School of Mechanical and Manufacturing Engineering UNSW, Kensington, Australia
Email: z3115638@student.unsw.edu.au
School of Mechanical and Manufacturing Engineering UNSW, Kensington, Australia
Email: m.hasan@unsw.edu.au

A consecutive number of studies on the adoption trend of logistics technology since 1988 revealed that logistics organizations are not in the frontier when it comes to adopting new technology and this delayed adoption created an information gap. In the advent of supply chain management and the strategic position of logistics, the need for accurate and timely information to accompany the logistics executive became more important than ever before. Through the use of literature from logistics and diffusion theory, this study develops a comprehensive transfer model of logistics technology with switching rules. In addition, the study gathers information on problems encountered during the adoption of these technologies and lists suggested solutions to enhance model applicability.
Keywords: Logistics technology, stage models, diffusion theory, adoption, implementation.
Unlike other business fields, logistics has gone through several major redefinitions of its role in organizations (Bowersox, 1983; Langley, 1986; Bowersox and Daugherty, 1987) starting with a fragmented approach to an integrated to a strategic orientation (Bowersox and Daugherty, 1995).
However, through each of these stages of logistics development the importance of technology in reducing logistics costs and improving customer service was known and confirmed (Bowersox and
Droge, 1989; Lalonde and Auker, 1995; Williams et al, 1997). As a result of moving toward an
integrated logistics concept, logistics technology 1 adopted the same approach in order to reflect this
integration (i.e. integrative technology).
In organizations which recognize logistics field as a strategic weapon, logistics executives face a tremendous challenge from other departments (Kahn and Mentzer, 1996) and top management to show unprecedented results as logistics has a significant grip in strategy formulation and implementation (O’Neil and Iveson, 1991). Therefore, the need for technology that provides accurate and timely information has become more important than ever before. Robenson (1988) predicted that in 1995, logistics managers would spend their time dealing with issues related with computers and information processing. Later, Dawe (1994) stated that logistics organizations are not in the frontier when it comes to adopting new technology and this delayed adoption creates an information gap.
Recently, Nilsson (2006) found, through grounded theory, that one of the main sources of uncertainty
1 Logistics technology is used here to point to information technology applications in logistics. These can be software or hardware. Some examples are Enterprise Resource Planning (ERP) and Electronic Data Interchange
(EDI), Bar Coding.

that faces logistics managers is concerned with technology implementation and understanding. As a result, the need to address the issue of logistics technology adoption and implementation has become rather urgent.
Most Logistics technology studies have been case studies and questionnaire surveys. The case studies depict the process of successful or unsuccessful implementation of logistics technologies (Bamfield,
1994; Sum et al, 1997; Motwani et al, 2002; Muscatello et al, 2003; Xue et al, 2005). Questionnaire surveys, on the other hand, discuss mostly problems encountered during logistics technology implementation or critical success factors that contribute to the success of the implementation
(Cerveny and Scott, 1989; Ang et al, 1995; Hong and Kim, 2002).
Throughout studies of adoption factors of logistics technology, Electronic Data Interchange (EDI) literature has received much attention in the last sixteen years. In this stream of research, several adoption factors have been discussed such as readiness factors, technology-related factors, and organizational related factors (Iskandar et al, 2001 and Chwelos et al, 2001).
Research that treats adoption and implementation simultaneously is limited in logistics literature.
Russell and Hoag (2004) developed a model of adoption rate where adoption means adoption of end users to the system. The model uses several of the well-known adoption factors such as perceived attributes of innovation, organizational factors and leadership factors. Also, McGarrie (1998) developed a framework to help managers in selecting and implementing production planning and control technologies. While the framework covers several issues in the area of adoption and implementation, more research in this path is needed to cover the process in a more holistic way.
The above presentation of literature in the logistics area has revealed very little handling of logistics technology adoption and implementation process. Therefore, further knowledge has been sought from the innovation theory literature.
The literature on diffusion theory can be divided broadly into three streams of research namely, diffusion of innovation
2 , organizational innovativeness and process theory (Wolfe, 1994). Diffusion
of innovation research investigates the rates and pattern of innovation adoption over time and/or space. Organizational innovativeness research aims at finding the set of factors which can predict the organizational propensity to innovate. Process theory research investigates the nature of the
2 Innovation refers to a technology or a practice which is being used for the first time by members of an organization, whether or not other organizations have used it previously (Klein and Sorra, 1996).

