Inf Syst E-Bus Manage (2008) 6:341–360 DOI 10.1007/s10257-007-0075-8 ORIGINAL ARTICLE
A Theory of Constraints approach to interorganizational systems implementation Nitza Geri Æ Niv Ahituv
Published online: 29 November 2007 Ó Springer-Verlag 2007
Abstract Interorganizational systems (IOS) may provide substantial benefits, however many organizations are reluctant to implement them. This empirical research takes a novel approach and develops a model of IOS feasibility, which is based on the Theory of Constraints (TOC). It introduces the notion of maximal infeasibility, which is the highest among the values of five factors: economic infeasibility, organizational infeasibility, technological infeasibility, risks, and lack of financial resources. The highest value was selected because implementation is hindered even if only one of the feasibility requirements is not fulfilled. Data collected from 139 medium and large Israeli business organizations validated the model, and indicated that strategic motivation is the main driving force for an organization to initiate or to join an IOS, while the main barriers are organizational infeasibility issues such as lack of management support or uninterested potential partners. Adopting a TOC approach to IOS implementation may assist organizations to overcome these obstacles and increase the chance of a successful implementation. Keywords Interorganizational systems (IOS) Theory of Constraints (TOC) Information systems adoption and implementation Organizational feasibility of information systems An earlier shorter version of this paper was presented at WEB 2006, a pre-ICIS workshop on e-business, in Milwaukee, WI. N. Geri (&) The Department of Management and Economics, The Open University of Israel, 108 Ravutski Street, P. O. Box 808, Raanana 43107, Israel e-mail:
[email protected] N. Ahituv The Marko and Lucie Chaoul Chair for Studies in Information Evaluation, Academic Director of Netvision Institute for Internet Studies, Faculty of Management, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel e-mail:
[email protected]
123
342
N. Geri, N. Ahituv
1 Introduction Interorganizational systems (IOS) are becoming a competitive necessity due to globalization and the growing importance of business alliances. Since more and more organizations engage in outsourcing and offshoring, either as customers or as suppliers, IOS are essential to coordinate their supply chain. Moreover, technological improvements and enhanced Internet connectivity enable the implementation of a wide variety of IOS, which may provide organizations with substantial benefits (Saeed et al. 2005; Chi et al. 2007). Still, many organizations are disinclined to implement IOS (Chwelos et al. 2001; Borman 2006). Therefore, it is important to examine the motives of joining and using IOS. The issues concerning IOS adoption and usage have been widely studied (Chwelos et al. 2001; Teo et al. 2003), however this research adopts a novel perspective and examines this subject through the lens of the Theory of Constraints (TOC), developed by Goldratt and Cox (1986). In recent years, TOC has gained increasing acceptance among practitioners as well as academics (Rahman 1998; Mabin and Balderstone 2000; Gupta 2003). According to TOC, the strength of a system is measured by its weakest link, which is the system’s constraint. In this study, TOC is used for identifying the constraint, which limits IOS implementation. The main research question is why organizations initiate or join IOS and what factors influence their implementation level. This issue is important since many organizations are compelled to adopt IOS, and a TOC approach may help them focus on the crucial factors, which can increase the chance of a successful implementation. Furthermore, organizations invest in IOS development but use mainly their simple functions and do not fully utilize their potential. The findings and insights of this research may help managers to improve IOS implementation and increase their contribution to value creation. IOS is broadly defined in this research as ‘‘an automated information system shared by two or more organizations’’ (Cash and Konsynski 1985; Johnston and Vitale 1988; Neumann 1994). Therefore, this study adopts the same approach as Saeed et al. (2005) and it concerns all sorts of IOS such as Electronic Data Interchange (EDI), Business-to-Business (B2B) e-commerce, extranet and electronic marketplaces. In this paper, the term implementation is used to encompass both adoption and use of IOS. Various models, which dealt with IOS implementation, have been developed. However, these models concerned only certain aspects of IOS adoption or use. Chwelos et al. (2001) checked intent to adopt EDI among non-users and planners. Others dealt only with IOS users (Premkumar et al. 1994; Monczka et al. 1998; Lee et al. 1999; Vlosky et al. 2000). Premkumar et al. (1997) included both users and nonusers, but focused on firms in the trucking industry. Previous research dealt mostly with one specific group, such as purchasing managers (Chwelos et al. 2001), customers (Monczka et al. 1998; Lee et al. 1999), or suppliers (Hart and Saunders 1998). This study addresses a number of related parties: users, planners, and non-users of IOS, while the proposed model examines all the potential IOS connections between an organization and its external environment (i.e., business customers, suppliers, competitors, partners, banks and others). Nevertheless, the main contribution of the study is the application of TOC to the field of IOS
123
A Theory of Constraints approach to interorganizational systems implementation
343
implementation. The most significant aspect of the suggested model is the maximal infeasibility concept, a term developed in this study reflecting the identification of the severest barrier to IOS implementation, i.e., the constraint. The model has been validated through a field survey of Chief Information Officers in 139 medium and large Israeli business organizations.
