The search for factors that lead to better project performance and success spans

Transcription

1 PROJECTS AND PROJECT MANAGERS: THE RELATIONSHIP BETWEEN PROJECT MANAGERS PERSONALITY, PROJECT TYPES, AND PROJECT SUCCESS DOV DVIR, Ben-Gurion University, Israel ARIK SADEH, Holon Institute of Technology, Israel AYALA MALACH-PINES, Ben-Gurion University, Israel ABSTRACT The fit between project managers personality and management style and the types of projects they manage is crucial for projects success. This exploratory interdisciplinary study focuses on the relationships among three aspects: projects types (profiles), project managers personality, and projects success. Based on the person-organization fit theory it was hypothesized that a project with a particular profile needs a manager with fitting personality traits in order to achieve optimal performance and success. A questionnaire, consisting of three parts was used: (1) classifying projects along the four dimensions (novelty, complexity, technology, and pace [NCTP]); (2) focusing on project managers personality traits relevant to these project dimensions; and (3) assessing the projects success from several perspectives. Preliminary results lend tentative support to the study s hypothesis. Keywords: project managers; project typology; personality traits; project success 2006 by the Project Management Institute Vol. 37, No. 5, 36-48, ISSN /03 Introduction The search for factors that lead to better project performance and success spans many years of research. The project management literature has dealt extensively with factors affecting projects performance and success (e.g., Might & Fischer, 1985; Pinto & Slevin, 1988; Rubinstein, Chakrabarti, O Keefe, Sounder, & Young, 1979; Slevin & Pinto, 1986). More recent studies (see, for example, Balachandra & Friar, 1997; Tishler, Dvir, Shenhar, & Lipovetsky, 1996; Dvir, Lipovetsky, Shenhar, & Tishler, 1998) have shown that the universalistic approach, which assumes that all projects are similar, may not be optimal for managing projects. Different types of projects should be managed in different ways. Nevertheless, A Guide to the Project Management Body of Knowledge (PMBOK Guide Third Edition) (2004) provides general guidelines for better project management without distinguishing among different types of projects or attempting to match project managers management style to specific types of projects. Although the fit between project managers personality and the nature of the specific projects they manage have not received much research attention, findings regarding the qualifications of managers (Colinson & Hearn, 1996; Cromie, Callaghan, & Jansen, 1992) and their psychological dynamic (Kets de Vries, 1991; Zaleznik, 1966) have been reported in the scientific literature. In recent years the differences between projects and the different managerial practices required for managing them have gained growing attention (e.g., Crawford, Hobbs, & Turner, 2004; Shenhar, 2001; Shenhar & Dvir, 1996). However, no studies heretofore addressed the personality of project managers and its influence on project performance and success. The current interdisciplinary exploratory study combined two disciplines project management and personality psychology and is based on three bodies of research: (1) project classification, (2) managers personality, and (3) measures of projects success. Project Classification A common misconception regarding projects is that they are all alike so one can use similar tools for all project activities. This is sometimes called the project-is-aproject-is-a-project syndrome (Shenhar, 2001). Managing projects with this attitude frequently leads to project failure and disappointment, because companies are 36 D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL

2 using improper project management techniques for many of their project efforts. In reality, projects differ in many important ways. To understand the conceptual foundation of projects as unique organizational forms, one can return to classical works in the early days of the organizational theory, particularly the theory of contingencies in organizations. Classical contingency theory asserts that different external conditions may require different organizational characteristics; organizational effectiveness is contingent upon the congruence or goodness of fit between structural and environmental variables (Drazin & Van de Ven, 1985; Lawrence & Lorsch, 1967; Pennings, 1992). Burns and Stalker (1961) presented what is now accepted as the traditional distinction between incremental and radical innovation, and between organic and mechanistic organizations. A mechanistic organization was described as formal, centralized, specialized and bureaucratic, with many authority levels and maintaining only a minimal level of communication. An organic organization, in contrast, was characterized as informal, decentralized, with few authority levels, breadth view, and extensive levels of communication. According to classical theorists, organic organizations cope better with uncertain and complex environments, whereas mechanistic organizations predominate in simple, stable, and more certain environments. Later scholars have argued, similarly, that organizations that perform more innovative tasks are different from organizations that develop more routine products (e.g., Abernathy & Utterback, 1978; Burgelman, 1983; Dewar & Dutton, 1986; Drazin & Van de