Sunday, April 08, 2007

Organizational Environmental Uncertainities

From the genesis of management studies it has been recognized that organizations do not operate in a vacuum. In the seminal work, The Functions of the Executive, Chester Barnard (1938) theorized that an organization’s survival was dependent on its ability to sustain a balance with its external environment by readjusting its internal processes to match the various elements in the environment (Barnard, 1938, p. 6). In recognition of Barnard’s observation that firms must maintain equilibrium in an ever-changing environment, a considerable body of literature has developed that is devoted to conceptualizing and comprehending the external environment and its role in management theory.
Numerous conceptualizations of environmental uncertainty have been explored in the literature (e.g. Barnard, 1938; Thompson, 1967; Lawrence and Lorsch, 1967; Duncan, 1972; Pfeffer and Salancik, 1978; Milliken, 1987; Tan and Litschert, 1994). The majority of these have rested on one of two dominant perspectives: information uncertainty or resource dependence theory (Tan and Litschert, 1994). The information uncertainty perspective is derived directly from Barnard (1938) and is built on the assumption that uncertainty arises from a lack of perfect information about the environment. Researchers adopting this perspective in their theory building include Lawrence and Lorsch (1967), Thompson (1967), Duncan (1972), Milliken (1987), and Dickson and Weaver (1997).
Barnard’s conceptualization of environmental uncertainty dominated discourse in this area of management theory until the early 1970s, when another school of thought began to develop with Child (1972). Child attributed environmental uncertainty primarily to organizational dependence on resources and argued that uncertainty arises as firms attempt to manage critical resource flows from partners who have varying degrees of power (Pfeffer and Salancik, 1978). Researchers whose work has primarily focused on this aspect of environmental uncertainty include Child (1972), Pfeffer and Salancik (1978), Dess and Beard (1984), and Finkelstein (1997).
Throughout the last three decades both schools of thought have made significant contributions to the field of management studies. However, scholars employing either theoretical lens have encountered a significant challenge in the operationalization of the environmental uncertainty construct (Milliken, 1987; Gerloff et al., 1991). Early efforts to capture environmental uncertainty tended to employ relatively simple, unidimensional measures. Over time, measures of environmental uncertainty have tended to become increasingly complex with numerous contemporary researchers (e.g. Steensma et al., 2000) utilizing multidimensional tools. Unfortunately, as the various conceptualizations and operationalizations of uncertainty have evolved, the true meaning of the construct has become muddled (Milliken, 1987; Koberg and Ungson, 1987; Tan and Litschert, 1994). The fundamental concern raised by these developments is that the environmental uncertainty construct may soon be stretched beyond usefulness, as it becomes so broad as to be fundamentally meaningless.
The first step in rectifying this disturbing trend is to return to the nascent stages of environmental uncertainty research and to examine the historical evolution of this concept and its operationalizations. Analyzing the historical development of environmental uncertainty is an essential undertaking, as the “study of evolving management thought can provide the origins of ideas and approaches, trace their development … and thus provide a conceptual framework which will enhance the process of integration. A study of the past contributes to a more logical, coherent picture of the present” (Wren, 1979, p. 4).
Management history also plays an important role in determining the true meanings of key management concepts (McMahon and Carr, 1999; Rutgers, 1999). Koontz (1996) claimed that imprecise terminology is one of the most significant problems currently inhibiting organizational research. He argued “as is so often true when intelligent men argue about basic problems, some of the trouble lies in the meaning of key words. The semantics problem is particularly severe in the field of management” (Koontz, 1996, p. 27). This semantics problem poses a significant threat to research on the environmental uncertainty construct. If the study of environmental uncertainty is to continue making a significant contribution to the field of management studies, then it is imperative that researchers be made aware of the fundamental elements of the uncertainty construct present in these various conceptualizations.
This paper presents a systematic analysis of the historical development of the uncertainty construct and evaluates its current state. Utilizing the early environmental literature, the authors trace the development of environmental uncertainty over the last 60 years. The rise of the information uncertainty and resource dependence schools are explored, as is the evolution of the construct’s operationalizations from simple to complex measures. The insights provided by this analysis form the basis of a categorization scheme for conceptualizations and operationalizations of the uncertainty construct. This categorization scheme provides insight into the fundamental elements of the environmental uncertainty construct and enables future researchers with a tool to ensure greater precision and consistency in the use of this construct.
Early conceptualizations of environmental uncertainty
In the management literature, the external environment can be broadly defined as “the totality of physical and social factors that are taken directly into consideration in the decision-making behavior of individuals in organizations” (Duncan, 1972, p. 314). Organizational researchers have long theorized that the overall environment consits primarily of several independent components (e.g. Duncan, 1972; Miles and Snow, 1978; Hambrick, 1982). Among the most significant elements that were theorized to exist in the external environment were customers, competitors, government regulations and labor unions. While the individual components that made up each researcher’s conception of the environment were not always the same, each conception agreed that the various environmental elements acted to create uncertainty for firms.
Chester Barnard (1938) was one of the first management scholars to explore the relationship between firms and their external environment. In his work, The Functions of the Executive, Barnard examined the impact that environmental uncertainty had on organizational strategies. Barnard believed that the physical environment was inherently unstable and that this instability created strategic uncertainty for firms. He argued that the primary reason for this uncertainty was the inability of managers to comprehend all the information present in a given environmental situation. Barnard felt that “under most ordinary conditions, even with simple purposes, not many men can see what each is doing or the whole situation” (Barnard, 1938, p. 106). This lack of perfect information about the environment posed significant problems for both firms and managers as it created ambiguity during the strategic decision making process.
Barnard believed that organizations should survey the opportunities and threats present in the external environment before deciding whether to operate in that environment. He argued that interacting or not interacting “with a particular environment centers on the identification of the key strategic factor and the ability of the organization to provide the missing factor, or to be able to effectively match the current capacities of the organization with the key strategic factor in such a way as to create an advantageous opportunity for the organization” (McMahon and Carr, 1999, p. 233).
Simon (1957), March and Simon (1958), and Cyert and March (1963) expanded on the work of Barnard contending that managers were forced to make decisions under conditions of “bounded rationality.” Bounded rationality concerns itself with organizational processes related to the “choice of courses of action in an environment which does not fully disclose the alternatives available or the consequences of those alternatives” (Thompson, 1967, p. 9). A logical result of bounded rationality is that managers and firms are not able to fully understand complex environments, and are forced to make decisions while possessing incomplete information about their strategic options.
Two dominant perspectives: information uncertainty and resource dependence theoryInformation uncertainty perspective
In the 1960s, authors further elaborated on the information uncertainty perspective developed by Barnard. Lawrence and Lorsch (1967) and Duncan (1972) both argued that imperfect knowledge about the environment created uncertainty for firms. It was also posited that managers would perceive the environment in ways that were consistent with their training and personal characteristics. As such, managerial perceptions played a significant role in determining the amount of uncertainty managers perceived in the environment.
Within the information uncertainty school of thought, Lawrence and Lorsch (1967) defined three components of environmental uncertainty. The first component, based on the work of Barnard, was the lack of clear information available about the external environment. The second component was the long time span required for feedback after strategic action. Even after a firm had formulated and implemented a strategy, it still might not be sure if it had achieved a fit with its external environment. The final component was the general uncertainty inherent in causal relationships. It was very difficult for firms to accurately predict the effects that specific strategic actions would have on the external environment, and also what effect environmental changes would have on the firm.
Duncan (1972) argued “uncertainty and the degree of complexity and dynamics of the environment should not be considered as constant features in any organization. Rather, they are dependent on the perceptions of organization members and thus can vary in their incidence to the extent that individuals differ in their perceptions” (Duncan, 1972, p. 325). He believed that the overall amount of uncertainty present in the environment was determined by managerial perceptions of that environment.