2 Theoretical background and the suggested model 2.1 The Theory of Constraints The Theory of Constraints claims that the attention of management should be focused on the few constraints, which prevent the organization from achieving its goal. TOC application provided thousands of organizations worldwide with significant performance improvements, such as increased throughput, reduced inventory levels and shorter lead time (Mabin and Balderstone 2000; Ronen 2005). There are many reports of successful TOC implementations mainly from manufacturing organizations, especially in the aerospace, apparel, automotive, electronics, furniture, semiconductor, steel and heavy engineering sectors (Mabin and Balderstone 2003). TOC has also been implemented in diverse non-manufacturing industries, including financial institutions, enterprise software (Ioannou and Papadoyiannis 2004), health services (Ronen et al. 2006), the public sector (Shoemaker and Reid 2005) and in education (Goldratt and Weiss 2005). Goldratt (1991) has initially defined the five focusing steps of TOC for maximizing the performance of a system (see steps 3–7 below). Ronen and Spector (1992) enhanced the process by adding two preliminary steps (see steps 1–2 below). These two steps are particularly important regarding sub-systems such as business units that each one of them is considered a separate profit center, or in situations of dynamic constraints when the binding constraint changes over time. Therefore, the seven focusing steps are (Ronen et al. 2001): 1. 2. 3. 4. 5. 6. 7.
Define the system’s goal. Determine global performance measures. Identify the system’s constraints. Decide how to exploit the system’s constraint. Subordinate the system to the constraint. Elevate the system’s constraint. If a constraint has been broken in the previous steps, go back to step 3. Do not let inertia become the system’s constraint.
2.2 The IOS implementation status model Grounded on TOC, this study develops an IOS implementation status model, which explains differences in IOS usage among firms, and is presented in Fig. 1. The goal
123
344
N. Geri, N. Ahituv
Perceived Potential Strategic Benefits
+ H1
Perceived Potential Transactional Benefits Economic Infeasibility
Power Position of Initiator
Organizational Infeasibility Technological Infeasibility Risks
H2
+ H3 -
MAX Maximal Infeasibility
Lack of Financial Resources
IOS Implementation Status
H4
Industry IOS Status
Organization Size
CONTROL VARIABLES
Fig. 1 The IOS implementation status model
of a business organization is to increase shareholder value, or as Goldratt and Cox (1986) phrase it: ‘‘make more money now and in the future’’. The basic assumption of this study is that IOS utilization helps organizations achieve this goal, and therefore, the appropriate performance measure should be the IOS implementation status. The following model deals with TOC’s third stage and identifies the system’s constraints.