innovation process and the sequence of activities in the development and implementation of innovations. Of interest to this study is the organizational innovativeness and process theory streams.
Research in the organizational innovativeness stream investigated the influence of individual factors
(e.g. job tenure, education background, in Kimberly and Evanisko, 1981), organizational factors (e.g. centralization, professionalism, in Zmud, 1982; Damanpour, 1988; Damanpour, 1987), environmental factors (e.g. uncertainty, inter-organizational dependence, in Cooper and Zmud, 1990), task factors
(e.g. task uncertainty, autonomy, in Cooper and Zmud, 1990; Kwon and Zmud, 1987) and technological factors (e.g. relative advantage and compatibility, in Tornatzky and Klein, 1982) on the different stages of the innovation process (e.g. adoption and implementation stages). In addition, studies in this stream examined the effect of factors related to one stage over factors related to subsequent stages in the innovation process (Ahire and Ravichandran, 2001; Premkumar et al 1994).
A major thesis of this stream is the prevalence of unsuccessful implementation. The above literature, for so long, has been investigating the set of predictors which will explain the variance in the “yes/no” adoption decision. Only recently, the importance of investigating the determinants of successful implementation has been realized. However, studies which discuss determinants of successful implementation have investigated this within a single innovation context thereby not adding a lot to cumulative knowledge. This is despite the existence of treatments to rectify the instability in innovation research which were offered by Downs and Mohr (1976).
Research in the process theory stream has resulted in various stage models of the organizational innovation process (table 1). Briefly, Thomson’s (1969) model, which is composed of initiation, adoption, and implementation, is considered a first step in the stage models. Thomson’s model captures the overall picture of technology transfer, but it can’t be used solely to guide the technology transfer efforts as it overlooks the importance of some pre-adoption and post-adoption evaluation processes. Therefore, subsequent stage models have come into existence to shed light on these processes. Kwon and Zmud’s model (1987) gives more emphasis for post adoption stages as they were decomposed into four stages namely, adaptation, acceptance, routinization and infusion.
Infusion is a distinctive feature in their model which reflects advanced incorporation enabling deeper and more comprehensive embedding of an innovation within an organization’s operational and/or managerial work systems beyond routinization (Zmud and Apple, 1992). Roger’s model (2003) , on the other hand, explores the area of fit between task characteristics and technology characteristics by imposing two stages for this purpose in his model (matching and redefining/restructuring). Zaltman et al (1993) explored the issue of sustainability of implementation in his model. Finally, Sheirer’s model
(1983) is distinctive with the assessment of outcomes and diffusion of information stages.

Authors 1
Thomson
(1969)
Initiation
Rogers
(2003)
Kwon &
Zmud
(1987)
Agendasetting
Matching Redefining/ restructuring
Initiation Adoption
Clarifying Routinizing
Zaltman
(1993)
Knowledgeawareness
Formation of attitudes
Sheirer
(1983)
Basic research
Technology development and testing
Decision Initial
Diffusion of information implementation
Continuedsustained implementation
Adoption Implementation Assessment of outcomes
Routinization
Despite their dominance in academic research, the existing versions of stage models can’t guarantee the success of the transferring process and this is because of three main factors. First, essential differences exist among them making it hard to choose the right model when transferring a technology into the organization. Second, the models don’t describe how different innovation patterns should be approached. For example, an innovation process that is initiated internally is different from one which is initiated by external factors (e.g. order from headquarters, competition, or pressure from a trading partner). Third, these models are static and deterministic in nature. In other words, the actual innovation process is dynamic and it has many feed forward and feed backward cycles (Wolfe, 1994).
As the objective of diffusion theory is to strive to investigate the possibility of deriving a unified theory which can cover several innovations while not violating organization-innovation attributes, a systematic and cumulative perspective should be followed (Downs and Mohr, 1976; Poole and Van de
Ven, 1989:637-662).
Poole and Van de Ven (1989:641), in discussing a strategy to develop a theory of innovation process theories, stated that
A good metatheory must specify conditions under which various models hold and when to switch between models to explain an innovation process at a given point in time.
While developing this metatheory is way beyond the scope of this article, a similar thought was considered throughout this study. Stemming from this, the purpose of this paper is of three fold:
1) Observe the patterns of organization innovation processes of logistics technology.