Managerial perceptions of environmental uncertainty can also be influenced by the importance managers assign to certain environmental variables. As Hitt et al. (1982) explained, “the recognizable pattern of organizational responses to environmental conditions is determined not so much by the objective characteristics of the organization-environment interactions as by managerial perceptions of the strategic importance of the critical areas contained within different organizational functions” (Hitt et al., 1982, p. 270). Thus, organizations will respond to environmental factors that they judge as having a high degree of importance to firm survival.
The common theme unifying the works of Barnard (1938), Lawrence and Lorsch (1967), and Duncan (1972) was the belief that it was impossible for a firm to acquire perfect knowledge about its environment and this lack of information created uncertainty for the firm. The threats and opportunities that managers perceived to exist in the external environment ultimately determined a firm’s choice of strategic actions and influenced a firm’s evaluation of its strategic options. As perceptions can directly influence the firm’s actions, researchers in the information uncertainty school were not especially concerned with the objective environment (Sharfman and Dean, 1991).
Consistent with their argument that managerial perceptions ultimately shape strategy formation, researchers in the information uncertainty school have typically employed perceptual measures of uncertainty (Duncan, 1972; Miles and Snow, 1978; Tung, 1979; Hrebiniak and Snow, 1980; Milliken, 1987; Daft et al., 1988; Sawyerr, 1993; Buchko, 1994; Dickson and Weaver, 1997). These researchers “objected to the use of objective measures of environmental uncertainty. They argue[d] that firms respond to the environment perceived and interpreted by the decision makers and that the environmental conditions that are not noticed do not affect management’s decisions nor actions” (Sawyerr, 1993, p. 290).
Resource dependence theory
In the early 1970s researchers began to question whether managers were able to accurately perceive the threats and opportunities actually present in the external environment. Scholars soon began to search for a more objective method of operationalizing the environmental uncertainty construct. Attempting to solve this dilemma, researchers in the 1970s began to explore resource dependency as a more objective measure of the uncertainty that organizations faced when dealing with their environment.
Pfeffer and Salancik (1978) utilized the previous environmental literature to develop resource dependence theory. Resource dependence theory is based on the notion that environments are the source of scarce resources and organizations are dependent on these finite resources for survival. A lack of control over these resources thus acts to create uncertainty for firms operating in that environment. Organizations must develop ways to exploit these resources, which are also being sought by other firms, in order to ensure their own survival.
According to Pfeffer and Salancik (1978):
… the elemental structural characteristics of environments are concentration, the extent to which power and authority in the environment are widely dispersed; munificence, or the availability or scarcity of critical resources; and interconnectedness, the number and pattern of linkages, or connections, among organizations. These structural characteristics, in turn, determine the relationships among social actors – specifically, the degree of conflict and interdependence present in the social system. Conflict and interdependence, in turn, determine the uncertainty the organization confronts (Pfeffer and Salancik, 1978, p. 68).
Pfeffer and Salancik determined three factors that influenced the level of dependence organizations had on particular resources. First, the overall importance of the resource to the firm was critical in determining the resource dependence of the firm. Second, the scarcity of the resource was also a factor. The more scarce a resource was, the more dependent the firm became. Finally, another factor influencing resource dependence was the competition between organizations for control of that resource. Together, all three of these factors acted to influence the level of dependence that an organization had for a particular resource.
Resource dependence theory also inferred that a firm’s strategic options were determined to a great extent by the environment. Since firms were dependent on the environment for resources, they needed to enact strategies that would allow them to acquire these resources. Therefore, the external environment had already been determined for these firms, and they experienced little strategic choice. However, those who supported the notion of managerial choice argued that some organizations were more effective than others in the same environments, thus proving that strategic choice did exist.
Hrebiniak and Joyce (1985) argued that strategic choice and environmental determinism did not have to be mutually exclusive. They reasoned, “control over scarce resources is central to the relationship between choice and determinism” (Hrebiniak and Joyce, 1985, p. 343). Lawless and Finch (1989) found limited support for the model developed by Hrebiniak and Joyce, stating that “parts of the model were not supported by our analysis, and that further questions … are actually raised” (Lawless and Finch, 1989, p. 361). Bedeian (1990) argued that neither argument is completely accurate, as “organizational adaptation is an ongoing, multi-directional relationship in which organizations neither mechanistically react to environmental forces nor exercise unrestricted free will (strategic choice)” (Bedeian, 1990, p. 571).
Within the resource dependence school, the environment was seen as the source of scarce resources that were critical to a firm’s survival. It was the lack of control over these critical resources, rather than a lack of information, that gave rise to environmental uncertainty. Environments that contained high levels of resources were perceived as less hostile to the stability of organizations, whereas those with low levels of resources acted to increase the intensity of competition among firms. Accordingly, resource dependence theorists argued that in order to reduce the impact of this environmental uncertainty on organizational performance, it was necessary for organizations to develop and sustain effective relationships with their external environment.
Perceptual versus archival measures of uncertainty
In operationalizing the environmental uncertainty construct, researchers in the resource dependence school have utilized both perceptual and archival measures of environmental uncertainty. However, archival measures have been most commonly employed to yield an objective measure of resource hostility (Dess and Beard, 1984; Yasai-Ardekani, 1989; Boyd, 1990; Wiersema and Bantel, 1993; Goll and Rasheed, 1997; Simerly and Li, 2000). These authors believed that the scarcity of resources in an environment was an objective reality, and thus needed to be measured objectively. Yasai-Ardekani (1989, p. 133) stated that “environmental munificence and scarcity refer to the objective condition of an environment and were thus measured with objective industry-demand data”.
A limited number of researchers have instead used perceptual scales in order to measure the level of environmental resource dependence (Koberg, 1987; Koberg and Ungson, 1987; Tan and Litschert, 1994; Tan, 1996). In a study of the joint effects of environmental uncertainty and resource dependence, Koberg and Ungson (1987) claimed that “consistent with the argument that perceptions of organizational contingencies and not objective properties determine decision-making behavior, two perceptual measures of environment were employed. One was a measure of environmental uncertainty … the other was a measure of environmental resource dependence” (Koberg and Ungson, 1987, p. 729).
Simple and complex measures of environmental uncertainty
As conceptualizations of environmental uncertainty have continued to evolve in the management literature, so too have operationalizations of uncertainty. Since the seminal works in the information uncertainty and resource dependence schools both posited that only one primary source of uncertainty existed in the external environment, researchers utilized simple measures to operationalize the uncertainty construct. As research in this area matured, scholars increasingly argued that several factors acted together to determine the total amount of uncertainty a firm faced in the environment. To reflect this belief and to form a more comprehensive view of uncertainty that had been lacking in the early literature, multidimensional operationalizations of uncertainty were developed (Milliken, 1987; Tan and Litschert, 1994).
Thompson (1967), in Organizations in Action, argued “uncertainty appears as the fundamental problem for complex organizations and coping with uncertainty, as the essence of the administrative process” (Thompson, 1967, p. 159). He conceptualized a firm’s external environment in terms of two main dimensions: heterogeneity/ homogeneity and stability/dynamism. A heterogeneous environment consisted of many elements that were different in nature; a homogeneous environment contained very similar elements. The stability/dynamism dimension referred to the rate of change present in the environment. A dynamic environment changed at a very rapid pace and thus created a great deal of uncertainty for firms; a stable environment typically remained unchanged and was therefore more predictable.
Duncan (1972), employing the works of Emery and Trist (1965) and Thompson (1967), also argued that there were two main dimensions along which the environment could be measured. Duncan called these the simple-complex dimension and the static-dynamic dimension. The simple-complex dimension measured the number of factors that were present in the environment. A simple environment consisted of a small number of key factors; a complex environment contained many different defining factors. The static-dynamic dimension of the environment was concerned primarily with the amount of change in these factors. A static environment experienced little or no change, while a dynamic environment was in a constant state of change.