2.2.1 Perceived potential benefits of IOS IOS may provide organizations with many benefits, and as Chwelos et al. (2001) found, higher perceived benefits (Ahituv 1989) lead to greater intent to adopt IOS. From a TOC point of view, IOS implementation is just one option among many others that an organization may choose to create value. However, since the organization resources, and especially management attention, are limited, the organization will focus on the options that are supposed to make the greatest contribution. Therefore, higher perceived potential benefits of IOS should lead to higher levels of IOS implementation. Yet, the question is how these benefits should be defined. Chwelos et al.’s (2001) 17-item construct included both transactional benefits (e.g., reduced errors) and strategic benefits (e.g., enhanced ability to compete). A different approach was taken by Mirani and Lederer (1998) who studied the organizational benefits of information systems projects in general. They adopted the theoretical framework suggested by Turner and Lucas (1985), as extended by Weill (1992), and sorted the benefits into three categories: strategic, transactional and informational. Strategic benefits include enhancing or creating a competitive advantage, avoiding a competitive disadvantage, aligning with the organizational goals, and improvements related to customers, such as better service. Transactional benefits relate to operational efficiency: saving communications costs, improving productivity, and shortening lead times. Informational benefits deal with improving information availability, quality and flexibility. The distinction between strategic
123
A Theory of Constraints approach to interorganizational systems implementation
345
and transactional benefits is important since we hypothesize that even those organizations, which do not use IOS and do not regard them as strategic, are aware of their potential transactional benefits. This awareness is due to the increasing utilization of IOS worldwide. However, we expect that the awareness of IOS users to their potential strategic benefits will be greater than that of non-users. H1: The perceived potential strategic value of IOS positively influences the IOS implementation status index. Although cost reduction may serve as a strong motivation for organizations to implement IOS, that incentive alone is probably not enough to motivate organizations to implement IOS (Markus and Christiaanse 2003). Most organizations may gain substantial cost reductions if they implement IOS. Still, there are many organizations that do not use IOS. Hence, it is likely that other motives are required to trigger IOS use. H2: The perceived potential transactional value of IOS does not affect the IOS implementation status index.
2.2.2 Power position of an initiator Despite the many benefits attributed to IOS, in practice they may be difficult to implement, since they require coordination between independent organizations, which do not govern each other. Social choice researchers (Arrow 1963; Mnookin and Ross 1995) claim that the only analytic solution for a group decision is dictatorship. Moreover, sometimes joining an IOS is apparently against the best interests of an organization because it improves the bargaining power of its trading partners, or increases the threat of existing and potential competitors (Borman 2006). From a TOC perspective, an external pressure of a powerful initiator such as an important customer, may enhance IOS implementation and force the organization to overcome, at least partially, other implementation barriers. This proposition is supported by previous research (Hart and Saunders 1997, 1998; Premkumar et al. 1997; Chwelos et al. 2001; Teo et al. 2003), which found that external pressure of trading partners enhanced IOS implementation. H3: A power position of an initiator positively affects the IOS implementation status index.
2.2.3 Maximal infeasibility The feasibility of an information system is the ability to implement and use it successfully (Ahituv et al. 1994). The three major aspects of feasibility are: economic, organizational, and technological. Previous research measured separately the impact of these and other factors on IOS implementation and on the willingness to adopt IOS (Premkumar et al. 1994; Chwelos et al. 2001). This study has taken a TOC approach and defined a new construct: maximal infeasibility, which negatively affects the IOS implementation status.
123
346
N. Geri, N. Ahituv
Maximal infeasibility is defined as the highest among the values of five factors: economic infeasibility, organizational infeasibility, technological infeasibility, risks, and lack of financial resources. The reason for choosing the highest value is that it is sufficient that only one of the feasibility requirements is not fulfilled, to impede IOS implementation. For instance, suppose that a certain organization may benefit from IOS use and it can obtain the necessary resources. Further, the proposed system is technologically feasible, and its risk level is acceptable. However, the Chief Executive Officer (CEO) does not support the initiative. In this case, the organization will not implement IOS due to organizational infeasibility, which becomes the effective constraint to IOS implementation. We conjecture that the inhibitor of IOS implementation depends on the special circumstances of each organization where the effective constraint should be identified. Maximal infeasibility denotes the factor that is the strongest barrier to IOS implementation. It does not imply that IOS are not used at all by the organization. For example, an organization may use IOS just for issuing or receiving orders because its business partners have requested so, but it may not fulfill the value creation potential of the IOS since the systems are not used for customer service or e-collaboration (Markus and Christiaanse 2003) such as data sharing. The approach suggested here is based on TOC. We regard the maximal infeasibility factor as the constraint, which actually limits IOS implementation. The infeasibility factors are described below and the operationalization of the maximal infeasibility construct is depicted in Sect. 3.2 and Table 4 below. Economic infeasibility: An organization is unlikely to implement an IOS if the estimated costs exceed the expected benefits. Sometimes it is worthwhile to connect just to suppliers, or only to customers, or to a business partner who supplies complementary products. IOS are economically infeasible when it is not worthwhile for an organization to form an IOS with any of its business associates. Organizational infeasibility: A positive attitude of senior management towards IOS is essential for a successful implementation (Armstrong and Sambamurthy 1999). Furthermore, resistance to change may inhibit the implementation of any new system (Rogers 2003). Internally, the organizational culture should support cooperation with external entities. Externally, effective use of IOS requires the acceptance and cooperation of potential partners. Technological infeasibility: An organization needs to have appropriate information, communication and technology (ICT) infrastructure, and its standards must be compatible with those of its partners, to enable IOS implementation. Moreover, in order to fulfill the benefits of IOS, they must integrate with relevant internal information systems. Zhu and Kraemer (2002) highlight the notion of resource complementarity, which means that to gain competitive advantage through IOS, organizations must have complementing resources, such as adequate ICT infrastructure. Risk: The development and implementation of any information system involves certain risks. One aspect of these risks is breaching the security of the transmitted data; another aspect is fear of opportunistic behavior by potential IOS partners.