2) Develop switching rules to determine how and when observed patterns should be used.
3) Enhance the successfulness of the different patterns by gathering and solving problems which were observed during the transfer process.
The domain of the research study was derived from the logistics technology adoption and implementation articles published in literature. Only case studies and questionnaire surveys which had their research questions as the adoption and implementation process of a specific logistics technology were chosen to derive the patterns observed. The collected papers were then classified according to the transferred technology. Although, there was no intention to restrict the study to some journals, the final list is dominated by some of the top journals in the area. Starting from the most frequent, there is
Production and Inventory Management Journal, International Journal of
Operations and Production Management, International Journal of Production Economics,
Information & Management, Supply Chain Management, and International Journal of Physical
Distribution and Logistics Management .
For the collection of problems faced during the adoption and implementation process, questionnaire surveys and case studies which included research questions as problems faced during the transfer process were gathered. In the questionnaires, only those problems which were statistically significant were included.
In preparing the papers for building the model, the adoption and implementation process in each paper were analyzed and the given sequences were listed. As the sequences derived from the papers were very detailed, Thomson’s (1969) model of initiation, adoption and implementation was used.
Following this model, activities which happened before making the adoption decision were classified as initiation and the ones after adoption were classified as implementation. Using an iteration process, activities which were classified as initiation under each technology were further classified according to their similarities. The same process was undertaken for after adoption activities. By this time, patterns started to emerge. Finally, similar sequences among technologies were grouped together.
In developing the switching rules, some of them were already apparent from the final classification.
However, precise understanding for further branching was obtained by looking at the conditions that governed each sequence.

Pattern and Switching Rules Results
A total of 46 articles pertaining to logistics technology adoption and implementation were identified through a search of the literature. The articles correspond to six logistics technologies which represent the only available to extract from literature despite an initial aim of having more technologies. These logistics technologies are Manufacturing Resource Planning, Material
Requirement Planning/Just In Time, Enterprise Resource Planning, Electronic Data Interchange,
Efficient Consumer Response, and Vendor Managed Inventory. The first three correspond to organizational technologies and the rest correspond to inter-organizational logistics technologies.
The sequence and patterns analysis resulted in four main sequences and the switching rule analysis resulted in two rules. The first rule states that logistics technology adoption process is generally classified according to organizational/inter-organizational exposure. Once this is specified, the second rule states that the sequence of the expected innovation process depends on the way it is initiated. Under this rule, there are two initiating patterns which were observed in literature; one is internal to the organization and the other is external. In an internally initiated pattern, the company identifies needs and inconsistencies in the current working system which inhibit further improvement and development. Some examples of these needs are problems in previous manufacturing system, increase in costs of materials, the need for connectivity, difficulties in responding to any dynamic operation within the company, decrease in revenues, deteriorating customer service and the ‘bullwhip’ effect. On the other hand, an externally initiated pattern is outside the control of the company and it ranges from normal to severe. Some examples are competitive pressures, order from headquarters, pressure from trading partner(s), and strong software sales discourse existing in the market.
By combining the emerged patterns and the switching rules, two models were derived. The first model shown in figure 1 is the organizational logistics technology transfer model and the one shown in figure 2 is the inter-organizational logistics technology transfer model.

Phased Implementation
Implementation
Decision
Full Implementation

Pilot Implementation
Implementation
Decision
Full Implementation

Problems faced during the adoption and implementation (transfer) process of logistics technology
The problem gathering phase resulted in 21 problems spanning over 6 logistics technologies (the same technologies used in the models’ analysis). Further, the problems were ranked according to their frequency over the six logistics technologies. Based on this, a problem with a frequency of six was ranked as number one and a problem with frequency of 5 was ranked as number two. The final list is shown in table 2.
Table 2: Problems encountered during the transfer process
MRP/JIT MRPII ERP EDI ECR VMI Rating
Lack of Education and training
Lack of top management support
Lack of effective project management
Lack of expertise (Company and technical)
Organizational Resistance
Data accuracy
Lack of support from software vendor
Lack of suitable hardware and software
Lack of cultural (organizational) readiness
Improper change management
Autocratic mandatory implementation by top management
High setup costs
Lack of standard formats and methods
Lack of customer sophistication
Lack of awareness of benefits
Conflicting priorities for resources
Inflexible information systems
Information sharing and accessibility
Inappropriate/inaccurate performance and cost measures
Loss of control of key products
Lack of understanding the technology
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√ 5
√ √ 4
√
√
√
√
√
√
√
√
√
√
√
√
√
√ 2
√
√
√
√
√
√
√
2
2
√ 4
√ 2
√ 4
√ 5
6
6
√ 6
√
√
√
√
√ 6
√ 6
√ 6
√
√
√
5
6
√
√
4
5
5
1
The table shows that the highest ranked problem, faced during the transfer of logistics technology, is lack of understanding the technology. This is followed by lack of education and training, lack of top management support, lack of effective project management and organizational resistance. Given a difference of one between first level and second level problems, these problems can be considered the main problems leading to the failure of logistics technology adoption and implementation. Lack of understanding the technology is related to lack of education and training. Therefore, a careful assessment of education and training needs should minimize this problem. Despite the recognition of lack of education and training as a significant problem by several authors, there is no framework which could help managers to identify the required amount of education and training for their staff.
Through the surveyed case studies, the importance of multilayer education and training (i.e. senior level, implementation team, and end users) was found to be related to management commitment and eventual success of the project (Ormsby et al, 1990).