Child (1972) utilized three dimensions to conceptualize the external environment. His first two dimensions were similar to those theorized by Thompson (1967) and Duncan (1972), measuring both rate of change and complexity. However, he also drew upon the resource dependence literature to develop a third dimension called “illiberality.” Illiberality referred to the overall availability of resources in the external environment.
Dynamism, complexity and munificence
Integrating the work of previous authors, Dess and Beard (1984) employed three environmental dimensions in their measure of uncertainty. These three dimensions, which were very similar to those developed earlier by Child, were “dynamism,” “complexity,” and “munificence.” The first dimension, “dynamism,” referred to the “rate of change and innovation in an industry as well as the uncertainty or predictability of the actions of competitors and customers” (Miller and Friesen, 1983, p. 222). Dynamism in Dess and Beard’s measure was similar to the stability/dynamism dimension of Thompson’s measure, the static-dynamic element of Duncan’s, and the variability component of Child’s.
The second dimension of Dess and Beard’s measure was “complexity.” Complexity referred to “the level of complex knowledge that understanding the environment requires” (Sharfman and Dean, 1991, p. 683). This dimension was concerned with the overall number of factors that a firm needed to analyze in its external environment. Thompson’s heterogeneity/homogeneity dimension and Duncan’s simple-complex component were both very similar to complexity. As the number of environmental factors that must be considered by a firm increased, so did the level of uncertainty present in the environment.
The final component of Dess and Beard’s (1984) operationalization was “munificence,” also known as hostility. This dimension was not part of the earlier constructs developed by Thompson and Duncan, and was referred to as “illiberality” by Child. Munificence described “the level of resources available to firms from various sources of the environment” (Tan, 1996, p. 33). Covin and Slevin (1989) argued, “hostile environments are characterized by precarious industry settings, intense competition, harsh, overwhelming business climates, and the relative lack of exploitable opportunities” (Covin and Slevin, 1989, p. 75).
According to these authors, the concepts of dynamism, hostility, and complexity could be utilized in order to measure the level of uncertainty present in a given environment (Table I). High levels of dynamism, hostility, and complexity all acted to create high levels of uncertainty. Low levels acted to reduce the overall amount of environmental uncertainty. By analyzing the levels of dynamism, hostility, and complexity present in an environment, firms were able to formulate and implement strategies to match these environments.
State, effect and response uncertainty
Extending the multidimensional conceptualization of environmental uncertainty, Milliken (1987) built on the work of Lawrence and Lorsch (1967) to develop a measure that distinguished between three types of uncertainty that existed in a firm’s external environment. Milliken’s typology included “state uncertainty,” “effect uncertainty,” and “response uncertainty.” “State uncertainty” referred to the general unpredictability of the environment and its various components. “Effect uncertainty” was the inability of firms to predict the effect of future environmental changes on their business operations. “Response uncertainty” captured the difficulty firms had in predicting the response of their competitors to a particular strategy that the firm implemented. According to Milliken, these three concepts acted together to determine the overall level of uncertainty present in a firm’s external environment.
Analyzing key elements of the uncertainty construct: a new categorization scheme
An examination of the evolution of the conceptualization and operationalization of the environmental uncertainty construct reveals that the seminal works on uncertainty can be categorized according to two predominant factors:
the primary source of uncertainty theorized by the author (i.e. information uncertainty or resource dependence); and
the complexity of the measure employed to operationalize this uncertainty (i.e. simple versus complex).
Figure 1 summarizes the major works on environmental uncertainty according to these two factors.
It is important to note that while operationalizations of environmental uncertainty have become more complex with time, simple measures can still significantly contribute to organizational research. Indeed, depending on the research questions under consideration the operationalizations of environmental uncertainty in each sector of this figure have the potential to address critical issues. Issues that delineate the appropriateness of each measure include whether uncertainty is a primary or secondary variable of interest and the characteristics of the population under consideration, including firm and industry level factors.
Simple measures are useful when uncertainty is a secondary variable of interest and only broad analyses are necessary. These measures of uncertainty tend to be less precise than complex measures, but are generally easier to calculate. Multidimensional operationalizations are useful when uncertainty is the primary variable of interest. These measurements tend to be more comprehensive than those attained through simpler methods and provide a more complete set of information for the researcher.
Characteristics of the population under consideration provide a useful indication of whether a researcher should employ measures from the information uncertainty or resource dependence schools. Information uncertainty measures are useful in studying firms that are dependent on information for their economic prosperity, such as those in technology-based industries (i.e. Internet firms, the electronics industry, etc.). These firms tend to be agile and flexible, and usually operate in highly competitive industries. Resource dependence theory provides an effective tool for measuring the uncertainty faced by firms in resource-intensive industries (i.e. mining, manufacturing, etc.). These firms tend to have larger, more traditional organizational structures and are less dependent on technology for their survival.
Figure 2 summarizes the primary research situations in which measures from the four different quadrants should be utilized. It also lists examples of recent articles that have productively employed each particular operationalization.
The first quadrant (information uncertainty/simple measure) of this matrix contains measures useful when studying firms competing in information-based industries, where only a general measure of uncertainty is needed. For example, Bergh and Lawless (1998) employed a very simple measure of uncertainty in an article related to firm diversification. The authors calculated uncertainty as the change in net sales over a given period of time. Although this did not provide a very precise measure of environmental uncertainty, it was sufficient to support their findings that uncertainty affects the relationship between diversification strategy and portfolio restructuring (Bergh and Lawless, 1998, p. 98).
The measures in the second quadrant (information uncertainty/complex measure) allow for a much more precise measurement of uncertainty. Boyd and Fulk (1996) employed a very sophisticated measurement of information uncertainty in their study. They developed four perceptual measures to gauge the amount of uncertainty present in the environment: the adequacy of information available about the environment, and the overall analyzability, predictability, and variability of the environment. Given their particular research situation, their findings supported modeling uncertainty “with multiple indicators” (Boyd and Fulk, 1996, p. 14).
The third quadrant (resource dependence/simple measure) contains operationalizations that can be effectively utilized while performing research on traditional firms in resource-intensive industries. Finkelstein (1997) examined resource dependence theory by utilizing a basic construct developed by Pfeffer (1972). Similar to Pfeffer’s seminal work, Finkelstein measured inter-industry mergers in the context of resource dependence theory. Although their findings were not identical, Finkelstein concluded, “the basic resource dependence hypothesis on the relationship between interindustry transactions and mergers was supported” (Finkelstein, 1997, p. 808).
The fourth quadrant (resource dependence/complex measure) contains measures that should be employed when uncertainty is the primary variable of interest and resource availability is a major factor being considered. Lawless and Finch (1989) utilized a very complex construct in order to measure resource dependence theory. The authors used the values calculated by Dess and Beard (1984) to determine the validity of Hrebiniak and Joyce’s (1985) model of organization-environment relations. They measured munificence, complexity, and dynamism for all four environmental types proposed in the model. Their findings suggest, “relationships between returns and particular strategy types vary by environment” (Lawless and Finch, 1989, p. 360).
Although this is by no means an exhaustive list of the articles that have recently employed measures of environmental uncertainty, it is clear that each quadrant in this classification scheme has value in answering specific research questions. Simple measures are effective when uncertainty is a secondary variable of interest, while complex measures allow for precise measurements when uncertainty is the primary variable being studied. Operationalizations from the information uncertainty and resource dependence schools can also be effectively utilized when performing organizational research, depending primarily on the characteristics of the firm and industry being studied.
A decision tree for studying the environmental uncertainty construct
The categorization scheme developed in this paper provides a decision tree that can be utilized when studying the environmental uncertainty construct. First, the researcher must determine whether environmental uncertainty is the primary or secondary variable being studied. If uncertainty is the primary variable of interest, then the researcher should employ a complex measure in order to ensure more precision and comprehensiveness while measuring the construct. If uncertainty is only a secondary variable of interest, then researchers need only employ simple measures that are easier to calculate and provide more generalized information regarding the amount of uncertainty present in the external environment.