Ven, 1985; Freeman & Beale, 1982; Mansfield, 1968; Pennings, 1992; Perrow, 1967; Thompson, 1967; Zaltman, Duncan, & Holbek, 1973). Although correlates of structural and environmental attributes have been well studied when the organization is the unit of analysis, they have been investigated far less in the context of projects. The project management literature has often ignored the importance of project contingencies, assuming that all projects demand a universal set of managerial traits (Pinto & Covin, 1989; Shenhar, 1993; Yap & Souder, 1994). Yet, projects can be seen as temporary organizations within organizations, and may exhibit variations in structure when compared to their mother organizations. Indeed, several authors have criticized the universal, one-size-fits-all idea, and recommended a more contingent approach to the study of projects (Eisenhardt & Tabrizi, 1995; Yap & Souder, 1994). Any search for a framework for categorizing projects must address the case of projects that are temporary, part of an organization and its culture, and performing new tasks that have not been done before. In addition, such a framework should be context-free and independent of a particular industry, technology, or organization. When searching for such a framework, one could look at three influential works, published independently in 1967, that had a significant impact on the contingency theory (Lawrence & Lorsch, 1967; Perrow, 1967; Thompson, 1967). More recent studies have looked at management of innovation and the change associated with it. For example, Tushman and Anderson (1986) discussed the interplay between radical and incremental innovation, and the cyclical model of technological change. Henderson and Clark (1990) linked different types of technological change to product class and different organizational consequences. And Burkhardt and Brass (1990) conceptualized technological change as a source of uncertainty and discussed the relationship between social structure and power and the diffusion and adoption of technological change. Although traditional contingency studies in the management of innovation have had only a limited impact on the literature of project management, some exceptions exist. Several studies focused on the impact of uncertainty and change on the way organizations are conducting their projects. For example, Blake (1978) suggested a normative distinction between minor change (alpha) projects, and major change (beta) projects; and Wheelwright and Clark (1992) mapped product development projects according to the degree of change in the product. Some have adopted the radical versus incremental distinction (e.g., Eisenhardt & Tabrizi, 1995; Souder & Song, 1997; Yap & Souder, 1994), while others suggested more refined frameworks (e.g., Cash, McFarlan, & McKenney, 1988; Pearson, 1990). Another dimension, in addition to degree of change, is complexity. The hierarchical nature of systems and their subsystems has long been the cornerstone of the general systems theory (Boulding, 1956; Shenhar, 1991; Van Gigch, 1978). Yet another dimension is time. Although classical theory focused on sustaining organizations, two compelling phenomena in modern organizations must be addressed: First, the temporary nature of projects and the time limitation that exist must be reflected in any framework for project categorization. Second, the high speed with which decisions are made and the shortened life cycles of products and markets make time a necessary dimension of any modern examination of organizations (Brown & Eisenhardt, 1997; Eisenhardt & Tabrizi, 1995). Regardless of the industry or technology involved, Shenhar and his associates identified three dimensions to distinguish among projects: uncertainty, complexity, and pace (Shenhar, 2001; Shenhar & Bonen, 1997; Dvir et al., 1998). Together, these three dimensions create the uncertainty, complexity, and pace (UCP) model and form a context-free framework for selecting the proper management style. Uncertainty: Different projects present, at the outset, different levels of uncertainty (mainly technological) and project execution can be seen as a process aimed at uncertainty reduction. Uncertainty determines, among other things, the length and timing of frontto-end activities, how well and how fast one can define and finalize product requirements and design, the degree of detail and extent of planning accuracy, and the level of contingency resources. D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL 37

3 Complexity: Project complexity depends on product scope, number and variety of elements, and the interconnection among them. Complexity will determine the organization and the process, as well as the formality with which the project will be managed. Pace: The third dimension for distinction among projects involves the urgency and criticality of time goals. The same goal with different time constraints may require different project structures and different management attention. Based on the basic UCP model, Shenhar and Dvir have conducted several studies to test its validity in the real world (Shenhar, 1998; Shenhar, 2001; Shenhar & Dvir, 1996). Through these studies, another dimension emerged: Novelty, which defines how new the product is to its potential users. The additional dimension provides a more complete model and enables to classify more accurately the project on hand. This NCTP model can guide project managers in selecting their project