Lack of top management support can be attributed to several causes. For example, lack of awareness of benefits and lack of education for top and middle management are some of them. Sum et al (1997) identified three elements of top management support namely, showing interest, providing necessary resources, and showing leadership. Underestimation in any of these elements can result in lack of top management support as well. Meredith (1981) developed a set of questions which should be checked by asking top management before proceeding into the implementation process. The answers to these questions provide an indication of the extent of top management support. Therefore, these answers should be used instead of the ‘yes/no’ adoption decision.
Lack of effective project management is a result of several things. It could be because of the backgrounds of the team members or it could be because of the project management software. The implementation or project team should have at least one competent project planning member. On the other hand, project management software is a necessary for a logistics technology transfer project.
Weston (2001) gave a list of the abilities that should be available in the project management software to achieve minimum functionality. Other factors which contribute to this problem are external. For example, the project management could be placed under pressure from top management to finish the project fast or the forthcoming activities (including education and training of end users) in the implementation process are ambiguous which affect the project plan. These two problems can be solved effectively by educating the project team and senior management about the implementation process of the logistics technology under consideration.
Organizational resistance is a result of improper change management which is a problem in itself. For these to be solved, a change management plan should be put in place before proceeding to implementation. The change plan should address all three layers in the organization. As the implementation team could be the layer that knows most about the problem size, the solution, and potential benefits, the other two layers (top management and end users) should also be aware of these three issues. Other factors that the plan should address include the required amount of education and training, the rewarding system and project communication. Another observation that relates to this issue is the sudden drop in end users ability. Before moving to the new system of work, end users already developed competency in using the old system which could have been most likely connected to the rewarding system. Therefore, the change plan should address this issue effectively and make sure that end users agree to adopt the systems not just top management. In this way, they will be committed to change.
Solutions for other problems are listed in table 3.

Table 3: Solutions
Problems Encountered Suggested solutions from literature
Lack of expertise (Company and technical) Education, outside expert, consultant
Data accuracy Education, importance of data integrity
Lack of support from software vendor
Lack of suitable hardware and software
Lack of cultural readiness
Rigorous Selection Process, Careful technology adjustment process
Rigorous Selection Process
Refer to organizational resistance problem
Refer to organizational resistance problem Improper change management
Autocratic mandatory implementation by top management
High setup costs
Top management education about change management
Awareness of benefits and achieving critical mass
Lack of customer sophistication
Lack of awareness of benefits
Conflicting priorities for resources
Inflexible information systems
Information sharing and accessibility
Inappropriate/inaccurate performance and cost measures
Loss of control of key products
This should be used to assess customer abilities
Education and Training
Refer to Kurnia and Johnston (2001)
Refer to Pearce (1997)
Buyer-Supplier exchange programs
Activity Based Costing
Buyer-Supplier exchange programs
Initiation Process
LTTM has two initiating patterns; one is internal and the other is external. Under internal pattern, the company finds that the current system or operation is limited either because it can’t satisfy the current set of organizational goals or that the current goals were raised requiring a change in the system. In either case, the system must be examined carefully to find out what are the exact restraining factors.
Failing to define the exact needs or motives for change might result in an incomplete transfer process or a total failure. Some examples are decline in revenue, deteriorating customer service, and market expansion. These reasons are aggregate in nature and can’t be used solely to justify guiding the transfer process. Causes of these should be examined by breaking them down to a level where areas of potential improvements can be specified. Techniques such as “fishbone from quality management” can be used effectively here. Therefore, this process should result in a list of areas of potential improvements. In the inter-organizational case, one or both of the companies should realize some of the above factors where they work to find out the areas of potential improvements.
In the external initiating pattern, the company doesn’t internally realize or
understand
the need for change. However, this doesn’t mean by any way or another that a change is not needed. It could even be a chance for the company to improve its performance. However and in most cases the company can’t understand this or doesn’t know the right way to deal with it which could result in disruption in the system depending on the severity of the external factor. In competitive environments, for