Second, the attributes of the firms and industry in the study must be closely examined. The primary focus of the researcher during this stage should be in determining whether a information uncertainty or resource dependence perspective more closely aligns with their specific research questions and sample characteristics. If the industry being studied tends to experience rapid change and the firms in this industry are dependent on information from the environment, then measures based on the information uncertainty perspective should be employed. If the change rate in the industry is slow and firms tend to be more dependent on acquiring environmental resources than information, then researchers should utilize measures developed from resource dependence theory.
After performing these two analyses, the organizational researcher can determine the measure of uncertainty that would be most appropriate in their study. Figure 3 provides a decision tree that can aid researchers in determining which of the four types of environmental uncertainty measures delineated in this article would be most appropriate for their purposes. For example, a researcher who is studying uncertainty as a primary variable of interest (thus needing a precise measure of uncertainty) and whose sample consists of firms in a rapidly changing, information-dependent industry (such as e-commerce), could choose from the measures of environmental uncertainty developed by Thompson (1967), Duncan (1972), or Milliken (1987). Thus, through the two-step process of determining whether uncertainty is a primary or secondary variable of interest, and analyzing the characteristics of the firms and industry being studied, organizational researchers can utilize the decision tree presented in Figure 3 to choose and employ measures of uncertainty that provide the richest information in their particular research situation.
Summary observations
Multiple operationalizations have developed over the last 60 years to measure the amount of uncertainty present in the external environment. Each of these measures can be effectively utilized in performing organizational research depending upon the specific research questions being addressed. This article has presented a systematic method for determining which measure should be utilized in a given research situation. While none of the four categories of measures discussed in this paper is perfect in every research situation, each can be effectively employed in specific situations to perform research on the topic of environmental uncertainty.
The most significant problem raised by this analysis is the threat of concept stretching in regard to the environmental uncertainty construct. As conceptualizations of uncertainty have continued to evolve and diverge from one another over the last 60 years, integrating research streams and ensuring the generalizability of results on this topic has become increasingly difficult. The categorization scheme and decision tree developed in this paper provide a starting point to reverse this unsettling trend.
Research on environmental uncertainty has several practical implications. In order to sustain organizational growth and survival, firms must be able to successfully interact with their external environment. One of the key factors in so doing is a firm’s ability to effectively handle the problems created by environmental uncertainty. By studying the topic of uncertainty, researchers are better able to understand the relationship that exists between an organization and its external environment. The categorization scheme presented in this paper provides a valuable tool for future investigation of the uncertainty construct. By determining the theoretical foundation of the question under consideration and the role of environmental uncertainty in the research model, investigators can employ this categorization scheme to choose the appropriate measure of environmental uncertainty.

Understanding Customer Relations Management

In the mid-twentieth century, mass production techniques and mass marketing changed the competitive landscape by increasing product availability for consumers. However, the purchasing process that allowed the shopkeeper and customer to spend quality time getting to know each other was also fundamentally changed. Customers lost their uniqueness, as they became an “account number” and shopkeepers lost track of their customers’ individual needs as the market became full of product and service options. Many companies today are racing to re-establish their connections to new as well as existing customers to boost long-term customer loyalty. Some companies are competing effectively and winning this race through the implementation of relationship marketing principles using strategic and technology-based customer relationship management (CRM) applications.
CRM technology applications link front office (e.g. sales, marketing and customer service) and back office (e.g. financial, operations, logistics and human resources) functions with the company's customer “touch points” (Fickel, 1999). A company's touch points can include the Internet, e-mail, sales, direct mail, telemarketing operations, call centers, advertising, fax, pagers, stores, and kiosks. Often, these touch points are controlled by separate information systems. CRM integrates touch points around a common view of the customer (Eckerson and Watson, 2000). Figure 1 demonstrates the relationship between customer touch points with front and back office operations.
In some organizations, CRM is simply a technology solution that extends separate databases and sales force automation tools to bridge sales and marketing functions in order to improve targeting efforts. Other organizations consider CRM as a tool specifically designed for one-to-one (Peppers and Rogers, 1999) customer communications, a sole responsibility of sales/service, call centers, or marketing departments. We believe that CRM is not merely technology applications for marketing, sales and service, but rather, when fully and successfully implemented, a cross-functional, customer-driven, technology-integrated business process management strategy that maximizes relationships and encompasses the entire organization (Goldenberg, 2000). A CRM business strategy leverages marketing, operations, sales, customer service, human resources, R&D and finance, as well as information technology and the Internet to maximize profitability of customer interactions. For customers, CRM offers customization, simplicity, and convenience for completing transactions, regardless of the channel used for interaction (Gulati and Garino, 2000).
CRM initiatives have resulted in increased competitiveness for many companies as witnessed by higher revenues and lower operational costs. Managing customer relationships effectively and efficiently boosts customer satisfaction and retention rates (Reichheld, 1996a, b; Jackson, 1994; Levine, 1993). CRM applications help organizations assess customer loyalty and profitability on measures such as repeat purchases, dollars spent, and longevity. CRM applications help answer questions such as “What products or services are important to our customers? How should we communicate with our customers? What are my customer's favorite colors or what is my customer's size?” In particular, customers benefit from the belief that they are saving time and money as well as receiving better information and special treatment (Kassanoff, 2000). Furthermore, regardless of the channel or method used to contact the company, whether it is the Internet, call centers, sales representatives, or resellers, customers receive the same consistent and efficient service (Creighton, 2000). Table I provides a brief overview of some of the benefits that CRM offers by sharing customer data throughout the organization and implementing innovative technology.
With much success, software vendors such as Oracle, SAP, PeopleSoft, Clarify, SAS, and Siebel are racing to bring off-the-shelf CRM applications to organizations. Many of these are the vendors responsible for developing enterprise resource planning (ERP) systems. AMR Research estimates that the CRM market will top $16.8 billion by 2003 (Tiazkun, 1999).
While there are many compelling reasons to consider a CRM strategy, caution and careful analysis is prudent. Hackney (2000) warns that although CRM software vendors may entice organizations with promises of all-powerful applications, to date there is no 100 percent solution. Possible risks such as project failure, inadequate return on investment, unplanned project budget revisions, unhappy customers, loss of employee confidence, and diversion of key management time and resources must be well thought out (Schweigert, 2000). In one example, a large telecommunications company rolled out a major CRM application to more than 1,000 sales reps in late 1999, at a cost of $10,000 per user, only to find a year later that fewer than 100 were using the system (Patton, 2001). Recent surveys further reveal that the average investment in CRM applications is $2.2 million dollars (CIO Research Reports, 2002), and that CRM implementation failure rate is as high as 65 percent (Apicella et al., 1999).
It is becoming increasingly clear that stalled or failed CRM projects are often the result of companies lacking a thorough understanding of what CRM initiatives entail. Thus, this paper first presents the evolution of CRM to facilitate the comprehension of the implementation issues. It then sets out to explore the underlying critical components that can enable (or hinder) the successful implementation of CRM initiatives. A CRM implementation model that integrates the three key dimensions of people, process, and technology within the context of an enterprise-wide customer-driven, technology-integrated, cross-functional organization is proposed in Figure 2. The essential roles of these three dimensions are further elaborated in the subsequent sections following the evolution of CRM.