management style during project initiation, recruiting team members, structure, processes, and tools. The four dimensions of this framework novelty, complexity, technological uncertainty, and pace can be seen in Figure 1. Novelty Complexity Breakthrough Platform Derivative Figure 1: The NCTP framework Regular Fast/Competitive Time-Critical Blitz Project Managers Personality According to the person-organization (P- O) fit theory (Caplan, 1987; Kristof, 1996), P-O fit occurs when an organization satisfies individuals needs, desires, or preferences. In other words, when there is a good match between the characteristics/requirements of a particular job and the characteristics/expectations of the person working in that job. Individuals tend to make job choice decisions based on P-O fit. They prefer organizations that have the same personality as they do (Cable & Judge, 1994; Chatman, 1989; Judge & Bretz, 1992). Based on the P-O fit theory it can be expected that project managers will be attracted to projects that fit their personality. It can further be expected that they will do better in such projects than in projects that do not fit their personality. Getting back to the NCTP classification of projects proposed by Shenhar and Dvir (2004), the current study attempted to explore the idea of personality characteristics that may fit the project type portrayed by the four dimensions of this framework: novelty, complexity, technological uncertainty, and pace. Because no single personality construct and no single instrument apply to all four of these project dimensions, an attempt was made to Array System Assembly Pace Technology Low- Medium- High- Super-High Tech Tech Tech Tech combine a number of personality dimensions and their measures that seemed relevant conceptually. In all cases, those were dimensions that received significant attention in personality theory and research. As an exploratory study, the notion was to merely demonstrate the applicability of these personality dimensions to the four project dimensions. The novelty component was addressed by openness to experiences, one of the Big 5 components of personality (Costa & McCrae, 1992). The Big 5 (The Five Factor Model of Personality) is based on the idea that personality can be described and measured using five broad dimensions: Openness to experiences is one of them. A person high in openness to experiences has broad interests, is imaginative, curious, creative, adventurous, original, and artistic. A person low in openness to experiences is conventional, avoids the unfamiliar, is not artistic, and lacks imagination. The pace component was addressed by Type A behavior pattern (Friedman & Rosenman, 1974; Rosenman, 1993). Type A behavior pattern refers to a driven individual who feels oppressed by time. This is the person for whom punctuality is a supreme value that honks and fumes in traffic, barks at sluggish salesclerks, and feels compelled to do several things at once. The uncertainty component was addressed by a test of risk-taking tendency (Wallach, Kogan, & Bem, 1964) In the test that was designed to measure this tendency, respondents are presented with hypothetical situations and asked to imagine finding themselves in a situation that requires them to choose between two options and to indicate the lowest probability of success in which they would take the particular risk, from 1 out of 10 (the greatest risk) to 9 out of 10 (the lowest risk). The complexity component was addressed by two measures: the inventor personality type in Jung s (1990) typology and the investigative and enterprising personality types according to Holland s (1997) classification of vocational personalities. 38 D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL

4 1. The inventor is a personality type in Jung s (1990) typology of psychological types that divides between: introversion vs. extraversion, thinking vs. feeling, sensation vs. intuition, and perceiving vs. judging. The inventor is characterized by intuition, perceiving, and extroversion. Intuition includes being interested in possibilities rather than actualities, preferring principles to facts, and being innovative rather than practical. Perceiving includes being flexible rather than planned, disliking deadlines, and preferring unpredicted events. 2. The investigative and enterprising personality types are part of Holland s (1997) classification of vocational personalities. Holland believed that personality types, vocational choices and vocational stability, satisfaction, and success are contingent on the congruence or fit between individuals personality types and their work environments. Holland assumed that there are six personality types: realistic, investigative, artistic, social, enterprising, and conventional, and six work environments that the six personality types prefer to work in. Each vocational personality has preferred activities. Activities of the investigative (e.g., working on scientific projects) and enterprising (leading a group toward the accomplishment of a goal) types were chosen to represent the complexity dimension. Two general personality measures also seemed relevant to project management: 1. Personality traits that were found in previous research to characterize successful managers (e.g., commitment, involvement, and love of management) and high technology entrepreneurs (love of challenge and risk taking) (see Pines, Sadeh, Dvir, & Yanai, 2002). 