example, the need for change comes to the attention of top management first, but not necessarily the rest of the organization. Therefore, this may result in many question marks within the company unless a thorough matching process is undergone to prepare for the change. In the case of order from headquarters, the whole company including top management of the organization may not totally comprehend the reason for the change depending on the adoption plan of headquarters. The need for an executive sponsor from headquarters to explain the reasons for change to top management and also to proctor the implementation process is desirable (Muscatello et al, 2003). For a comprehensive discussion of the ‘headquarters’ scenario, the reader can refer to Markus et al (2000). In interorganizational logistics technology transfer, pressure from a trading partner has been cited as a significant factor in the adoption process. Crook and Kumer (1998) listed the use of coercion, support, collaboration and the use of incentives as four strategies that companies use to approach their trading partners.
Matching and assessing Processes
A Matching process can best be described as a cognitive learning process. Once the areas of potential improvement are identified, the firm(s) scans for solutions through different sources. The solution doesn’t have to be a technological one. It could be a procedure or formation of a department or assignment of an employee to perform a specific task. In the logistics technology case, a thorough understanding should be developed as to how this solution is going to solve current problems. Also, it should reliably differentiate those pairs (need-solution) which are naturally satisfied from those that require adjustment. Quality Function Deployment (QFD) House can be used effectively in the matching process. In cases where the technology is known through an external factor, matching would mean finding those areas within the company that the logistics technology would affect and improve. In the assessing process of an inter-organizational model, the approached trading partner will assess whether or not to accept the request of other trading partner(s) by the leverage this partner has in the relationship and the strategic importance of retaining them.
Selection Process
The Selection process shouldn’t be understood from a narrow perspective of only selecting the software vendor. It could also mean selecting whether to buy the logistics technology or to develop it in-house. In this matter, company policy and directions affect the final selection. In terms of interorganizational technology, the selection process seeks to select the most suitable trading partner to initiate a partnership with. As figure 2 shows, the selection process goes hand in hand with the conceptualization process. Once a trading partner is selected, the selection process can then be performed again to select the software vendor jointly with the trading partner. Factors such as vendor support, quality and cost can be used to select the software and the vendor. For inter-organizational

technology, factors such as size of trading partner, product range, product shelf-life, complexity of the business and history of the relationship can be used to select the appropriate trading partner(s).
Adoption Process
This is the time when top management commits itself to showing interest, providing necessary resources, and showing leadership toward the implementation of the logistics technology. The adoption decision is affected by several factors or predictors. Some of these are technology-related factors (e.g. relative advantage, compatibility, and complexity), external factors (e.g. order from headquarters, trading partner pressure, and competitiveness), organizational and inter-organizational readiness (e.g. financial readiness, technological readiness and trading partner readiness).
Top management adoption decision is also affected by the adoption strategy. Frohlich (1998) discussed the affect of three adoption strategies that top management may pursue with regards to
Advanced Manufacturing Technology (AMT) namely, prototype (pilot) learning, simulation learning, and vicarious learning. Vicarious learning includes self learning, expert learning, consultant learning, and vendor learning. Management uses these strategies usually to reduce the risk of implementation failure.
Conceptualization Process
This process by far is the most important process in the logistics technology transfer project. Some authors call it the “get organized” stage. Most technology transfer projects fail to recognize the importance of this stage and don’t give it enough time. In the organizational context, this stage involves:
Developing detailed implementation process (project scope, schedule, resource requirements, quality, and risk concerns).
Assessing training and education needs.
Dividing project responsibilities (sub-groups could be established to proctor specific tasks implementations).
Specifying baseline performance metrics.
Determining amount of adjustment required either to the organization or to the technology.
In the inter-organizational context:
Establishing cross-functional cross organizational team.
Joint missions, goals and performance measurements.
Aligning corporate goals.
Agreeing on a common vision, benefits, and training activities.
Check-list of capabilities.
Building a trust relationship.