123
A Theory of Constraints approach to interorganizational systems implementation
347
Although development and implementation risks are not treated directly in this research, they are addressed indirectly through the other feasibility aspects. Lack of financial resources: Sometimes, the organization lacks the required resources for IOS implementation. These are not necessarily financial resources, and may include specific expertise or managerial skills. However, in the current business environment, organizations can use outsourcing to complement their internal resources. Therefore, we define lack of resources as a situation where the organization lacks the necessary financial resources for IOS implementation. In summary, the most influential aspect among the above infeasibility aspects, which may vary in each organization, will determine its ability to implement IOS. H4: Maximal infeasibility is negatively related to the IOS implementation status index.
2.2.4 Control variables Two additional control variables known to positively affect the IOS implementation status were added to the model: Organization size: Larger organizations are considered more capable of adopting innovations (Damanpour 1991), and firm size has been found to have significant influence on IOS adoption (Premkumar et al. 1997; Zhu et al. 2003; Wang et al. 2004). Also, large organizations are more likely to have transactions that suit IOS, at least with some of their trading partners. Industry IOS status: Each industry possesses unique characteristics which may influence the possibilities and the extent of information systems utilization in general and IOS in particular. While in certain industries, like banking or airlines, IOS are considered a strategic necessity, in other industries, their feasibility may be limited for various reasons. Institutional isomorphism (DiMaggio and Powell 1983), which studies the reasons for organizations’ similarity, can explain the impact of an industry IOS implementation level on the IOS implementation status of an organization within that specific industry. A study by Teo et al. (2003) implies that institutional theories may also be applicable to innovations at the early stage of diffusion, such as IOS. Previous research (Crook and Kumar 1998; Chwelos et al. 2001) found that higher levels of industry employment of IOS increased the pressure to adopt IOS, thus this construct is controlled for.
3 Research methodology 3.1 The research population and the sample The IOS implementation status model was empirically tested with data obtained by a mail survey from 139 medium and large Israeli business organizations, which addressed the largest industrial, trade and services companies. Banks and financial institutes were excluded due to the special nature of their operations. The study was aimed at medium and large organizations since it was likely that they would have
123
348
N. Geri, N. Ahituv
the necessary economic, organizational and technological capabilities for IOS implementation, as well as large transaction volume which might economically justify their use. One questionnaire was filled out for each participating organization, preferably by the Chief Information Officer (CIO). In smaller organizations, the survey was directed to the CEO’s asking them to forward it to the appropriate manager. At the beginning of 2001, questionnaires were mailed to 860 organizations. By the end of May 2001, there were 113 replies. Following a reminder, additional 35 responses were received. Altogether, there were 148 answers (17.2%), of which three organizations sent a letter explaining why they believed they should not be included; four incomplete questionnaires were excluded, and two other slightly incomplete questionnaires were used just for the industrial IOS status index. Eventually, the final sample included 139 answers, and the effective response rate was 16.2%. Early respondents were compared to late respondents to check for non-response bias (Armstrong and Overton 1977). This procedure, by which late respondents are supposed to represent nonrespondents, was used in many studies (e.g., Mirani and Lederer 1998). Chi-square tests compared industrial sector distribution, annual revenues and number of employees, resulting in no significant difference between the groups. Moreover, we checked the distribution of IOS use, to ensure the sample was not biased towards users, and again, there was no significant difference.
