Toward an understanding of how organizations create manufacturing flexibility *.

In today's competitive environment, success is not about the surfeit of assets that an organization can flaunt. It is about the flexibility of those assets. It is about how organizations adjust to environmental change, while maintaining optimal productivity and seamless scalability. However, as Hayes (2000) aptly points out, the new demands for such organizational capabilities are different from those that managers have experienced in the past. He encourages us to look beyond the obvious and to scrutinize issues that underlie the decisions made by managers. This is particularly true in the manufacturing environment where high sunk-costs in equipment and processes make it difficult for organizations to respond quickly.

Researchers have made some progress. However, a comprehensive understanding of the creation of manufacturing flexibility has not yet materialized. One plausible explanation is that developments have been impeded by the narrowly defined research focus on manufacturing flexibility and its antecedents. Researchers have focused primarily on one of the antecedents, that is, environmental uncertainty. A wider scope of understanding of the antecedents of manufacturing flexibility will provide a context that is valuable to both researchers and practitioners.

In this article, an option-theoretic perspective will be used to identify factors that influence the creation of manufacturing flexibility, and to suggest a conceptual framework that links manufacturing flexibility to these factors. It begins with a presentation of contemporary perspectives on manufacturing flexibility. Four antecedents of manufacturing flexibility will be identified and a framework will be proposed to explain how these antecedents induce firms to configure their manufacturing flexibility. Six hypotheses will be developed and implications for researchers and practitioners will be presented in the final section of the article.

Option-theoretic Perspectives on Manufacturing Flexibility

Real-options and Real-option Theory

One can visualize a real option as a vehicle that provides an organization with preferential access to a course of action that could not be gained without prior creation of that option. (Unless otherwise indicated, the term "option" refers to a real-option, and not a financial option.) Once an option is created, it gives an organization the right, without the obligation, to take action in the future (Sharp, 1991; Amram and Kulatilaka, 1999). Typically, organizations make small initial investments to create options that can be followed by larger investments when the options are exercised.

Real-option theory grew out of dissatisfaction among academics and practitioners with the traditional methods of capital budgeting under conditions of uncertainty. When managers make investment choices, they are confronted with decisions in three areas: where to invest, how much to invest, and when to invest. Traditional methods of arriving at these decisions, as espoused in the capital budgeting literature (net present value analysis, discounted cash flow, capital asset pricing models, and other capital budgeting techniques), assume predictable risk levels and cash flows that result from relatively static operating conditions in the future. Unfortunately, such methods are less appropriate under conditions of environmental uncertainty.

The traditional approaches of dealing with significant levels of uncertainty include the use of sensitivity analysis, simulations and decision-tree analysis. However, as Bhagat (1999) points out, these approaches have their limitations. For example, carrying out a sensitivity analysis is not difficult. However, this process downplays interdependencies among variables. Simulations have been developed to handle interdependencies. However, these algorithms are somewhat limited in their ability to adequately address managerial preferences. Real option theory (option-theory within the context of organizational assets, as opposed to financial securities) is useful in these circumstances. It provides techniques that allow for the valuation of managerial preferences. This can provide significant strategic/competitive advantage to an organization. Put formally, management's ability to adapt its future actions by creating real options that mitigate or eliminate downside risk introduces an asymmetry in the probabilistic distribution of the projected net present value that expands the investment opportunity's true value (Trigeorgis, 1996). Within an option-theoretic framework, then, the organization's goal is to assemble an appropriate mix of real options that can provide the necessary flexibility to maximize return on its investments.

The Generalized Framework for Manufacturing Flexibility

D'Souza and Williams have defined manufacturing flexibility as: "...(T)he ability of the manufacturing function to make adjustments needed to react to environmental changes without significant sacrifices to firm performance" (2000: page 578). Building on prior research, they suggest that there are four underlying dimensions on which manufacturing flexibility can be defined and measured. Two of these dimensions (volume flexibility and variety flexibility) are externally oriented and address the need to manage uncertainty in the external environment. The other two dimensions (process flexibility and materials-handling flexibility) are internally oriented and address flexibility at the value-adding core activities of the business. Other researchers (e.g., Upton, 1995; Gerwin, 1993) have reasoned that each of the four primary dimensions should have characteristics of "range" and "mobility." Range reflects the scope of deviation from the norm afforded by a flexibility dimension, while mobility refers to the speed and efficiency with which changes can be made on that flexibility dimension. D'Souza and Williams provide details on how the four dimensions of manufacturing flexibility can be operationalized in terms of their range and mobility (2000).