Redefining/Restructuring Process
Redefining/Restructuring is the same stage as the one in Roger’s Model (2003). Several of current technology transferring processes require that some changes be introduced either in the technology or the organization. There is a wide range of options available for technology changes especially in ERP
(Brehm et al, 2001). Also, there is a significant amount of changes which could be carried out in the organization, for example business process reengineering. An important observation from literature is that several companies are hesitant to perform the required changes or may not know how (Kulunda,
2000 and Hong and Kim, 2002). Concurrently, education and training of employees is carried out.
Implementation Process
The implementation stage involves actual implementation or installation of the technology. During this stage, three sub stages were often cited in literature namely, pilot or phased implementation, final implementation decision, and full implementation. Phased implementation tends to occur in organizational logistics technology such as ERP and MRP while pilot implementation occurs in interorganizational logistics technology such as EDI and Vendor Managed Inventory (VMI). In these implementations, partial implementation is performed and evaluated. Problems which arise are reported and solved using an effective feedback system. In the second sub-stage, the previous process is evaluated. If things went smoothly a final implementation decision is given to perform final implementation otherwise the technology transfer process stops here. In the final full implementation sub stage, implementation for other departments and/or products is carried out.
Evaluation Process
In the evaluation process, results are compared against initial objectives and baseline performance.
Also, the project team prepares the final report, which contains the comparison of scope, schedule, resources used against initial expectations. Benefits realized by the project team can be communicated at this stage to top management and end users to facilitate the acceptance of the new technology.
Acceptance and Routinization processes
The acceptance process goes hand in hand with implementation. As the technology is implemented, user resistance or acceptance is reported along with the implementation problems. Further acceptance of the system is enhanced and increased as the system is diffused among larger group of users.
Routinization is the process by which the change in the working system becomes a routine or a normal activity. Naturally, routinization is achieved after acceptance of change spreads among users.

Not all technology transfer efforts reach this high level of success or routinization. Two problems might occur right before the routinization stage; an incomplete acceptance of the change or unsatisfied needs. This might lead the users to revert back to the old system. Therefore, it is important to eliminate the possibility of returning back to the old system and equally important to open a channel for effective feedback to solve problems that arise. From there, another cycle of technology adoption and implementation is started over to indicate either a new technology is introduced in the company or an advanced incorporation (infusion) of the same technology (Zmud and Apple, 1992; Humphreys et al, 2001).
The aim of this paper has been to investigate the issue of logistics technology adoption and implementation. Through a survey of literature pertaining to case studies and survey of logistics technology along with knowledge from innovation theory literature, it was possible to arrive at a comprehensive model which encompasses different initiating scenarios. The model is composed of switching rules that can be used to identify which part of the model flow would be most appropriate for a given situation.
In order to enhance the practicality of the model, a survey through literature to gather information about problems encountered during the adoption of logistics technology was undertaken. In addition, suggested solutions from literature were given with special attention to those problems that span several logistics technologies.
A next step in this direction would be to develop a motor or a mechanism for each process which is linked to other processes. This motor should be able to remove as many ambiguities as possible by taking into consideration the different scenarios that govern the transfer process. The description given for each process along with the literature can be used as a guide in developing the constructs and interconnections within and between processes.
Another step in the same direction would be to develop a concurrent change model which can work with the logistics technology transfer model to guide the transfer process in the right path. The model should be of practical use to top management and implementation team. Also, it should address change to all the different layers in the organization. In addition, the change model should cope with the dynamic nature of nowadays enterprises.

Ahire, SL & Ravichandran, T November 2001, ‘An Innovation Diffusion Model of TQM
Implementation’, IEEE Transactions on Engineering Management , vol. 48, no. 4, pp. 445-464.
Ang, JSK, Sum, CC, & Chung, WF 1995, ‘Critical Success Factors in Implementing MRP and
Government Assistance: A Singapore Context,
Information & Management
, vol. 29, pp. 63-70.
Bamfield, J 1994, ‘Learning by Doing: Electronic Data Interchange Adoption by Retailers’,
Logistics
Information Management
, vol. 7, no. 6, pp.32-39.
Bowersox, DJ 1983, ‘Emerging from the Recession: The Role of the Logistical Management’,
Journal of Business Logistics
, vol. 4, no. 1, pp. 21-33.
Bowersox, DJ & Daugherty, PJ 1987, ‘Emerging Patterns of Logistical Organization’,
Journal of
Business Logistics
, vol. 8, no. 1, pp. 46-60.
Bowersox, DJ & Droge, C 1989, ‘Similarities in the Organization and Practice of Logistics
Management among Manufacturers, Wholesalers and Retailers’,
Journal of Business Logistics
, vol.
10, no. 2, pp. 61-72.
Bowersox, DJ & Daugherty, PJ 1995, ‘Logistics Paradigms: The Impact of Information
Technologies’, Journal of Business Logistics , vol. 16, no. 1, pp. 65-80.
Brehm, L, Heinzl, A & Markus, ML 2001, ‘Tailoring ERP Systems: A spectrum of Choices and Their
Implications’, in Proceedings of the 34 th
Hawaii International Conference on System Sciences ,
Hawaii.
Cerveny, RP & Scott, LW 1989, ‘A Survey of MRP Implementation’, Production and Inventory
Management Journal , vol. 30, no. 3, pp. 31-34.
Chwelos, P, Benbasat, I & Dexter, AS September 2001, ‘Research Report: Empirical Test of an EDI
Adoption Model’, Information Systems Research , vol. 12, no. 3, pp. 304-321.
Cooper, RB & Zmud, RW 1990, ‘Information Technology Implementation Research: A
Technological Diffusion Approach’, Management Science , vol. 36, no. 2, pp.123-139.
Crook, CW & Kumar, RL 1998, ‘Electronic Data Interchange: a Multi-industry Investigation Using
Grounded Theory’, Information & Management , vol. 34, pp. 75-89.
Damanpour, F 1987, ‘The Adoption of Technological, Administrative, and Ancillary Innovations:
Impact on Organization Factors’, Journal of Management , vol. 13, pp. 675-688.
Damanpour, F October 1988, ‘Innovation Type, Radicalness, and the Adoption Process’,
Communication Research
, vol. 15, no. 5, pp. 545-567.
Dawe, RL 1994, ‘An Investigation of the Pace and Determination of Information Technology Use in the Manufacturing Materials Logistics System’,
Journal of Business Logistics
, vol. 15, no. 1, pp. 229-
259.
Downs, GW & Mohr, LB December 1976, ‘Conceptual Issues in the Study of Innovation’,
Administrative Science Quarterly
, vol. 21, no. 4, pp. 700-714.
Frohlich, M 1998, ‘How Do You Successfully Adopt an Advanced Manufacturing Technology’,
European Management Journal
, vol. 16, no. 2, pp. 151-159.

