (2006) the achievement of SISP in environmental dynamism is critical to planners. Analysis in dynamism environment might be expected to produce greater knowledge about competitors, resources, customers and regulators. Thus, the presence of environmental dynamism can strongly moderate the relationship of SISPP phases to success in manufacturing enterprises than in non-manufacturing enterprises. These arguments support the second set of hypotheses:

H7: Environmental dynamism will strongly moderate the association between strategy

awareness and SISPS in manufacturing enterprises than in non-manufacturing enterprises.

H8: Environmental dynamism will strongly moderate the association between situation analysis

and SISPS in manufacturing enterprises than in non-manufacturing enterprises.

H9: Environmental dynamism will strongly moderate the association between strategic

conception and SISPS in manufacturing enterprises than in non-manufacturing enterprises.

H10: Environmental dynamism will strongly moderate the association between strategic

formulation and SISPS in manufacturing enterprises than in non-manufacturing enterprises.

H11: Environmental dynamism will strongly moderate the association between strategic

implementation and SISPS in manufacturing enterprises than in non-manufacturing

RESEARCH METHODOLOGY

The instrument

Demographic characteristics were measured by means of demographic information (DI), which were included individual factors such as gender, age, educational level, IS experience, SISP experience, duration of employment with the current SMMEs, scope of SISP, planning horizons, IS employees, SMMEs primary industry and SMME's size.

The measuring instruments used in this study have been used in the previous studies (e.g., Mirchandani and Lederer, 2008; Newkirk and Lederer, 2007; 2006, Newkirk, 2001; Mirchandani, 2000; Segars and Grover, 1998, Teo and King, 1997 and Mentzas, 1997).

The above researchers used the questionnaire instrument, which consists of five-point Likert-scales, in order to operationalise the following three constructs: SISPP, SISPS and environmental dynamism

Sampling frame and sampling procedure

The sampling frame adopted was the 2009 edition of "Who Owns Whom in South Africa", published by McGregor. This directory contains the names, titles, addresses of top computer executives in South Africa. The entities within the directory include small enterprises, micro enterprises, medium enterprises, large firms, educational institutions, hospitals and governmental agencies.

In developing a desirable sub frame, (i) all large firms, hospitals, educational institutions and governmental agencies were eliminated from consideration; (ii) the job titles of key informants remaining in the frame were examined as a means of determining the level of planning activity; (iii) medium enterprises with a senior executive carrying the job title of chief information officer, vice president, director of strategic planning, director of MIS or head of IS/IT establish in Gauteng province were retained. This resultant sub frame contained 518 SMMEs. From this frame 350 SMMEs were chosen at random.

Data collection

A questionnaire was mailed out to 350 CIOs, information systems managers or head of information systems in medium enterprises established in South Africa Gauteng province. Of the 350, 92 keys informant returned the survey. Out of the total returned (92), 73 were usable for analysis and 19 were not. In addition, a total of 48 surveys returned during the follow-up, 45 were usable for analysis and 3 were not. On the whole, a total of 140 responses have been received from both the initial and follow-up mailing, 118 were usable for analysis but 22 were not. Of the total 22 responses found unusable for analysis, 13 were discarded from analysis because some questions were not completed, 2 respondents returned with notes that their organisations do not participate in surveys and 7 returned with notes that their organisations were not using SISP. Thus, the gross responses rate of the research survey was 40 %, of which, 118 returns i.e., 34% were suitable for analysis. The gross response rate and usable response rate received for the present study is quite high compared with previous SISP studies conducted previously (Mirchandani and Lederer, 2008; Newkirk and Lederer, 2007; 2006; Chi et al., 2005; Vedabrata et al., 2002; Kunnathur and Zhengzhong, 2001)

DATA ANALYSIS

Common method variance, response bias, reliability and validity of research variables

The returned surveys were examined for non-response bias to confirm that the decision to respond was uninfluenced by non-random events or motives. If the decision to respond is random, then the timing of the response should not significantly influence the value of survey measures (Kerlinger, 1986). Multivariate analysis of variance was used to evaluate whether differences among early and late responders were associated with different responses. The analysis indicated no significant differences in several key variables tested for the surveys. This is consistent with the absence of non response bias in the surveys.

Since dependent and independent variable data was collected from a single key informant (head of IS/IT). The head of IS/IT is typically seen as the most knowledgeable person to assess SISP, its context, and its outcomes (Premkumar and King, 1992). However, multiple subjects per organization are preferred in order to reduce common method variance, which arises from using one individual and can account for a relationship between similar measures (Newkirk and Lederer, 2006; Podsakoff and Organ, 1986).