2. CRM evolution
Customer relationship management itself is not a new concept but is now practical due to recent advances in enterprise software technology. An outgrowth of sales force automation (SFA) tools, CRM is often referred to in the literature as one-to-one marketing (Peppers and Rogers, 1999). SFA software automates routine tasks such as tracking customer contacts and forecasting. The goal of SFA is to allow the sales force to concentrate more on selling and less on administrative tasks. It should be noted, however, that CRM also has its roots in relationship marketing which is aimed at improving long run profitability by shifting from transaction-based marketing, with its emphasis on winning new customers, to customer retention through effective management of customer relationships (Christopher et al., 1991). Thus, CRM is a more complex and sophisticated application that mines customer data that has been pulled from all customer touch points, creating a single and comprehensive view of a customer while uncovering profiles of key customers and predicting their purchasing patterns. Technology that tracks and analyzes customer behavior allows companies to easily identify the best customers and focus marketing efforts and reward those who are likely to buy often. Acquiring a better understanding of existing customers allows companies to interact, respond, and communicate more effectively to significantly improve retention rates.
Innovations in technology, competitive environments, and the Internet are just several factors that make one-to-one initiatives a reality. Companies can develop these relationships to customize the shopping experience, better predict online buying patterns, entice customers with special offers or services, evaluate the economic advantage of each customer, and build long-term mutually beneficial relationships. The following examples highlight some of the benefits of CRM applications.
Ritz-Carlton, an upscale chain of hotels, records guest preferences gleaned from conversation with customers during their stay and uses them to tailor the services that customers receive on their next visit at any other Ritz-Carlton in the world. Requests for items such as hypoallergenic pillows and additional towels are recorded for future use so that personalized goods and services can be added for repeat customers. Mining customer data allowed Bank One to significantly reduce turnover among its most profitable small business customers by assigning dedicated account managers (Conlon, 1999). The service industry, however, is not the only industry to harness people, process, and technology to manage resilient customer relationships. Dell Computer Corporation exemplifies CRM success by combining IT with front and back office operations. Every PC that Dell manufactures is already sold. From the Internet, Dell customers are able to configure their own system, from thousands of hardware and software combinations, with an easy-to-use ordering system that provides delivery dates as well as progress updates.
3. The technology factor
Information technology (IT) has long been recognized as an enabler to radically redesign business processes in order to achieve dramatic improvements in organizational performance (Davenport and Short, 1990; Porter, 1987). IT assists with the re-design of a business process by facilitating changes to work practices and establishing innovative methods to link a company with customers, suppliers and internal stakeholders (Hammer and Champy, 1993). CRM applications take full advantage of technology innovations with their ability to collect and analyze data on customer patterns, interpret customer behavior, develop predictive models, respond with timely and effective customized communications, and deliver product and service value to individual customers. Using technology to “optimize interactions” with customers, companies can create a 360 degree view of customers to learn from past interactions to optimize future ones (Eckerson and Watson, 2000).
Innovations in network infrastructure, client/server computing, and business intelligence applications are leading factors in CRM development. CRM solutions deliver repositories of customer data at a fraction of the cost of older network technologies. CRM systems accumulate, store, maintain, and distribute customer knowledge throughout the organization. The effective management of information has a crucial role to play in CRM. Information is critical for product tailoring, service innovation, consolidated views of customers, and calculating customer lifetime value (Peppard, 2000). Among others, data warehouses, enterprise resource planning (ERP) systems, and the Internet are central infrastructures to CRM applications.
3.1 Data warehouse technology
A data warehouse is an information technology management tool that gives business decision makers instant access to information by collecting “islands of customer data” throughout the organization by combining all database and operational systems such as human resources, sales and transaction processing systems, financials, inventory, purchasing, and marketing systems. Specifically, data warehouses extract, clean, transform, and manage large volumes of data from multiple, heterogeneous systems, creating a historical record of all customer interactions (Eckerson and Watson, 2000). The abilities to view and manipulate set data warehouses apart from other computer systems. Constantly extracting knowledge about customers reduces the need for traditional marketing research tools such as customer surveys and focus groups. Thus, it is possible to identify and report by product or service, geographic region, distribution channel, customer group, and individual customer (Story, 1998). Information is then available to all customer contact points in the organization.
Data warehousing technology makes CRM possible because it consolidates, correlates and transforms customer data into customer intelligence that can used to form a better understanding of customer behavior. Customer data includes all sales, promotions, and customer service activities (Shepard et al., 1998). In addition to transaction details, many other types of data generated from internal operations can make significant contributions. Information related to billing and account status, customer service interactions, back orders, product shipment, product returns, claims history, and internal operating costs all can improve understanding of customers and their purchasing patterns. The ability of a data warehouse to store hundreds and thousands of gigabytes of data make drill-down analysis feasible as well as immediate. A corporate awareness survey conducted jointly by Cap Gemini and International Data Corporation (1999) found that 70 percent of US firms and 64 percent of European firms plan on building a data warehouse to support their CRM projects. SAS Corporation, a significant player in the data warehouse industry, has recently teamed with Peppers and Rogers Group to provide “CRM Resource”, a weekly guide on industry-focused CRM. A brief outline of organizational benefits with a data warehouse are:
accurate and faster access to information to facilitate responses to customer questions;
data quality and filtering to eliminate bad and duplicate data;
extract, manipulate and drill-down data quickly for profitability analysis, customer profiling, and retention modeling;
advanced data consolidation and data analysis tools for higher level summary as well as detailed reports; and
calculate total present value and estimate future value of each and every customer.
3.2 Enterprise resource planning (ERP) systems
Enterprise resource planning (ERP), when successfully implemented, links all areas of a company including order management, manufacturing, human resources, financial systems and distribution with external suppliers and customers into a tightly integrated system with shared data and visibility (Chen, 2001). An overview of ERP systems is provided in Figure 3. Major enterprise systems vendors, who have been successful in the ERP market, are gearing up for the growing needs of CRM by aggressively forming alliances with, or taking over other software companies that have been operating in the CRM market. For example, J.D. Edwards entered into a deal with Seibel, a leading CRM company, in May 1999 and subsequently shut down its in-house sales force automation team. Peoplesoft acquired Vantive's CRM software in October 1999 to integrate with its own ERP systems. Through mySAP initiatives, users of SAP R/3 system can add Web-based CRM and SCM functions while leaving the core R/3 system intact (Xenakis, 2000). Oracle has taken the most drastic steps in forming a new bond between ERP and CRM. The new flagship ERP/CRM software package, called 11i, is heavily Internet oriented and allows users to seamlessly implement modules of CRM with a smaller ERP suite (Sweat, 2000).
Significant differences exist between ERP technology and CRM applications. ERP serves as a strong foundation with tightly integrated back office functions while CRM strives to link front and back office applications to maintain relationships and build customer loyalty. ERP systems promise to integrate all functional areas of the business with suppliers and customers. CRM promises to improve front office applications and customer touch points to optimize customer satisfaction and profitability. While ERP systems address fragmented information systems, CRM addresses fragmented customer data. CRM applications are Web-enabled and designed to extend the data mining capabilities of ERP throughout the supply chain to customers, distributors, and manufacturers (Scannell, 1999). Organizations can use CRM analytical capabilities to predict and answer key business questions on customer intelligence and share the results across channels. Although ERP is not required for CRM, providing customers, suppliers, and employees with Web-based access to systems through CRM will only be beneficial if the underlying infrastructure, such as data warehouses and/or ERP, exists (Solomon, 2000). Companies with an ERP system, however, need to understand where they are in the implementation process, as well as assess where other technologies, such as data warehouses, fit in before plunging into CRM applications (Saunders, 1999).