Hong, KK & Kim, YG 2002, ‘The Critical Success Factors for ERP Implementation: An
Organizational Fit Perspective’, Information & Management , vol. 40, pp. 25-40.
Humphreys, P, McCurry, L & McAleer, E 2001, ‘Achieving MRPII Class A Status in an SME: A successful case study’,
Benchmarking: An Internal Journal
, vol. 8, no. 1, pp. 48-61.
Iskandar, BY, Kurokawa, S & JeBlanc, LJ November 2001, ‘Adoption of Electronic Data
Interchange: The Role of Buyer-Supplier Relationships’,
IEEE Transactions of Engineering
Management
, vol. 48, no. 4, pp. 505-517.
Kahn, KB & Mentzer, JT 1996, ‘Logistics and Interdepartmental Integration’,
International Journal of Physical Distribution and Logistics Management
, vol. 26, no. 8, pp. 6-14.
Kimberly, JR & Evanisko, MJ December 1981, ‘Organizational Innovation: The Influence of
Individual, Organizational, and Contextual Factors on Hospital Adoption of Technological and
Administrative Innovations’,
The Academy of Management Journal
, vol. 24, no. 4, pp. 689-713.
Klein, KJ & Sorra, JS October 1996, ‘The Challenge of Innovation Implementation’,
The Academy of
Management Review , vol. 21, no. 4, pp. 1055-1080.
Kulunda DJ Third Quarter 2000, ‘MRP in the Third World’, Production and Inventory Management
Journal , vol. 41, no. 3, pp. 19-23.
Kurnia, S & Johnston, RB 2003, ‘Adoption of Efficient Consumer Response: Key Issues and
Challenges in Australia’, Supply Chain Management: An International Journal , vol. 8, no. 3, pp. 251-
262.
Kwon, TH & Zmud, RW 1987, ‘Unifying the fragmented models of information systems implementation’ In Critical Issues in Information Systems Research (Edited by Boland and
Hireschheim), Wiley, NY.
LaLonde, BJ & Auker, K 1995, ‘Survey of Computer Applications and Practices in Transportation and Distribution’, International Journal of Physical Distribution and Logistics Management , vol. 25, no. 4, pp. 12-21.
Langley, CJ 1986, ‘The Evolution of the Logistics Concept’, Journal of Business Logistics , vol. 7, no.
1, pp. 1-13.
Markus, ML, Tanis, C & Fenema, PC April 2000, ‘Multisite ERP Implementations’, Communications of the ACM
, vol. 43, no. 4, pp. 42-46.
McGarrie, B 1998, ‘Case Study: Production Planning and Control-Selection, Improvement,
Implementation’,
Logistics Information Management
, vol. 11, no. 1, pp. 44-52.
Meredith, JR October 1981, ‘The Implementation of Computer Based Systems’,
Journal of
Operations Management
, vol. 2, no. 1, pp. 11-21.
Motwani, J, Mirchandani, D, Madan, M & Gunasekaran, A 2002, ‘Successful implementation of ERP projects: Evidence from two case studies’,
International Journal of Production Economics
, vol. 75, pp.83-96.
Muscatello, J, Small, M & Chen, I 2003, ‘Systems in Small and Midsize Manufacturing’,
International Journal of Operations & Production Management
, vol. 23, no. 8, pp. 850-871.