2. Attachment styles have been the subject of a large and steadily growing research literature, much of it based on Bowlby s (1969, 1973, 1980) attachment theory. According to this theory, positive attachment experiences in early childhood build working models of attachment that function as inner structures that guide people in assessing and coping with stress. It was repeatedly demonstrated that a secure attachment style is associated with positive appraisal of stressful situations and with constructive coping. On the other hand, insecure attachment (anxious ambivalent or avoidant) is associated with poor coping and maladjustment. Project Success Most projects are conceived with a business perspective in mind, and often with a goal, which is focused on better results and organizational performance more profits, additional growth, and improved market position. Several recent studies have indicated the impact of effective projects on firms performance (e.g., Ittner & Larcker, 1997; Menke, 1997). However, when project managers and project teams are engaged in day-today project execution, they are typically not focusing on business aspects. Their attention, rather, is operational, and their mindset is on getting the job done. Most project managers see their job as successfully completed when they finish the project on time, within budget, and to specifications. This operational mindset is clearly reflected in the project management literature, which has traditionally used time, budget, and performance as the main indicators of project success. Any of these measures, however, even when taken together, are incomplete and may be misleading. They may count as successful projects that met time and budget constraints, but did not meet customer needs and requirements (Atkinson, 1999), or projects that ended up having great difficulty in the commercialization process of the final product. Several studies suggested adding a new element to the assessment of project success client satisfaction and customer welfare (Lim & Mohamed, 1999). DeCotiis and Dyer (1979) emphasized the importance of customer satisfaction while Lipovetskey, Tishler, Dvir, and Shenhar (1997) claimed that customer satisfaction is the most important of the success indicators. Baker, Murphy, and Fisher (1988) went further, to include the level of satisfaction of four different stakeholders: the customer, the developer, the project team, and the end-user. Project success assessments may also differ according to the assessor. As Freeman and Beale (1992, p. 8) noted, Success means different things to different people. An architect may consider success in terms of aesthetic appearance, an engineer in terms of technical competence, and a chief executive officer may rate the project success in the stock market. The idea that project success assessments may differ according to the assessor facilitated the introduction of multidimensional frameworks for the assessment of project success. These frameworks reflect different interests and different points of view. Pinto and Mantel (1990), for example, identified three aspects of project performance as benchmarks for measuring the success or failure of a project: the implementation process, the perceived value of the project, and client satisfaction with the result. Freeman and Beale (1992), for another example, identified seven main criteria used to measure project success, among them, technical performance, efficiency of execution, managerial and organizational implications (including customer satisfaction), personal growth, and manufacturers ability and business performance. Whereas Cooper and Kleinschmidt (1987) discussed three dimensions of new product success: financial performance, the creation of new opportunities for new products and markets, and market impact. More recent research has suggested new perspectives. Baccarini (1999), for example, used a hierarchy of project objectives including goal, purpose, outputs, and inputs, and suggested distinguishing between those and project product success, arguing that a project management team is responsible for producing an output, but the determination of project s purpose is beyond its responsibility. According to this framework, project success is detached from the expected business results. Sadeh, Dvir, and Shenhar (2000) provided a template for project success D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL 39

5 utilizing four dimensions based on a classification identified by Dvir, Segev, and Shenhar (1993). The first dimension, meeting design goals, refers to the contract that was signed with the customer. The second dimension, benefit to the end-user, refers to the benefit to the customer from the project end products. The third dimension, benefit to the developing organization, refers to the benefit gained by the developing organization as a result of executing the project. The last dimension, benefit to the defense and national infrastructure, measures the benefit to the national technological infrastructure, as well as to the technological infrastructure of the firm that was engaged in the developmental process. The Current Study Based on the P-O fit theory (Cable & Judge, 1994; Caplan, 1987; Chatman, 1989; Judge & Bretz, 1992; Kristof, 1996), it was assumed that project managers are attracted to and more successful managing projects that fit their personality and that this is manifested in the relationships among project profiles, project managers personality