From an option-theoretic perspective, we can now view manufacturing flexibility as the mix of options created on four dimensions, giving the manufacturing function the ability to respond to environmental changes that it could not have accomplished without the prior creation of these options. However, what factors influence the creation of such manufacturing flexibility? Studies have shown that the choice is dependent on several factors. Building on research in real-option theory, Kogut and Kulatilaka (1994) synthesized past research findings and identified three critical factors that induce managers to choose flexibility options: environmental uncertainty, management preferences and time dependency. They have been presented as a generalized framework in Figure I.

If environmental uncertainty did not exist, an option would have no value because all future decisions could be made in advance. Conversely, when uncertainty is high the value of holding an option could be high. However, it is conceivable that although several flexibility options are available, managers will not recognize every option. Even if they do, hey may opt to disregard/ignore some options. On the other hand, hey may overreact to environmental stimuli and make poor choices. Overill, one expects management preferences to influence the creation of flexibility options positively or negatively. Time dependency is the third factor that could influence the creaLion of flexibility options. Options are useful because they allow an organization to exploit the advantages of preferential access to future opportunities. Some options have higher efficacies than others do. Therefore, we can visualize managers creating appropriate options depending on the timeframe within which they expect to exercise the option.

Contemporary Perspectives on the Creation of Manufacturing Flexibility Options

A review of the literature revealed only limited research on the three factors that induce the creation of manufacturing flexibility. However, of the three factors, environmental uncertainty is the one that is most often cited. The operations management literature makes fewer references to the time-dependency dimension. Finally, no work was found to adequately address the role of management preferences in the creation of manufacturing flexibility options. In the following sections, I will survey current research on these three factors, identify their dimensions and isolate measures used in previous research.

Environmental Uncertainty

Uncertainty, as perceived by the manufacturing manager, emanates from environments that are both "external" and "internal" to the organization. Researchers (Dixon, 1992; Watts et al., 1993; Gupta and Goyal, 1989; Gerwin, 1987; Sethi and Sethi, 1990) have identified several factors that contribute to external uncertainty. Among them are: (1) resource and supplier-based uncertainties that are embodied in measures like availability of materials, supplier reliability, stock-outs, fluctuation in input material specifications, etc., (2) manufacturing technology-based uncertainties that reside in incremental and radical changes in the manufacturing technology environment, forced obsolescence of existing technologies and the firm's ability to absorb these new technologies, (3) product-based uncertainties driven by product modifications and new product introductions, (4) uncertainties in the competitor arena embodied in the rivalry exhibited by competitor firms and the speed and intensity of competitor reaction to mov es made by this firm, and (5) demand-based uncertainties that are created by changing demand patterns and customer behavior.

Several factors contribute to internal uncertainty. Some of the earlier developments on internal uncertainty are found in the works of Garrett (1986) and Buzacott and Mandelbaum (1985). Buzacott and Mandelbaum (1985) and Sethi and Sethi (1990) suggest that four of the most common factors that embody internal uncertainty are equipment breakdowns, variable task times and queuing delays resulting from rejects/re-work. Gupta and Goyal (1989) support this argument and suggest similar factors that reflect internal uncertainty - machine breakdown, variability in processing time and quality problems. When pooled together with other operationalizations of internal uncertainty, the operations management literature, overall, suggests three sources of internal uncertainty for the manufacturing function. These are: (1) machine/equipment breakdown, (2) variability in task times, and (3) fluctuations in output quality (i.e., delivery quality, product quality and process quality).

A component of internal uncertainty that is missing from the manufacturing flexibility literature is the uncertainty that lies within the organization but outside the manufacturing function. This uncertainty results from the organization's effort to develop and improve its core capabilities and can occur in a few or all of the functional areas of the firm. Internally generated uncertainty affects the manufacturing function most noticeably during its interaction with other functions (e.g., marketing, sales, R&D, finance, accounting and information systems) within the organization. In some cases, organizational efforts to improve their core competencies are limited to fine-tuning the strategy. In these cases, the resultant uncertainty that is generated may not have a significant effect on the manufacturing function. In other cases, the change efforts could be more dramatic and could create significant uncertainty for the manufacturing manager. Table 1 provides a summary of the environmental uncertainties that i nfluence the creation of manufacturing flexibility options.