Nilsson, F 2006, ‘Logistics Management in Practice-Towards Theories of Complex Logistics’, The
International Journal of Logistics Management , vol. 17, no. 1, pp. 38-54.
O’Neil, BF & Iveson, JL 1991, ‘Strategically Managing the Logistics Function’,
Logistics and
Transportation Review
, vol. 27, no. 4, pp. 359-377.
Ormsby, JG, Ormsby, SY & Ruthstrom, CR Fourth Quarter 1990, ‘MRP-II Implementation: A Case
Study’,
Production and Inventory Management Journal
, vol. 31, no. 4, pp. 77-81.
Pearce, T 1997, ‘Insights from Industry: Lessons Learned from the Birds Eye Walls ECR Initiative’,
Supply Chain Management
, vol. 2, no. 3, pp. 99-106.
Poole, MS & Van de Ven, AH 1989, ‘Toward a General Theory of Innovation’, In AH Van de Ven, H
Angle & MS Poole,
Research on the Management of Innovations: The Minnesota Studies
, Harper &
Row, New York, pp. 637-662,
Premkumar, G, Ramamurthy, K, and Nilakanta, S Fall 1994, ‘Implementation of Electronic Data
Interchange: An Innovation Diffusion Perspective’,
Journal of Management Information Systems
, vol.
11, no. 2, pp. 157-186.
Robenson, JF 1988, ‘The Future of Business Logistics: A Delphi Study Predicting Future Trends in
Business Logistics’, Journal of Business Logistics , vol. 9, no. 2, pp. 1-14.
Rogers, EM, 2003, “ Diffusion of Innovations ”, 5th edn, The Free Press, New York.
Russell, DM & Hoag, AM 2004, ‘People and Information Technology in the Supply Chain: Social and Organizational Influences on Adoption’, International Journal of Physical Distribution and
Logistics Management , vol. 34, no. 2, pp. 102-122.
Sheirer, MA 1983, ‘Approaches to the Study of Implementation’, IEEE Transactions on Engineering
Management , vol. 30, no. 2, pp. 76-82.
Sum, C, James A, & Yeo L Third Quarter 1997, ‘Contextual elements of Critical Success Factors in
MRP implementation’, Production and Inventory Management Journal , vol. 38, no. 3, pp. 77-83.
Thomson, VA 1969, ‘ Bureaucracy and Innovation ’, University of Alabama Press, Huntsville.
Tornatzky, LG & Klein, K February 1982, ‘Innovation Characteristics and Innovation
Implementation: A Meta-analysis of Findings’, IEEE Transactions on Engineering Management , vol.
29, no. 1, pp. 28-45.
Van De Ven AH & Poole MS July 1995, ‘Explaining Development and Change in Organizations’,
The Academy of Management Review
, vol. 20, no. 3, pp. 510-540.
Westen, FCT Third Quarter 2001, ‘ERP Implementation and Project Management’,
Production and
Inventory Management Journal
, vol. 42, no. 3/4, pp. 75-80.
Williams, LR 1994, ‘Understanding Distribution Channels: An Interorganizational Study of EDI
Adoption’,
Journal of Business Logistics
, vol. 15, no. 2, pp. 173-203.
Williams, LR, Nibbs, A, Irby, D & Finley, T 1997, ‘Logistics Integration: The Effect of Information
Technology, Team Composition, and Corporate Competitive Positioning’,
Journal of Business
Logistics
, vol. 18, no. 2, pp. 31-41.

Wolfe, RA May 1994, ‘Organizational Innovation’, Journal of Management Studies , vol. 31, no. 3, pp. 405-431.
Xue, Y, Liang, H, Boulton, WR & Snyder, CA 2005, ‘ERP implementation failures in China: Case studies with implications for ERP vendors’,
International Journal of Production Economics
, vol. 97, pp. 279-295.
Zaltman G, Duncan R & Holbek J 1993, ‘
Innovations and Organizations
’, John Wiley, NY.
Zmud RW & Apple LE 1992, ‘Measuring Technology Incorporation/Infusion’,
Journal of Product
Innovation Management
, vol. 9, pp. 148-155.
Zmud, RW 1982, ‘Diffusion of Modern Software Practices: The Influence of Centralization and
Formalization’,
Management Science
, vol. 28, pp. 1420-1431.