Harman's one factor test was used to test for the presence of common method variance bias. The results of this analysis on our data revealed 9 factors with an Eigen value greater than one and no single factor explained most of the variance. Such results are consistent with the absence of a significant variance common to the measures.

In order to assess the reliability of all research variables measures, the internal consistency was calculated using Cronbach's alpha which indicated the degree of internal consistency among the measurement items and is inversely related to the degree to which a measure is contaminated by random errors (Wang and Tai, 2003). As provided in table 1, the results in the present research indicate that all research variables constructs have an acceptable Cronbach's alpha level.

Table 1 Reliability coefficient of research variables

Variable

Number of items

Cronbach's alpha

SISPP

Strategic awareness

Situation analysis

Strategy conception

Strategy formulation

Strategy implementation

SISPS

Alignment

Analysis

Cooperation

Capabilities

ENVIRONMENT DYNAMISM

26

5

6

4

5

5

30

8

8

7

7

4

.76

.70

.79

.75

.82

.82

.87

.80

.87

.82

.86

.78

Profile of respondents

Responses for demographics data are provided in tables 2 to 10 for both manufacturing and non manufacturing medium enterprises. Responses were presented by frequency and percentage to measure the following responses: gender, age of respondent, education level, information systems experience, SISP experience, employment with the current enterprise, scope of SISP, planning horizon and information systems employees.

The frequency and percentage of respondent gender are given in table 2. From this table 14% of respondent were female and 86% were male in the manufacturing enterprises whereas 29% were female and 71% were male in the non-manufacturing enterprises

Table 2 Gender

Gender

Non Manufacture

Manufacture

Freq

%

Freq

Female

26

29

4

Male

64

71

24

Total

90

100

28

The mode of respondent age was between 36 and 45 years for the both categories, such as presented in table 3 below.

Table 3 Age of respondent

Years

Non Manufacture

Manufacture

Freq

%

Freq

26 - 35

12

13

0

36 - 45

47

52

21

46 - 55

28

31

5

Over 55

3

4

2

Total

109

100

28

The results provided in the table 4 shown that most of respondent had a postgraduate degree in both enterprises following by some postgraduate school in manufacturing and 2 years college in non-manufacturing enterprises.

Table 4 Education level

Education

Non Manufacture

Manufacture

Freq

%

Freq

Some college

1

1

0

2 years college

14

16

5

4 years college

9

10

2

Some postgraduate school

3

3

8

Postgraduate degree

51

56

10

Other

12

14

3

Total

90

100

28

The information systems experience was higher for non-manufacturing enterprises IS executives than for their counterparts in manufacturing enterprises. Table 5 below presented IS experience results.

Table 5 IS experience

Years

Non Manufacture

Manufacture

Freq

%

Freq

6 - 10

17

19

0

11 - 15

22

24

14

16 - 20

35

39

6

21 or more

16

18

8

Total

90

100

28

The SISP experience was not differing for manufacturing and non-manufacturing enterprises. More than 80% of respondents had a SISP experience ranged between 1 to 10 years. Only 3% had SISP experience over 11. Table 6 below presents the breakdown of the SISP experience.

Table 6 SISP experience

Years

Non Manufacture

Manufacture

Freq

%

Freq

0 - 5

44

49

19

6 - 10

41

46

7

11 - 15

3

3

1

21 or more

2

2

1

Total

90

100

28

The results in table 7 shows higher employ stability in manufacturing enterprises than in non-manufacturing. 43% of manufacturing respondents were employed in the current enterprise for a period ranged between 11 and 15 years whereas 39% were employed in non-manufacturing for a period between 6 and 10 years.

Table7 Employment SMMEs

Years

Non Manufacture

Manufacture

Freq

%

Freq

0 - 5

25

28

10

6 - 10

39

43

6

11 - 15

22

24

12

16 - 20

4

5

0

Total

90

100

28

Enterprise was a SISP scope for 96% of manufacturing and 70% of non-manufacturing. Table 8 below provides the breakdown of the scope of SISP results.

Table 8 Scope of SISP

Scope

Non Manufacture

Manufacture

Freq

%

Freq

Function

2

2

0

Division

15

17

1

Enterprise

63

70

27

No response

10

11

0

Total

90

100

28

The planning horizon was normally distributed for the two samples with 71% of manufacturing using 3 years planning horizon and 52% of non-manufacturing in the same level.