Management Preferences

The management preference construct has not been well researched in the manufacturing flexibility literature. However, organization theorists have investigated it. Developments on management preferences that are applicable at the functional level of the organization are useful for our development. The fundamental question is: What roles do managers play in the creation of manufacturing flexibility options? The consensus among organization theorists is that managerial decisions are rarely without management's own "coloration" (e.g., Hambrick and Mason, 1984). Therefore, the creation of flexibility options will be influenced by the preferences of managers. Management preferences exist at all levels within an organization. Just as the CEO of an organization can decide to create a corporate option, the manufacturing vice-president can decide to create a manufacturing flexibility option. Building on work in the field of organizational behavior, Fry and Killing (1995) note that there are three key determinants of m anagement preferences: (1) the basic needs of the managers (i.e., the set of fundamental needs that shape an individual's personality and behavior), (2) the beliefs of managers about themselves, their organization, and the right way of doing business, and (3) the job context within which managers make decisions, which includes the position of the manager in the organization and the responsibilities of the job, along with the expectations of bosses, peers and subordinates. It is these key determinants that will guide the preferences of the manufacturing manager and, in so doing, influence the creation of manufacturing flexibility options. Table I presents these three dimensions d the corresponding elements of management preferences.

Time Dependency

Sharp (1991) notes that the value of an option increases with the duration of the option, although at a diminishing rate. However, to be truly competitive, the manufacturing function must create options that provide short-term and long-term solutions. Overall, manufacturing flexibility options can be classified as short-term and long-term (Ramasesh and Jayakumar, 1991; Upton, 1995; Olhager, 1993). Short-term options must be exercised quickly to provide acceptable tangible returns. For example, a product improvement created by a software developer may have a short window of opportunity within which to capitalize on the product. It will only be a matter of months, perhaps less, before the competition usurps the value embedded in this option. As another example, consider a footwear manufacturer that negotiates with its suppliers to lower their prices in the next three months should the footwear manufacturer need help during an anticipated slump in the market. Or, consider a bank that works out an agreement with the local high school to provide temporary help during the next summer season. These are examples of the creation of short-term options that expire in the near future and do not have the potential to provide long-term returns to the organization. If the manufacturer of athletic footwear had invested in building strong relationships with its suppliers, or if the bank had invested in the creation of a reputation in the marketplace of being a "good place" for high-school students to spend their summer, they may have created long-term options that could be exercised to provide enduring returns for the organization several years into the future.

Researchers have noted that long-term options, if created appropriately, tend to be more valuable to the organization than short-term options. However, this does not mean that there is no place for short-term options in the manufacturing manager's repertoire. The reality is that the manufacturing function will have to configure a mix of short- and long-term options that best meets its needs. This raises two issues concerning the time dependency of an option. The first is the obvious need to create a mix of short- and long-term options. The second issue is the need to appropriately time the creation of each option. This implies that if option creation data are analyzed over a shorter period of time, it may display some variations in the mix of short- and long-term options. However, over longer periods the mix of options may display a more stable and distinguishable pattern. Researchers (e.g., Bowman and Hurry, 1993) have argued that the choice of mix and timing of creation are decisions made by managers throug h a process of retrospective sense-making, and are moderated by their mental models (Senge, 1994) of reality and their own preferences.

An Organizational Framework for the Creation of Manufacturing Flexibility

The Fundamental Relationships

Prior research has focused on the relationship between environmental uncertainty and manufacturing flexibility (Gerwin, 1993; Upton, 1995). However, as noted earlier, the preference of managers (Fry and Killing, 1995) is another important factor that influences the development of manufacturing flexibility. This relationship has been hypothesized at the organizational level (Hambrick and Mason, 1984) but has received only limited empirical testing. Therefore, I will begin by creating a base model that extends the established relationship between environmental uncertainty and manufacturing flexibility to include managerial preferences. It is posited that both environmental uncertainty and management preferences are unique dimensions that influence the creation of manufacturing flexibility options.

P1: The level of manufacturing flexibility developed by an organization will depend on the level of uncertainty in the manufacturing environment and on the preferences of its manufacturing managers.