3.3 Impact of the Internet
The explosive growth of the Internet has also brought new meaning to building customer relationships. Greater customer access to the organization, such as online ordering and around the clock operations, has set the stage for a shifting paradigm in customer service. A recent report describes how successful Web sites are in building lasting relationships with “e-customers” by offering services in traditionally impossible ways (Peppers and Rogers, 2000). Using a series of richly detailed case studies, they also contended that in the broad arena of business-to-business commerce, organizations would rise or fall on the basis of their capabilities to cultivate one-to-one relationships with their customers (Peppers and Rogers, 2001). Customers expect organizations to anticipate their needs and provide consistent service at levels above their expectations. In return, customers are loyal to the organization for longer periods of time. For instance, the American Airlines Web site builds customized customer views in real time allowing two million frequent fliers to have a unique experience each time they log on (Peppers and Rogers, 1999). Prior to the Internet, there was not a cost-effective way to tell millions of customers fitting a certain profile about an immediately available special fare. With the interactive capability of the Internet, American Airlines can do exactly that without having to tell everyone about every special fare. As a part of CRM, American Airlines offers loyal customers promotional fares and special discounts to partner businesses based on individual customer preferences.
4. Business process changes
Not long ago, companies with efficient facilities and greater resources were able to satisfy customer needs with standardized products, reaping advantages through productivity gains and lower costs. Mass marketing and mass production were successful as long as customers were satisfied with standardized products. As more firms entered the market, mass marketing techniques, where the goal was to sell what manufacturing produced, started to lose effectiveness. Target marketing, or segmentation, shifted a company's focus to adjusting products and marketing efforts to fit customer requirements. Changing customer needs and preferences require firms to define smaller and smaller segments.
It has become well known that retaining customers is more profitable than building new relationships. Consequently, relationship marketing was developed on the basis that customers vary in their needs, preferences, buying behavior, and price sensitivity. Therefore, by understanding customer drivers and customer profitability, companies can better tailor their offerings to maximize the overall value of their customer portfolio. In his seminal study, Reichheld (1996a, b) has documented that a 5 percent increase in customer retention resulted in an increase in average customer lifetime value of between 35 percent and 95 percent, leading to significant improvements in company profitability.
Customer relationship marketing techniques focus on single customers and require the firm to be organized around the customer, rather than the product. Customer-centric organizations seamlessly integrate marketing and other business processes to serve customers and respond to market pressures. Firms that evolve to this stage will benefit from a marketing-manufacturing interface, resulting in the flexibility to meet changing customer needs efficiently and effectively (Prabhaker, 2001). Figure 4 demonstrates the change from weak to strong customer relationships based on changing marketing strategies of mass marketing, target marketing and customer relationship marketing.
Despite the technological perspectives discussed in the previous section, the philosophical bases of CRM are relationship marketing, customer profitability, lifetime value, retention and satisfaction created through business process management. In fact, Anton (1996) characterizes CRM as an integrated approach to managing customer relationships with re-engineering of customer value through better service recovery and competitive positioning of the offer. Couldwell (1998) further depicts CRM as a combination of business process and technology that seeks to understand a company's customer from the perspective of who they are, what they do, and what they are like. In fact, companies have been repeatedly warned that failure is eminent if they believe that CRM is only a technology solution (Goldenberg, 2000).
The statement “retaining customers is more profitable than building new relationships” is especially true in the changing Internet market. The Boston Consulting Group estimates that it costs $6.80 to market to existing customers via the Web, versus $34 to acquire a new Web customer (Hildebrand, 1999). A recent Deloitte Consulting survey of more than 900 executives across different industries also revealed that manufacturers that set goals for improving customer loyalty are 60 percent more profitable than those without such a strategy (Saunders, 1999). A CRM strategy can help create new customers, and more importantly, develop and maintain existing customers.
Customer relationship management is an enterprise-wide customer-centric business model that must be built around the customer. It is a continuous effort that requires redesigning core business processes starting from the customer perspective and involving customer feedback. The Seybold Group starts this process by asking customers what barriers they encounter from the company (Seybold, 1998; Seybold et al., 2001). In a product-focused approach, the goal is to find customers for the products using mass marketing efforts. In a customer-centric approach, the goal becomes developing products and services to fit customer needs. In Seybold's work, five steps in designing a customer-centric organization were suggested:
make it easy for customers to do business;
focus on the end customer;
redesign front office and examine information flows between the front and back office;
foster customer loyalty by becoming proactive with customers; and
build in measurable checks and balances to continuously improve.
The goals of a customer-centric model are to increase revenue, promote customer loyalty, reduce the cost of sales and service, and improve operations. Optimizing customer relationships requires a complete understanding of all customers; profitable as well as non-profitable, and then to organize business processes to treat customers individually based on their needs and their values (Renner, 2000). Within the paradigm of business process re-engineering, Al-Mashari and Zairi (1999) offer a holistic view of success and fail factors. Specifically, change management, management support, organizational structure, project management, and information technology were highlighted. Companies considering CRM implementation can also benefit from addressing these five BPR issues.
5. People changes
Implementation of enterprise technology, such as CRM and ERP, requires changes to organizational culture (Al-Mashari and Zairi, 2000). While both technology and business processes are both critical to successful CRM initiatives, it is the individual employees who are the building blocks of customer relationships. There are several underlying dimensions surrounding management and employees that successful CRM implementations require.
Top management commitment is an essential element for bringing an innovation online and ensuring delivery of promised benefits. Top management commitment, however, is much more than a CEO giving his or her blessing to the CRM project. Customer-centric management requires top management support and commitment to CRM throughout the entire CRM implementation. Without it, momentum quickly dies out. Furthermore, top management should set the stage in CRM initiatives for leadership, strategic direction and alignment of vision and business goals (Herington and Peterson, 2000). This view was reinforced in a recent META Group Report (1998) that singled out top management support and involvement as a key success factor for CRM implementations.
As in most major change efforts, objections and disagreement among various functional departments that arise in the process of business reengineering and CRM implementation can only be solved through personal intervention by top management, usually resulting in changes to corporate culture. The META Group Report (1998) concluded that investing in CRM technology without a customer oriented cultural mindset is like throwing money into a black hole. Dickie (1999) also warns against starting a CRM project if senior management does not fundamentally believe in re-engineering a customer-centric business model.
CRM projects require full-time attention of the implementation project team with representatives from sales, marketing, manufacturing, customer services, information technology, etc. Cap Gemini and IDC found that top management and marketing and sales management are generally the initiators of a corporate CRM project (1999). In addition, project teams require not only sponsorship by top management but also a project champion that can persuade top management for continuous change efforts (Al-Mashari and Zairi, 1999). In general, project teams assist companies to integrate their core business processes, combine related activities, and eliminate the ones that don't add value to customers.
A functional organization often takes “ownership” of customer data. Many departments and individuals see customer handling as a sales or marketing function, and regard the release of their data to another function as a loss of power. A customer-centric model requires sharing the data enterprise-wide; this usually requires a fundamental paradigm shift in the culture to sharing information and knowledge. Especially in organizations where tradition has established separate goals and objectives, top management must not take a passive role in change efforts. Silo-based organizational myopia must be replaced with a customer-focus so departments will collaborate rather than compete with each other. Many of these changes efforts can be aided by effective communication throughout the entire project and reaching all levels of employees.
CRM initiatives require vision and each and every employee must understand the purpose and changes that CRM will bring. Re-engineering a customer-centric business model requires cultural change and the participation of all employees within the organization. Some employees may opt to leave; others will have positions eliminated in the new business model. Successful implementation of CRM means that some jobs will be significantly changed. Management must show its commitment to an ongoing company-wide education and training program. In addition to enhancing employee skills and knowledge, education boosts motivation and commitment of employee and reduces employee resistance. Additionally, management must ensure that job evaluations, compensation programs, and reward systems are modified on a basis that facilitate and reward customer orientation. After all, how people are measured will determine their behavior.
6. Conclusion
Somewhere along the turn of the twentieth century, buyers and sellers lost their intimate relationships. Prior to the Industrial Revolution, sellers knew their customers, many times by name, and generally understood their needs. Mass production built a wall between buyers and sellers where the main concept was to find customers for standardized products. Customers are more empowered today than ever before and the Internet is accelerating the trend toward greater customer empowerment. CRM applications attempt to focus on the customer first, specifically one customer at a time, to build a long-lasting mutually beneficial relationship.