Table 9 Planning horizon

Horizon

Non Manufacture

Manufacture

Freq

%

Freq

1 year

1

1

0

2 years

8

9

2

3 years

47

52

20

4 years

15

17

6

More than 5 years

9

10

0

No response

10

11

0

Total

90

100

28

The results provided in table 10 show that more than 70% of enterprise employed less than 10 staff in the IS department in both enterprises.

Table 10 IS employees

Number

Non Manufacture

Manufacture

Freq

%

Freq

Less than 10

65

72

26

10 - 24

17

19

1

25 - 49

6

7

1

50 or more

2

2

0

Total

90

100

28

Comparison of correlations

4.4.1 Environmental dynamism and SISPP

It has found out in the previous studies that the increasing of environmental dynamism influence the enterprises information processing. In the context of high dynamism successful enterprises must make strategic decisions more quickly. Dynamic environments increase the firm's need for information resources which can facilitate inter-organisational linkage by improving information processing capabilities such as the building of planning process, the seeking out of new business opportunities, and the development and management of competitive initiatives (Grover, 1997).

Ten simultaneous multiple regressions examined influence of environmental dynamism on SISPP phases. For each regression, subjects were separated in manufacturing enterprises and non-manufacturing enterprises. The results are breaking down in table 11.

All equations were statistically significant except strategic conception in manufacturing enterprises. The values of were ranged from .063 to .630 for manufacturing enterprises whereas in the non-manufacturing there were ranged from .112 to .269 showing the dynamic environment importance in the SISPP phases.

Table 11 Results of the multiple regressions using environmental dynamism as independent variable

Dependents variables:

SISPP Phases

Independent variables: Environmental dynamism

F

Standardized coefficients

P

beta

t

MANUFACTURING ENTERPRISES (n = 28)

Strategic awareness

.313

2.337

.009**

.613

.565

12.687

Situation analysis

.000

.001

.999

.448

.379

6.493

Strategy conception

-.095

4.457

.652

.063

-.055

.535

Strategy formulation

.134

.732

.471

.281

.191

3.127

Strategy Implementation

.069

.421

.678

.412

.338

5.602

NON-MANUFACTURING ENTERPRISES (n = 90)

Strategic awareness

.346

2.663

.006**

.116

.085

3.757

Situation analysis

.318

2.444

.017*

.112

.081

3.619

Strategy conception

.444

3.517

.001**

.163

.134

5.597

Strategy formulation

.412

3.179

.002**

.153

.123

5.060

Strategy Implementation

.325

2.749

.007**

.269

.243

10.530

Significance at *p<.05, **p<.01, ***p<.001, ****p<.0001

One of the five beta coefficients is significant in the manufacturing enterprises while all five beta coefficients are statistically significant for non-manufacturing enterprises. These results suggest that environmental dynamism is more influential in non-manufacturing enterprises than in manufacturing enterprises.

4.4.2 SISPP and SISPS

The important role of SISPP in the success of SISP has been shown in the previous management information systems researches during the past two decades. The left part of table 12 provides the empirical results of relationship between SISPP phases and SISPS for manufacturing and non-manufacturing enterprises using multiple regressions analysis and SISPP phases as independent variable. All five beta coefficients indicate statistic significance at p < .05 for manufacturing enterprises while four of five beta coefficients are statistically significant at the same p level for non-manufacturing enterprises.

Multiple moderated regressions

To investigating the moderate influence of environmental dynamism in the relationship between SISPP phases and the success of SISP, the multiple moderated regressions in the right part of table 12 were performed.

Two simultaneous moderated regressions equations were carried on to examine the moderated role of environmental dynamism in the relationship between SISPP phases and SISP success. For each equation, subjects were separated in manufacturing enterprises and non-manufacturing enterprises. .

Both equations were statistically significant at p < .0001. The values of for non-manufacturing enterprises are higher than for manufacturing. Four of the five beta coefficients are significant for manufacturing enterprises and only two of the five beta coefficients are significant for non manufacturing enterprises. The results provide in table 12 suggest that environmental dynamism

Table 12 Results of the multiple moderated regressions

Independents variables:

SISPP Phases

Dependent variables: SISPS

Moderated variable:

(SISPP Phases * Environmental Dynamism)

F

Standardized coefficients

Standardized coefficients

beta

t

P

beta

t

P

MANUFACTURING ENTERPRISES (n = 28)