characteristics, and project success. Method Instrument The instrument, especially designed for use in the study, was a self-report measure that included three parts: (A) assessing project managers, (B) assessing projects characteristics, and (C) assessing projects success. Assessing Project Managers The specific measures and items chosen for use in the study that seem relevant to the four project dimensions include the following. The dimension of novelty: Seven of the openness to experiences items in the Big 5 factors of personality (Costa & McCrae, 1992) seemed appropriate for assessing project managers attraction to novelty: six items that indicate high openness to experiences (taking part in philosophical discussions, interest in solving problems or complicated riddles, preference for surprises, interest in many subjects, thinking differently from others, and willingness to try new and unfamiliar foods) and one item that indicates low openness to experience (preference for spending time in a familiar rather than in an unfamiliar environment). Participants were asked to what extent they agree with the statements on a 7-point scale ranging from 1 (very much disagree) to 7 (very much agree). They received one score for openness to experiences. The dimension of pace: Eleven items that measure aspects of Type A behavior pattern, based on Friedman and Rosenman s (1974) book, and seemed relevant for assessing project managers attraction to high pace projects were chosen (e.g., viewing absolute punctuality as of highest importance, compressing more and more activities into less and less time, doing and thinking about two things at once, hastening the speech of others, getting overly angry when forced to wait in line, getting impatient when watching others who seem to be doing things too slowly). Respondents were asked to what extent these behaviors characterize them on a 7-point scale from 1 (very little) to 7 (very much). They received one score. The dimension of uncertainty: Risktaking tendencies were chosen for assessing project managers attitude toward uncertainty. Based on The Choice Dilemma Questionnaire (Wallach, Kogan, & Bem, 1964) that assesses risk-taking tendencies, respondents were presented with hypothetical situations and asked to imagine finding themselves in situations that required them to choose between two options and to indicate the lowest probability of success in which they would take the particular risk from 1 out of 10 (the greatest risk) through 5 out of 10 (medium risk), to 9 out of 10 (the lowest risk). Three choice dilemmas were chosen because they seemed appropriate for assessing project managers attraction to uncertainty: an entrepreneurial risk, an investment risk, and a managerial risk. Respondents received, accordingly, three risk scores: entrepreneurial, investment, and managerial. In the entrepreneurial risk dilemma, respondents are asked to imagine being an electronics engineer working in a company where they are guaranteed a secure position for many years but their salary is low and chances for an increase in salary are slim. At a professional convention, a representative of a small high-tech company offers them a position with challenge, options for equity shares, and an opportunity to join as a partner if the start-up will be successful. The offer is attractive, but it involves a risk, because it does not guarantee job security. What is the lowest probability in which they would accept the offer? In the investment risk dilemma, respondents are asked to imagine having average means and income and inheriting some money. They can invest the money in expensive and promising stocks with little earnings, or in a stock that offers great earnings combined with the possibility of losing the entire investment. In the managerial risk dilemma, respondents are asked to imagine being the president of a company facing expansion. They can build a branch locally, and then the investment is secure with moderate earnings, or they can build a factory abroad in a country with an unstable government. If the government doesn t change, the investment can bring very high earnings, but if the government does change, it can cause very high losses. What is the lowest probability in which they would choose to build the factory abroad? The dimension of complexity: Two measures addressed this dimension: the inventor personality type in Jung s (1990) typology and the investigative and enterprising personality types according to Holland s (1997) classification of vocational personalities. Jung s (1990) typology of psychological types differentiates between: thinking vs. feeling, sensation vs. intuition, perceiving vs. judging, and introversion vs. extraversion. A 20-item measure is based on this typology (Wilde & Labno, 2002). Out of the 20 items, 15 were chosen. They included intuition and perceiving items that 40 D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL

6 seemed appropriate for assessing project managers attraction to complexity. In addition, extraversion items that seemed appropriate for assessing managers ease with customers were also included. The intuition items included, for example, preference for thinking about possibilities rather than dealing with actualities, for principles rather than facts, for the innovative rather than the practical, and for work on development rather than production. The perceiving items included, for example, tendency to be flexible rather than pre-planned, dislike of deadlines, preference for unpredicted events rather than for programmed events, and preference for preparing decisions rather than making them. The extraversion items included preference for working with a team rather than independently, talking at meetings rather than listening, having many friends rather than a few, for answering the phone rather than having someone else answer it, and being easy to approach rather than difficult. The statements were presented in pairs and respondents were asked to mark the statement that better describes them. Respondents received three scores: intuition, perceiving, and introversion. Holland s (1997) theory assumes the existence of six vocational personality types (realistic, investigative, artistic, social, enterprising and conventional), six corresponding work environments that the six personality types prefer to work in, and preferred activities that each vocational personality has. The activities that tend to characterize the investigative and enterprising types were chosen, based on the assumption that these vocational personality types seem appropriate for assessing project managers attraction to specific types of projects. The activities that characterize the investigative type include, for example, reading scientific books and magazines, conducting experiments, working on a scientific project, solving math or chess problems, and learning a new scientific topic. The activities that characterize the enterprising type include influencing others, running an independent business or service, holding a responsible role in an organized group, supervising the work of others, and leading a group toward the accomplishment of a particular goal. Participants were asked to indicate which of those activities they like to do. Each participant received two scores: investigative and enterprising. Managerial and entrepreneurial traits: Based on the work of Pines, et al. (2002) a 15-item measure was used. It includes eight items characterizing entrepreneurs, such as love of challenge, initiative, independence, tendency to dream, optimism, creativity, risk-taking, and rebelliousness, and seven items characterizing managers such as commitment, involvement, persistence, need for control, and love of management. The items were presented randomly and respondents were asked to rate to what extent these traits characterize them on a 7-point scale ranging from 1 (very little) to 7 (very much). Attachment style: Based on Bowlby s (1969, 1973, 1980) attachment theory and the measure of attachment styles developed by Hazan and Shaver (1987), the following three short paragraphs were presented to the respondents: It is relatively easy for me to become emotionally close to people. I am comfortable depending on others and having others depend on me. I don t worry about being abandoned or about having others get too close to me. (secure attachment style) I am somewhat uncomfortable getting close to others. I find it difficult to trust others completely or to be dependent on them. I get tense when someone gets too close to me. Often others who are close to me want a more intimate relationship than I am comfortable with. (avoidant attachment style) Others are reluctant to get as close as I would like. I often worry that others don t really love me or that they won t want to stay with me. I want to merge completely with others and at times this makes people distance themselves from me. (anxious/ambivalent attachment style) Respondents were asked to read the paragraphs and indicate to what extent each one describes their feelings on a 7-point scale ranging from 1 (not at all like me) to 7 (very much like me). They received three scores: S (secure), A (avoidant) and AA (anxious/ambivalent). Success Criteria Project success was measured along four dimensions representing different points of view that were validated in previous research on defense projects by Lipovetsky et al. (1997). 1. Meeting planning goals (project efficiency) 2. Customer benefits (success from the customer s point of view) 3. Benefits to the parent organization 4. Benefit to the community and national infrastructure Project Classification The UCP classification of projects scheme suggested by Shenhar (2001) was used in the study. This classification has been validated by a set of tests based on comprehensive data and expanded into the NCTP framework (Shenahr & Dvir, 2004). The four dimensions in the classification framework novelty, complexity, technology, and pace are described by four ordinal variables; each dimension includes at least three different project types (see literature review). In the study, the NCTP model for portraying the project and building a specific profile for each project in the sample was used. Participants: Eighty-nine Israeli project managers, managing 89 different projects, took part in the study. The project managers were primarily men (70%) with a minority of women (30%). Their mean age was 38 and mean level of education was 16 years. The projects varied greatly in size and type and included projects carried out in high-tech industries, in defense-related industries and in educational organizations (organizational change projects). Procedure: Project managers were approached by Israeli senior BSc students and asked to fill out the questionnaires. The students, who took part in a final project in project management D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL 41