Customer relationship management is a comprehensive approach that promises to maximize relationships with all customers, including Internet or “e-customers”, distribution channel members, and suppliers. Getting to “know” each customer through data mining techniques and a customer-centric business strategy helps the organization to proactively and consistently offer (and sell) more products and services for improved customer retention and loyalty over longer periods of time. Peppers and Rogers (1999) refer to this as maximizing “lifetime customer share”, resulting in customer retention and customer profitability. On the other hand, advanced customer data analysis also allows a company to identify the customers it does not want to serve. Beside the technological advances, CRM initiatives represent a fundamental shift in emphasis from managing product portfolios to managing portfolios of customers, necessitating changes to business process and people. As companies start to re-engineer themselves around customers, individual employees must also come to terms with changing business process, organizational culture and, thus, the ways they view their customers and how they treat them.
Organizations today must focus on delivering the highest value to customers through better communication, faster delivery, and personalized products and services. Since a large percentage of customer interactions will occur on the Internet rather than with employees (Bultema, 2000), technology must adapt to the changing and unpredictable market. Organizations that implement CRM and e-business applications will have the greatest gains (Lange, 1999). The future of CRM is e-relationship management or eRM that will synchronize cross-channel relationships (Saunders, 1999). It is also envisioned as an “e-partnering ecosystem” with a complex network of partners that operate as an interconnected whole, spanning entire markets and industries (Creighton, 2000; Siebel, 2001).
CRM implementations and the changing effect of the Internet offer abundant research opportunities. The identification of some implementation issues in this study raises several important research questions. In particular, what are the roles of suppliers and supply chain partners in CRM? How does e-CRM strategies affect brick and mortar companies? What business processes, integration challenges, and organization structures are common throughout successful CRM implementations? Research in these areas will contribute to building thriving customer relationships and long-term corporate survival. Years of academically researched topics of relationship marketing and customer retention are now practical and cost-effective to implement due to emerging technology. It is time to put academic theories to practice.

Egypt's Telecom Market Intelligence Report

Egypt's telecommunications sector is one of the fastest-developing markets in the Middle East and Africa (MEA) region, despite the fact that the fixed-line market is effectively monopolised by the state-owned incumbent operator, Telecom Egypt. The same company has a stake in Egypt's second-largest mobile telephone company - Vodafone Egypt - and also has stakes of varying sizes in the country's many value-added and Internet service providers (ISPs).
As the result of sustained network development and expansion, as well as the adoption of a free national Internet service, Egypt's fixed-line subscriber base has risen from just 3.9 million lines at the end of 1998 to around 10.4 million lines at the end of 2005. In the meantime, the waiting list for the installation of fixed lines has fallen from 1.4 million at the end of 1998 to a little over 66,000 by the end of 2005. At the same time, the Internet market has grown from around 150,000 users at the end of 1998 to around 5.0 million users by the end of 2005. The Egyptian authorities now expect to see the Internet user base soar to around seven million by mid-2007, representing just 10% of the population. In June 2004, the Egyptian government launched a public-private initiative to boost broadband access; the government also plans to raise awareness among small and medium-sized businesses about the advantages offered by broadband services. The Egyptian Ministry of Communications & Information Technology (MCIT) is actively supporting the use of computers at home, in schools and universities, as well as in businesses of all sizes. To further this end, the government is guiding Telecom Egypt to establish low-cost and transparent network interconnection and equipment co-location agreements with ISPs and application service providers throughout Egypt.
Egypt's mobile communications market has also witnessed strong growth in recent years, starting with 194,000 subscribers at the end of 1998, rising to 5.8 million customers at the end of 2003, 7.6 million customers by the end of 2004, and 12.8 million by the end of 2005. While cellular operators MobiNil and Vodafone Egypt initially were not able to acquire GSM 1800 frequencies to boost their existing GSM 900 offerings, a deal was done in late-2003 that split Telecom Egypt's GSM 1800 frequencies between the two companies, with MobiNil paying cash for its spectrum and Vodafone Egypt granting the incumbent a small, indirect stake in its business in return for its share of the spectrum. In the meantime, MobiNil and Vodafone Egypt are offering 2.5G services, such as WAP, GPRS, and SMS. A third GSM operator is to be licensed in 2006; an auction for this licence should close in May/June, with the new operator able to launch its services from 2007.
Egypt's telecommunications market was first opened to competition in 1997, when concessions to operate public payphone services were awarded to Menatel and Nile Telecom. Menatel has proved to be rather more successful than Nile Telecom, operating 30,810 payphones at the end of 2005, compared to Nile's 18,687; Telecom Egypt also operates a small-scale public telephone network, with 6,213 units in service at the end of 2005.
Public data networking services were liberalised in 1999, and the first wave of Internet service providers were able to enter the market in this way; however, it was not until the following year that the market for Internet infrastructure was opened to competition. The market for high-speed access services was liberalised in 2001, while the first virtual operators - mostly ISPs - were licensed in 2003. There were more than 200 ISPs in Egypt at the end of 2005. A revised version of the country's Telecommunications Act was adopted in February 2003, giving greater powers to the regulator, the National Telecommunications Regulatory Authority (NTRA), and broadening its remit to cover all aspects of the information and communications technology (ICT) market. The new law also protected Telecom Egypt's monopoly on fixed-line telephony services until the end of 2005; new international and local fixed-line carriers were expected to be licensed in 2006, but these plans now appear to have been put on hold until 2008. A public offering of shares in Telecom Egypt was completed in late-2005.

التنمية البشرية عماد تقدم المجتمع وازدهاره

ماذا يعني مفهوم تنمية الموارد البشرية؟ و ما الفارق بينه و بين مفهوم إدارة الموارد البشرية؟
ج. تطور مفهوم الموارد البشرية خلال الخمسين عاما الماضية من "مورد" ضمن باقى موارد أى مؤسسة إلى "رأس مال بشرى" ينبغى استثماره وتنميته والآن ينظر إلى الموارد البشرية الآن على أنها "رأس المال الفكرى" لأى مؤسسة. بمعنى ضرورة مشاركة العاملين فى إدارة شئونهم داخل المؤسسة والاستفادة من آرائهم ومقترحاتهم لتحسين ظروف العمل وجعل مكان العمل أكثر جاذبية وتحفيزا للعاملين على الإجادة وزيادة الإنتاج .ومن هنا كان من الضرورى زيادة كفاءة القيادات فى أى مؤسسة على حسن إدارة هذا المورد الاستراتيجى الهام والذى يتوقف عليه ازدهار المؤسسة ونموها وتوسعها وتغلبها على المنافسة وقدرتها على التغيير لمواكبة تحديات القرن الذى نعيشه.
ما هي عناصر تنمية الموارد البشرية ؟
لابد أولا من تضمين "ثقافة المؤسسة" مايؤكد حرصها على التعامل مع موظفيها على أنهم "رأس مال" يتطلب الحرص عليه ومداومة تطويره وزيادة مهاراته وكفاءته وفاعليتهثم يأتى بعد ذلك دور إعداد القيادات التى ستتولى المهام المختلفة داخل المؤسسة والتى ينبغ أن تلتزم بإطار التعامل مع الموظفين على أنهم "شركاء" فى المسئولية وليسوا متفرجين أو "متلقين" لأوامر يقومون بتنفيذها
يلى ذلك دعم "إدارة الموارد البشرية" ونقل تبعيتها لأعلى سلطة فى المؤسسة لكى تقوم بدورها الاستراتيجى فى التنسيق بين الإدارات المختلفة لتحقيق أهدافها المتعلقة بتنمية الموارد البشرية على مستوى الشركة ككل.