Strategic awareness

.158

2.48

.015*

.143

2.20

.030*

.554

.550

143.97

Situation analysis

.267

3.26

.001**

.167

2.21

.029*

Strategy conception

.247

3.58

.001**

.205

2.91

.004**

Strategy formulation

.281

4.14

.000***

.198

2.85

.005**

Strategy Implementation

.744

11.99

.000***

.104

1.16

.165

NON-MANUFACTURING ENTERPRISES (n = 90)

Strategic awareness

.126

2.08

.040*

.110

1.77

.040*

.612

.605

90.56

Situation analysis

.170

2.02

.046*

.103

1.39

.167

Strategy conception

.163

2.26

.026*

.138

1.97

.011*

Strategy formulation

.110

1.77

.080

.057

.689

.492

Strategy Implementation

.599

8.84

.000***

.065

.772

.441

Significance at *p<.05, **p<.01, ***p<.001, ****p<.0001

moderate more the relationship between SISPP and SISPS in manufacturing enterprises than in non-manufacturing enterprises.

DISCUSSION

This study had three objectives. The first objective was to investigate if environmental dynamism was more influential to SISPP Phases in manufacturing enterprises compared with non-manufacturing enterprises. The second objective was to examine the relationship between strategic information systems planning process (SISPP) phases and to the success of SISPS in manufacturing enterprises and in non-manufacturing enterprises. The third objective was to examine empirically if the presence of dynamic environment can strongly moderate the relationship between strategic information systems planning process (SISPP) phases and strategic information systems planning success (SISPS). The results of hypotheses testing are summarise in table 13. Of the 11 hypotheses, the empirical analysis supported 9 hypotheses (H2, H3, H4, H5, H6, H7, H8, H9 and H10) but 2 were not supported (H1 and H11).

5.1 Environmental dynamism and SISPP phases

The results revealed that environmental dynamism is not more influential of SISPP phases in manufacturing enterprises than in non-manufacturing enterprises. On the surface only one sub-hypothesis strategic awareness phase was statistically significant for the manufacturing enterprises whereas all sub-hypotheses in the non-manufacturing enterprises were statistically significant. These results make hypothesis H1 not supported. Therefore, environmental dynamism is less influential the planning process in manufacturing. This finding is contrary to the theory. In practice manufacturing enterprises are characterised by the high rate of change and innovation in the industry as well as the unpredictability of the actions of competitors and customers (Lederer and Sethi, 1998).

Table 13 Summary of results

HYPOTHESES

MULTIPLE REGRESSIONS

MULTIPLE MODERATED REGRESSION

DECISION

H1

H1A

H1B

H1C

H1D

H1E

NS

Ns

Ns

Ns

Ns

Not supported

Not supported

Not supported

Not supported

Not supported

Not supported

H2

H3

H4

H5

H6

*

**

**

***

***

Supported

Supported

Supported

Supported

Supported

H7

H8

H9

H10

H11

*

*

**

**

ns

Supported

Supported

Supported

Supported

No supported

Significance at *p<.05, **p<.01, ***p<.001, ****p<.0001

5.2 SISPP Phases and the success of SISP

The results provided in the left part of table 12 shown that all beta coefficients were statistically significant for manufacturing enterprises and four of five betas were significant in non-manufacturing enterprises. These results make supported hypotheses H2, H3, H4, H5 and H6. The implementation of planning process is an important predictor for success of SISP in manufacturing enterprises than in non-manufacturing. In the purpose to gain competitive advantage in the market chief executive officer (CEO) and chief information officer (CIO) have to firstly, collaborate in the process of alignment between business strategy and information systems strategy and secondly, be more careful in the implementation of planning process.

5.3. SISPP Phases and the success of SISP upon environmental dynamism

The right part of table 12 presents the empirical results of examining moderating role of dynamic environment in the relationship between strategic information systems planning process (SISPP) phases and strategic information systems planning success (SISPS). Two moderated regression equations were performed to test the study hypotheses. Of the five manufacturing enterprises hypotheses four were statistically significant and one not. Whereas, two were statistically significant in the non-manufacturing enterprises and three were not. These results make supported hypotheses H7, H8, H9 and H10 while H11 was not supported. It is well know that environmental dynamism and unpredictability of environment change challenge today manager in the making decision process and the use of planning process can reduce dynamic environment impact and leads to success (Newkirk and Lederer, 2006). The results suggest that environmental dynamism influence strongly the relationship between SISPP and SISPS in the following phases: strategic awareness, situation analysis, strategy conception and strategy formulation in the case of manufacturing enterprises.

IMPLICATIONS FOR FUTURE RESEARCH

IMPLICATIONS FOR PRACTICE

LIMITATIONS OF THE STUDY

CONCLUSION

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