3.2 Operationalization IOS implementation status index. We drew on Massetti and Zmud’s (1996) theoretical approach to EDI measurement, which is comprised of four facets: volume, diversity, breadth and depth, as a basis for measuring IOS implementation. However, that approach requires an in depth analysis which is more suitable for a case study, or an analysis of a few organizations. Therefore, an index to measure the IOS implementation status, which is appropriate for collecting data from many organizations by a survey, was developed. Table 1 presents the IOS implementation status matrix, which was designed to collect the data on existing and planned IOS Implementations of the organization. This 7 by 11 matrix defines 11 types of IOS applications (e.g., receiving or issuing purchase orders, payments, coordination) with seven groups of potential IOS partners in the organization’s business environment: business customers, suppliers within the value chain, business partners, competitors, maintenance repair and operation (MRO) services suppliers, information suppliers, and banks (see definitions in Table 1). The content validity of the instrument was validated by ten experts (see Sect. 3.3). The respondents were asked to mark in each cell the existing and planned IOS implementations: e for existing, p for planned, or leave the cell empty if IOS are neither used nor planned in the next 24 months. Each cell was given a numerical value: two points for existing use, one point for planned use, and zero for an empty cell. The IOS implementation index is defined as the sum of the cell scores plus additional 50 points for IOS actual users (a show of an existing use). The constant added to IOS users prevents a situation where planners of many applications might
123
A Theory of Constraints approach to interorganizational systems implementation
349
Table 1 IOS implementation status matrix IOS applications
Other organizations Business Suppliers Business customers within the partnersa value chain
Competitors MRO Information suppliersb suppliersc
Banks
Receive or issue orders Payments and foreign trade Customer support or technical maintenance Access to others’ inventory data Access to your organization’s inventory data Access to others’ sales data Access to your organization’s sales data Coordination or supervision Knowledge management or research and development Information distribution or advertising Other a
Business partners are those which have cooperation agreements with the organization, or ownership relationships such as parent company or a daughter company
b
Suppliers of maintenance repair and operation services like office supplies
c
Provide information services, such as those of Dun and Bradstreet
have higher index values than those that actually use IOS but indicated just a small number of applications. Apparently, the constant should be 77, as the number of the matrix’s cells, just in case that a certain organization plans to deploy all the suggested uses. However, in reality, there was no such organization, so the constant was set to 50 points. Therefore, the index value for organizations which neither have IOS nor plan to install them is zero, the planners have values ranging from 1 to 49, and the values of the users are above 52. The IOS implementation status index combines all the IOS applications and connections of the organization to a single aggregate measure. Elia et al. (2007) have taken a similar approach in building their index of IOS adoption. Overall, aggregated measures of organizational innovation,
123
350
N. Geri, N. Ahituv
including new technology adoption, are expected to be more robust and generalizable (Fichman 2001). Perceived potential strategic and transactional benefits of IOS. The items that were used to measure the perceived external and internal values of IOS were taken from previous research which measured benefits of IOS, especially EDI (Premkumar et al. 1994; Chatfield and Bjoren-Andersen 1997; Lee et al. 1999; Vlosky et al. 2000; Chwelos et al. 2001), as well as information system value in general (Mirani and Lederer 1998), and theoretic research (Malone et al. 1987; Johnston and Vitale 1988; Ahituv 1989). The items were measured on a five point Likert scale: (1) definitely false; (2) rather false; (3) equally true and false; (4) rather true; (5) definitely true. Since the item classification to external benefits and internal benefits is new, its validity was confirmed by factor analysis (see Table 3 below). The power position of an initiator was measured by one item: respondents were asked to indicate their opinion how true or false is the statement: ‘‘Your organization is compelled by other organizations to join IOS’’. The possible answers were measured by a five point Likert scale similar to the above. Since the question relates to factual information, there was no need for multiple items. Maximal infeasibility is a construct, which contains the maximum of the values of five variables: economic infeasibility, organizational infeasibility, technological infeasibility, risks, and lack of financial resources. Apparently, when an organization uses IOS it proves the feasibility. Hence, users and non-users (including planners) were treated separately. Non-users and planners were asked to answer 11 questions related to the infeasibility aspects. The items composing the infeasibility constructs were based on previous research (Premkumar et al. 1994, 