وتقوم تلك الإدارة – بالتعاون مع باقى الإدارات بالمؤسسة – فى وضع خطة استراتيجية طويلة المدى لاجتذاب أفضل العناصر للعمل، وتنمية قدراتهم باستمرار، ثم تحفيزهم للبقاء بالمؤسسة وضمان ولاءهم وعدم هجرتهم إلى خارجها.
كيف يمكن ضمان نجاح عملية التنمية للموارد البشرية ؟ و كيف يمكن قياس هذا النجاح و تقويمه؟
حين نتحدث عن أى مؤسسة، فإننا نتحدث عن "نظم" وقواعد وإجراءات تحكم العمل بها فى كل المجالات والأنشطة كالعمليات والمالية والتسويق والمبيعات، وطبقا الموارد البشرية.
لذلك لابد من توافر العناصر التى ذكرناها آنفا ، بالاضافة إلى "نظام" لتقييم الأداء يسبقه تحديد الأهداف المراد تحقيقها للمؤسسة ككل، ثم كل إدارة من إداراتها، ثم مسئوليات العاملين بتلك الإدارات طبقا للمسئوليات الوظيفية لكل منهم.
وينبغى أن تكون الأهداف موضوعية وواقعية وقابلة للتنفيذ ويمكن قياسها حتى يتم قياس الأداء بدقة . كما يجب أن يتضمن نظام قياس الأداء جزءا يوضح نواحى القصور فى الأداء وكيف سيتم تلافيها ودور كل من الرئيس المباشر والموظف فى ذلك بوضوح شديد.
كما ينبغى تخصيص جزء كبير من الزيادات السنوية فى المرتبات لاستخدامه كحافز على "التميز الحقيقى" فى الأداء، بل إنى من المؤيدين لوضع نظام حوافز إضافى يسمح بمكافأة العاملين المتميزين الذين يفوق أداؤهم المطلوب منهم تحقيقه بكثير، أو الذين يسهمون بأفكارهم ومقتراحتهم فى تحسن أداء المؤسسة ككل بشكل كبير وملموس.
ما أهمية تنمية الموارد البشرية للمجتمع؟
مرة أخرى، الناس هم عماد أى مجتمع. وقياس تقدم المجتمعات أو تأخرها يقاس فى النهاية بنوعية الناس الذين يشكلون تلك المجتمعات. والدول التى تقدمت عنا تعتمد فى نهضتها وتقدمها فى الأساس على "الجهود التطوعية" للناس، ويقتصر دور الحكومات عندهم على توفير البنية الأساسية للمشروعات ، أو إنجاز المشروعات العملاقة التى تحتاج إلى استثمارات هائلة، أو الصناعات الثقيلة ، أو الانتاج الاستراتيجى الذى يتوقف عليه اقتصاد الدولة وأمنها القومى
هل هناك استراتيجيات مختلفة لتنمية الموارد البشرية تختلف باختلاف طبيعة الدول نامية أو متقدمة ؟ و ماهي؟
طبيعى أن تتضمن خطط تنمية الموارد البشرية ظروف كل دولة. فالدول التى تزداد فيها نسب الأمية مثل مصر تحتاج إلى جهود مضاعفة فى جهود التنمية بوجه عام، والتنمية البشرية بوجه خاص. العلم والتقدم إذن متلازمان. لذلك لابد لنا فى المقام الأول فى مصر أن نعنى بتحسين جودة التعليم الذى أصبح يحتاج الآن إلى ثورة لكى يصل إلى المستوى العالمى الذى ينتج خريجا متعلما بحق ويعى مسئولياته الاجتماعية ويسم فى ازدهار بلده وتقدمها. وبدون ذلك سوف يظل خريجونا حاملى شهادات بغير علم.
لقد عاش جيلى عصرا ذهبيا كنا نتلقى العلم على أيدى أساتذة عظام أصحاب فكر ورسالة، وكانت المدارس – ناهيك عن الجامعات – معامل لتفريخ القيادات فى المجالات العلمية والثقافية والرياضية . كانت المدارس مثالا للانضباط يتم التعامل فيها فى خطين متوازيين مع العلم والتربية. كنا نخرج فى قوافل تجوب القرى المحيطة بعواصم الأقاليم التى ولدنا بها لكى نمحو الأمية ونزيد الوعى الصحى وندرب على رياضات بسيطة يمكن للبسطاء أن يمارسوها فى أى أرض فضاء. كنا نعى دورنا الاجتماعى فى قيادة قاطرة التنمية وتقدم المجتمع.
كيف يمكن توظيف ثورة تكنولوجيا المعلومات في تنمية الموارد البشرية؟
وهذه أيضا من مستلزمات تنمية الموارد البشرية حيث يتسم القرن الحالى بأنه عصر ثورة المعلومات. ومن حسن الحظ أن الوزارة الحالية تؤمن بذلك وتدفع فى اتجاه "الحكومة الإلكترونية" ونشر ثقافة استخدام التكنولوجيا فى التعليم وفى الأنشطة المجتمعية المختلفة.
إن قوة الدول لم تعد اليوم تقاس بمقدار ماتحتويه ترساناتها الحربية من أسلحة، وإنما " بمقدار ماتملك من معلومات توظفها لرفاهية المجتمع" طبقا لتعريفات الأمم المتحدة.
إننى لاأستطيع أن أفكر فى أى نشاط مؤسسى أو مجتمعى أيا كان نوعه لايتم فيه استخدام التكنولوجيا فى الحصول على المعلومات وتحليلها ونقلها والاستفادة منها فى البحوث والتطوير وحل المشكلات التى تعترض أى مشروع تنموى صناعى أو تجارى أو خدمى.
ما هو الدور الذي يمكن أن تلعبه مؤسسات المجتمع المدني في تنمية الموارد البشرية؟
يحتاج الأمر أولا إلى تشريعات تطلق حرية المجتمع المدنى وتضمن له دورا فاعلا فى تطوير السياسات والنظم المجتمعية ومساعدة الحكومية فى تحقيق أهداف التنمية.
وأرى أن البداية فى تضمين المقررات الدراسية بجميع مراحلها برامج "تعلم" أصول وقواعد ومتطلبات التنمية البشرية، وتمنح درجات للمتمزين من الطلاب فى تلك المجالات تشجعهم على التطوع لتطبيق مايدرسونه.
كذلك ينبغى على الدولة أن تساعد فى قيام الجمعيات الأهلية ومدها بالبنية التحتية التى تتيح لها استخدام التكنولوجيا فى أعمالها. وفى الوقت ذاته هناك دور إيجابى ينبغى للجمعيات الأهلية أن تقوم به فى اجتذاب العناصر الفاعلة لعضويتها، والتعرف على احتياجات الممجتمع من الخدمات، والالتصاق أكثر بالناس.
و كيف يمكن إحداث التكامل بين دور الدولة و دور القطاع الخاص و مؤسسات المجتمع المدني في تنمية الموارد البشرية ؟
تعنى الدولة بالتشريعات وتقديم التسهيلات وإعداد البنية التحيتية كما تقدم، بينما تقدم الجمعيات الأهلية الخدمات لمستحقيها وتعمل على زيادة قاعدة العضوية ونشر نشاطها متجاوزة حدود الحيز الجغرافى الذى بدأت به. وفى مصر حاليا أكثر من 000ر20 جمعية أهلية لو كانت تعمل بجد لصارت مصر أكثر تقدما من أمريكا نفسها، ولكن الواقع المرير يقول أن أكثر من 95% من تلك الجمعيات لاتعدو كونها لافتة ومجل إدارة لايجتمع وإنجازات بسيطة لاتحتاج أساسا لإنشاء جمعية لأدائها.
لذل فأنا من المنادين بضرورة التدقيق فى منح التراخيص دون تعنت من جانت جهة الإدارة لضمان الجدية وإمكانية المتابعة والمراجعة على فترات فى إطار من الود والتعاون بين جهة الإدارة ومجالس إدارات مؤسسات المجتمع المدنى.