Summarizing earlier research, Russell and Taylor (1998) argue that the manufacturing function should be viewed as the "technical core" of an organization. Because of the perceived need to defend the technical core of the organization, managers intentionally isolate it from the external environment by using other departments like sales, marketing, finance, and purchasing, as buffers. In addition, the nature of their job sensitizes managers to internal uncertainty much more than it does to external uncertainty. For example, a line manager may spend weeks debating the need to create manufacturing flexibility options that will help him/her wade through volatile economic conditions. However, the same manager is quick to sense uncertainty arising from another department and has no hesitation creating necessary flexibility options to deal with it. Hence, it is argued that the manufacturing manager's decisions to create options are preferentially linked to uncertainties in other departments in the organization rather than to conditions in the external environment of the firm (Skinner, 1996). This leads to the belief that internal uncertainty would be more influential in developing manufacturing flexibility than external uncertainty. Based on the prevalent model of managing organizations one expects that:

P2: Manufacturing flexibility will be more strongly correlated with internal environmental uncertainty than with external uncertainty.

Moderating Effects of the Option Scanning Process and of Management Preferences

How exactly do uncertainty and management preferences affect manufacturing flexibility? While researchers have recognized the relationship between these constructs, not much work has been done to assess how the relationship is structured. Uncertainty in the environment presents the manufacturing manager with a set of manufacturing flexibility needs. For example, a proposed new strategic thrust by the marketing department creates internal uncertainty for the manufacturing department. This uncertainty signals the need to create manufacturing flexibility options. Similarly, uncertainty in the demand for the organization's product creates external uncertainty that also signals the need to create manufacturing flexibility options. To handle these uncertainties, manufacturing managers will need to create options in one or more of the four dimensions of manufacturing flexibility identified earlier in this article--volume flexibility, variety flexibility, process flexibility and material-handling flexibility. They wi ll scan sources and environments where they expect to find option-creating opportunities. This is followed by the identification of a set of viable options along each dimension. Bowman and Hurry (1993) note that this occurs through a process of retrospective sense-making. However, the ability to identify an appropriate number of flexibility options will necessarily depend on the quality and capability of the organization's process for scanning and recognizing these options. An organization may have the resources necessary to create flexibility. However, it may never achieve the needed flexibility because of the inadequacy of its option-scanning and recognition processes. Therefore, it is posited that:

P3: The relationship between uncertainty in the manufacturing environment and the level of manufacturing flexibility will be moderated by the effectiveness of the option-scanning and recognition processes of the manufacturing function.

Once the set of viable options is identified, managers have to make choices. During this process, they work with the evidence presented by the option-scanning process and supplement it with their own insights and preferences. Consider a situation in which a manager is presented with two competing manufacturing flexibility options. Both options can be created with similar levels of investment. However, option A displays a slightly lower level of risk than option B. In such a situation, one would expect option A to be most likely selected. Yet our manager displays a preference for and ultimately selects Option B. The manager has exercised his/her preference. This example illustrates a common practical occurrence--management preferences moderate the selection of options. Thus, it is posited that:

P4: The relationship between uncertainty in the manufacturing environment and the level of manufacturing flexibility is moderated by management preferences.

Next, let us consider what happens as uncertainty in the manufacturing environment increases. Visualize, first, the case of an organization in an industry known to have a significant but predictable seasonal demand pattern. Since the magnitude of seasonal swings is predictable, uncertainty is deemed to be low. The manufacturing manager has the necessary information to control costs and may not need to create flexibility options. Now, consider another situation in which the fluctuations in the demand are significant but do not follow a discernable pattern. In such a situation, the manager may want to invest in the creation of several options that would allow the organization to respond appropriately to future demand scenarios. However, such investments cost money, and unused options expire without providing tangible returns. While it may be true that the cost of creating an option is relatively low, if undertaken on an ongoing basis, the costs add up. Efficient and appropriate selection of options becomes a pr iority of the organization. This implies that as environmental uncertainty increases, the option-scanning process and preferences of managers will play roles that are more significant in the creation of manufacturing flexibility options. Therefore, it is posited that:

P5: The moderating effect of management preferences and the option-scanning process will increase as the level of environmental uncertainty increases.

Time Dependency of the Chosen Options

The literature recommends that managers strive to create long-term options. In support, Upton (1995) notes that managing flexibility in the short run has not consistently led to the type of long-term flexibility needed by the organization. However, as noted earlier, such recommendations may not always be practical. Firms typically do need to hold a mix of short- and long-term options, and in general, the theoretical universe of short- and long-term options held by an organization increases as the level of environmental uncertainty increases.