1997; Chatfield and Yetton 2000; Truman 2000; Vlosky et al. 2000; Chwelos et al. 2001). The items were measured on a five point Likert scale similar to the above. Table 4 presents the constructs’ components and the results of the factor analysis, which validated them. As indicated above, the highest value of the five infeasibility constructs is defined as the maximal infeasibility measure, since even if only one of the feasibility conditions is not met it may be enough to prevent IOS implementation. The infeasibility measure of the existing users is the average of the answers to four questions, listed in Table 2, each representing one aspect of feasibility. An average was calculated, rather than a maximal value, since IOS are already used, and different levels of feasibility are expected to influence the IOS implementation level. Organization size was measured by the annual revenues. The common measures of organization size are revenues and number of employees. Chwelos et al. (2001) included both in a construct, which indicated the financial readiness of an organization for EDI implementation. Usually, the number of employees is used when the research population includes organizations that their revenues are hard to measure or are unavailable, such as nonprofit organizations. However, since this research is conducted on business organizations, they all have annual statements. Furthermore, since the study concerns IOS it seems that the number of employees is not an appropriate measure because effective IOS may result in fewer employees. Moreover, many organizations outsource activities or use offshoring, and it may
123
A Theory of Constraints approach to interorganizational systems implementation Table 2 Infeasibility measure for IOS users
a
351
Feasibility aspect
Please indicate to what extent the statements are applicable to the IOS in your organization: (1) not at all; (2) a little bit; (3) to a moderate extent; (4) to a great extent; (5) to a very great extent
Economica
IOS implementation is cost-benefit justified
Organizationala
Senior management is committed to IOS use
Technologicala
IOS are integrated with relevant internal systems
Risks
There is a risk that other IOS participants will use them against your organization
Reversed scale
distort the number of employees’ data. Therefore, this study measured organization size by the annual revenues. The industry IOS status index was measured by the average of the IOS status index of all the organizations in its industry, which participated in the survey. The sample was checked for non-response bias and has been found adequate with respect to the industrial sector distribution. The organizations were classified into nine sectors, which are exhibited in Table 5 that includes the industrial index data, as well.
3.3 Instrument validation Due to the exploratory nature of this study, multiple linear regression analysis was selected. The data was analyzed by SPSS. The validity and reliability of the constructs were evaluated according to the guidelines provided by Straub (1989) and Boudreau et al. (2001). External validity. The procedures performed to check for non-response bias were described in Section 3.1. Reliability. The Cronbach’s coefficient a values of the multiple-item constructs are detailed in Tables 3 and 4. All of them range from 0.735 to 0.874, and indicate adequate internal consistency. Content validity of the constructs was established first by an extensive literature review, and then by a pretest of the questionnaire. Ten information systems experts, including academics, CIO’s, CEO’s and senior consultants were asked to evaluate the pilot questionnaire. Following the feedback analysis, the questionnaire was slightly revised and improved. Construct and discriminant validity of multiple item constructs were examined by factor analysis, using varimax rotation. An analysis on 14 items that measured the perceived potential benefits of IOS, with a two factors constraint, indicated that the constructs are valid (see Table 3). Another analysis was performed on the 11 items that measured infeasibility. However, out of the 55 IOS users, 20 decided to answer the 11 questions intended for the non-users and planners (in addition to the four questions dedicated to the
123
352
N. Geri, N. Ahituv
Table 3 Validity and reliability of perceived potential values of IOS Construct
Cronbach’s a (n = 139) Item description
Loading
Perceived Potential Strategic Benefits of IOS
0.874, 9 items
Gain competitive advantage
0.706
Avoid competitive disadvantage
0.565
Improve bargaining power over customers/ 0.595 suppliers Improve service to consumers
Perceived Potential Transactional Benefits of IOS
0.758, 5 items
0.770
Shorten lead time
0.556
Enhance sales
0.758
Fit products to costumer requirements
0.772
Launching new products and services
0.721
Support after-sale service or maintenance
0.628
Cheaper procurement
0.849
Reduce transaction costs
0.827
Reduce errors and returns
0.607
Enable outsourcing of more activities
0.645
Reduce the organization’s inventory levels 0.476
users) because they felt that these factors inhibit IOS implementation in their organizations. Thus, their maximal infeasibility measure was based on the 11 questions, and the analysis results are presented in Table 4. The factors and their composition were identical to the theoretic model. Hence, the measurement instruments demonstrate adequate construct and discriminant validity.