Let us consider the effect of internal uncertainty on the mix of manufacturing flexibility options. Consider the purchase of a machine by the manufacturing function. Over time, this machine will age and gradually become less reliable. Managers will create a mix of options to deal with the reliability problem. It is posited that as uncertainty increases over the life of the machine, the increase in short-term and long-term options may not increase proportionally, and that the number of short-term options held by an organization over the life of that resource will follow a curvilinear pattern. In our example, during the first few years, when operational uncertainty is low, the organization is unlikely to hold any short- or long-term flexibility options. However, during early mid-life of the machine, uncertainty about the machine's capability increases. The organization now begins to look more closely at creating short-term options that will help them handle minor machine lapses. Several such options are availab le. Dedicating maintenance hours to this machine and strategic alliances with other parties to subcontract the activities undertaken on this machine at short notice are two such options. Managers may also consider long-term options. However, limited visibility on the business horizon may hinder the valuation of these long-term options and hence delay their selection or creation.

As the machine reaches the latter part of its mid-life, visibility on the business horizon becomes clearer and managers will begin to look closely at some long-term options. For example, they could create a financial option for a major overhaul of the machine, or for the purchase of a new one. Finally, as the machine nears the end of its expected life, machine failure and serious disruption of manufacturing operations are no longer uncertain. They are predictable. At this stage, the creation of additional flexibility options adds little value. There is only a need to exercise the option that was created earlier (overhaul machine or make a new purchase) and start the investment's life cycle once again.

Thus, at very low levels of uncertainty managers will be comfortable not holding any options. However, as the environmental uncertainty increases there will be a tendency by managers to gravitate toward creating short-term options. As environmental uncertainty increases to even higher levels, the set of feasible short-term options becomes less attractive, while visibility on the horizon simultaneously begins to clear. This induces managers to look for options that will provide long-term relief. Therefore, it is posited that,

P6: As uncertainty in the manufacturing environment increases, the number of short-term options in the mix of flexibility options owned by the manufacturing function will increase up to a point after which the number of short-term options in the mix will begin to decrease.

Toward A Framework of Factors That Induce Manufacturing Flexibility

The theoretical developments presented above are an attempt to systematically codify what is perceived to be a complex process of creating an appropriate mix of manufacturing flexibility options. Figure II provides a consolidated framework for the process. It builds on accepted theory in operations management, real-option theory and organization theory to trace the influence of key antecedents in the creation of manufacturing flexibility options. The rationale for the model is presented below.

In line with current research, Figure II presents uncertainty in the manufacturing environment as the primary driver of the creation of manufacturing flexibility options. This environmental uncertainty has an external component and an internal component. In the framework, the option identification screen follows the environmental uncertainty driver. Clearly, unless managers recognize and identify options, they cannot create the options. A key input to operationalizing this screening process is the option-scanning and recognition system instituted by the firm. Such a system could be formally structured, similar to those often found in larger or older firms, or it could be informally structured, similar to those found in smaller or younger firms. The option identification screen identifies and pre-screens viable options, usually based on payoff expectations. The screening process gives managers a pool of options that they could but do not necessarily have to create. The preferences of managers usually drive the actual option selection process. Hence, Figure II depicts an option selection screen governed by management preferences. The outcome of the scanning, recognition and selection processes is presented as a 2 X 2 matrix in Figure II ([n.sub.1], [n.sub.2], [n.sub.3] and [n.sub.4], represent the basket of resulting options in each cell). The matrix represents a mix of short-term and long-term options and reflects the time-dependent characteristics of manufacturing flexibility options. In addition, these options address the four dimensions of manufacturing flexibility--volume flexibility, variety flexibility, process flexibility and materials-handling flexibility.

Summary, Discussion and Suggestions for Future Research

Researchers have established the relationship between manufacturing flexibility and uncertainty. This connection is logical. If there is uncertainty, then organizational nimbleness, or flexibility, is a solution. What is surprising is the other antecedents of manufacturing flexibility have not been adequately addressed. In an attempt to systematically codify the process of creating manufacturing flexibility, I have highlighted three key components that influence the way in which the manufacturing function deals with environmental uncertainty. The first component is the option-scanning and recognition system. This system is dependant on many factors, including, but not limited to, the degree of departmentalization, centralization, the effectiveness of organizational communication, and the quality/quantity of information captured and distributed by the management information system, and the sense-making that integrates them (Bowman and Hurry, 1993). The second component is management preferences. These prefere nces result from the manager's basic needs, the manager's beliefs, and the organizational context, and reside in what is often called the mental-model of the manager (Senge, 1994). Exactly how these factors affect the relationship between uncertainty and manufacturing flexibility is not clear at this time. Indeed, until now, there has not been an integrated framework that account for them. Finally, the time dependency of a flexibility option induces managers to selectively create a mix of short- and long-term manufacturing flexibility options that meet the needs of the organization.

Agenda for Future Research

This paper is a call for more structured investigations into the relationship between environmental uncertainty and manufacturing flexibility. Six propositions on the relationship between environmental uncertainty, management preferences, and manufacturing flexibility were developed as a lead-in to further investigation and empirical testing. The preliminary framework presented in this article provides one interpretation on how managers configure manufacturing flexibility. Empirical research is needed to refine the framework. In the following paragraphs, I will review areas that would benefit from such research.

A review of the manufacturing literature indicates that researchers have not adequately integrated the preferences of manufacturing managers into their frameworks for manufacturing flexibility. This needs to change. The critical role played by management preferences suggests that there is a need for research that investigates this construct. Research effort aimed at operationalizing and measuring this construct at the manufacturing level is the first step. Linking this construct with manufacturing flexibility is the next step. Only then, can we move forward and address more interesting questions. For example, are there specific components of management preferences that are more influential than others in determining manufacturing flexibility options?

There is limited research on the process of creating manufacturing flexibility. Additional work is also needed on the outcomes of the process of creating manufacturing flexibility. For example, can we say something about the relationship between the mix of short-term/long-term options and the performance of the manufacturing function of the organization? Do short-term options ([n.sub.1] and [n.sub.3] in Figure II) provide greater flexibility/performance than long-term options ([n.sub.2] and [n.sub.4] in Figure II), or vice versa? Is there an optimal balance in the mix of short-term and long-term manufacturing flexibility options? Is it possible to identify a generalizable typology of short-term and long-term flexibility options? Answers to these questions would be valuable to both researchers and practicing managers.

One of the more challenging areas of research is the uncertainty that emanates from other functional areas of the organization. There exists very limited research in this area. We must attempt to understand how the manufacturing function deals with such internal uncertainty. Indeed, if the manufacturing function is significantly affected by such uncertainties, as proposed in this article, the need to understand these inter-departmental relationships is even greater. The supporting or constraining role of the rest of the organization on the manufacturing function is an area that needs to be researched further.

There is need for research that explores how manufacturing managers scan and recognize manufacturing options. This area has not received much research attention. I have hypothesized that the quality of manufacturing flexibility created by manufacturing managers is moderated by the quality of the scanning and recognition process. The development of efficient and effective systems to undertake this process could translate to higher levels of manufacturing performance and would be extremely valuable to the practicing manager. It is therefore essential that researchers address this important topic. For example, how does one operationalize the option-scanning process at the manufacturing level? What are the key steps/tasks in this process? How do the structure and culture of the organization impact the scanning and recognition process? What technologies (e.g., artificial intelligence, mathematical modeling, statistical techniques) are available to assist managers to undertake this task? Answers to these questions will provide a clearer picture of the process of creating manufacturing flexibility.

The creation of manufacturing flexibility options is not the result of individual managers unilaterally responding to changes in the environment. The structure of the organization, its policies and its procedures play a part in this process. In addition, the personal attributes of the decision makers and the ways in which decision makers interact influence the creation of options. The framework that has been proposed in this article provides a canvas that is more inclusive than those that were previously developed. It is hoped that the framework will provide researchers with the theoretical foundation necessary to expand their investigation on the antecedents of manufacturing flexibility. It is also hoped that the article will provide practicing managers new insights into the creation of manufacturing flexibility in their own organizations.

[FIGURE 2 OMITTED] TABLE I Determinants of Manufacturing Flexibility CONSTRUCTS DIMENSIONS ELEMENTS

1. External * Resource and supplier-

Uncertainty based uncertainty

* Manufacturing technology-

based uncertainty

* Products-based uncertainty

* Uncertainty in the

competitor area

* Demand-based uncertainty Environmental * Manufacturing Domain Uncertainty * Machine/equipped breakdowns

* Variability in task times

* Fluctuations in output quality

2. Internal * Non-manufacturing Domain

Uncertainty * Marketing

* Sales and distribution

* R&D

* Finance and accounting

* Purchasing

* Others

1. Basic Needs * Need for affiliation and

recognition

* Need for achievement

* Need for power Management 2. Beliefs of * Beliefs about self Preferences Managers * Beliefs about organization

* Beliefs about environment

3. Job Context * Position and responsibilities

* Expectations of bosses, peers

and subordinates

* Organizational goals and

strategies Time Dependency * Short-term

* Long-term

* I would like to thank Fredrick Williams for his assistance on earlier drafts of this article.

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