4 Results The annual revenues of participating organizations ranged from 7.5 million USD to 2.5 billion USD, with an average of 200 million USD (SD 418). They employed from 9 to 14,600 employees, with an average of 967 people (SD 2,239). 39.7% of the organizations were IOS users, 19.9% were in the planning stage, and 40.4% did not use or plan to install IOS. Table 5 shows the distribution of IOS usage, categorized by industrial sectors. The model was tested by a multivariate linear regression on the sample of 139 organizations. The model explains 46.4% (adjusted R square) of the variance in the IOS implementation status and the estimated standardized coefficients results are presented in Fig. 2. All four hypotheses were supported and significant in the range of 0.001–0.05 levels. The perceived potential strategic benefits (H1) and a power position of an initiator (H3) positively influenced the IOS implementation status, whereas maximal infeasibility (H4) negatively influenced it, and had the strongest effect. The coefficient of the perceived potential transactional benefits construct was not significant. Thus, the findings support Hypothesis H2, and suggest that the perceived
123
A Theory of Constraints approach to interorganizational systems implementation
353
Table 4 Validity and reliability of maximal infeasibility Construct
Cronbach’s a (n = 106)
Item description
Loading
Economic Infeasibility
0.788, 2 items
IOS not perceived as cost effective
0.875
Organizational Infeasibility
0.735, 3 items
Technological Infeasibility
0.839, 3 items
Risks
Lack of resources
IOS will not bring any benefit (disregarding their 0.885 costs)
0.775, 2 items
NA, 1 item
Uninterested senior management
0.768
Unsupportive organizational culture
0.757
Potential partners are not interested
0.775
Insufficient computing infrastructure
0.887
Integration difficulties with internal systems
0.875
Incompatible communications, hardware, or software standards
0.790
Information security risks
0.848
Fear of opportunistic behavior by potential partners
0.879
Lack of financial resources
NA
Table 5 Industrial IOS implementation status results IOS Implementation Status
Industry IOS status Users
Actual index range Industrial Sector
54–137 Index
a
#
#
b
%
Planned
None
2–45
0
#
#
%
%
Services
54.70
18
13 72.2 2
11.1 3
Trade
37.46
35
17 48.6 4
11.4 14 40.0
16.7
Electronics and Computers
34.88
25
10 40.0 9
36.0 6
24.0
Food
33.50
13
6
15.4 5
38.5
46.2 2
Chemicals, pharmaceutics, and agricultural inputs 30.10
16
6
37.5 4
25.0 6
37.5
Textile
27.70
6
2
33.3 2
33.3 2
33.3
Metal
11.70
10
1
10.0 3
30.0 6
60.0
Plastics
6.40
10
1
10.0 1
10.0 8
80.0
Paper, wood and construction
0.40
8
0
0
12.5 7
87.5
Total
31.5
141
56 39.7 28 19.9 57 40.4
a
1
# is the number of organizations included in the category
b
% is the percentage of the organizations included in the category out of the total number of organizations in the sector
potential transactional benefits of IOS do not influence the implementation status index. As in previous research, the two control variables: organization size and industry IOS status were significant and were found to positively affect the IOS implementation status.
123
354
N. Geri, N. Ahituv
Perceived Potential Strategic Benefits
+ H1 0.170*
Perceived Potential Transactional Benefits Economic Infeasibility
Power Position of Initiator
Organizational Infeasibility Technological Infeasibility
H2
-
MAX
0.012
+ H30.220**
IOS Implementation Status
-0.358**
H4 0.153*
0.146*
Maximal Infeasibility
Risks Lack of Financial Resources
N = 139 Adjusted R Square = 0.464
Industry IOS Status
Organization Size
CONTROL VARIABLES
*p