7 Success Dimensions Meeting design goals Benefit to the end-user Benefit to the developing organization Benefit to the community, and national infrastructure Table 1: Success dimensions and measures proficiency, had similar age, education, and professional background, and were familiar with projects and project management, but did not have previous interviewing experience. As part of their participation in this study, they were instructed how to make contact with the project managers, soliciting their cooperation, and guiding them how to fill out the questionnaires. Confidentiality was promised and strictly enforced. Data management: After the questionnaires were collected, the projects described were analyzed according to the NCTP model. It turned out that the sample did not contain breakthrough projects, array projects, or super-hightech projects. The sample also did not contain either time-critical or blitz projects. Grouping of projects exhibiting the same levels of novelty, complexity, uncertainty, and pace created 20 different groups of projects. Because the sample size did not allow meaningful statistical analyses, the low levels of technological uncertainty and pace were combined, reducing the number of groups to five. However, even this reduction yielded too many small groups. In the final step, assembly and Success Measures Functional specifications Technical specifications Schedule goals Budget goals Meeting acquisition goals Answering the operational need Product entered service Reached the end-user on time Product had a substantial time for use Meaningful improvement of user operational level User is satisfied with product Relatively high profit Opened a new market Created a new product line Developed a new technological capability Increased positive reputation Contributed to critical subjects Maintaining a flow of updated generations Decreasing dependence on outside sources Contribution to other projects system projects were grouped together, creating three groups of projects. Hypothesis Based on the P-O fit theory and the other theories and studies described in the theoretical section, the following hypotheses were proposed: Hypothesis 1 (from the projects perspective): Projects managed by managers whose personality characteristics match their projects profiles will be more successful than projects managed by managers whose personality characteristics do not match their projects profiles. Hypothesis 2 (from the project managers perspective): Project managers will be attracted to and will be more successful managing projects that fit their personality characteristics. Results Project Profiles Due to the small variability of projects in the sample and the lack of projects with high levels of novelty, complexity, technological uncertainty, and pace, content analysis revealed that the projects can be divided into three main categories: (1) derivative projects producing new products that present only modest improvements relative to older products; (2) platform projects that produce a new generation of products, but with low technological uncertainty; and (3) projects characterized by a high level of technological uncertainty (e.g., high-tech projects). These last projects were also characterized by relatively low complexity. The correlations among project managers personality characteristics and their projects measures of success were analyzed separately for these three project profiles. Success Criteria A factor analysis (Principal Component Analysis with Varimax rotation) of the nine success measures used in the study, revealed three rather distinct factors that all together explained 78% of the variance. The new opportunities factor loaded highest on the creation of a new technological infrastructure (.89), the creation of a new product line (.87), the creation of a new market (.86), and the creation of a new operational infrastructure (.78). This factor explained 34% of the variance. The customer satisfaction factor loaded highest on meeting customers requirements (.92), keeping to operational specifications outlined at the start of the project (.86), and customer satisfaction (.83). This factor explained 26% of the variance. The efficiency factor loaded highest on meeting schedule goals (.90) and on meeting budget goals (.86). This factor explained 18.6% of the variance. (Please note that factors are presented in order of the size of the explained variance.) The three success factors were used (rather than nine distinct items) in the rest of the data analysis. Managers Profiles Using the measures and scales described in the instrument section, the project managers were each given scores that rated their: openness to experiences, Type A behavior pattern, risk-taking (entrepreneurial, investment, and managerial), psychological type (intuition, perceiving, and extraversion) and attachment style (secure, anxious/ambivalent, and avoidant). 42 D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL

8 Intuition Perceiving Introversion Investigative Enterprising Type A Secure Avoidant Anxious-Ambivalent Open to Experiences Entrepreneurial Risk Investment Risk Organizational Risk Entrepreneur Manager Rebellious Dreamer Significant correlations (p<.05) appear in bold A factor analysis (Principal Component Analysis with Varimax rotation) of the 15 managerial and entrepreneurial traits revealed three factors that explained 56% of the variance. The first factor: entrepreneur loaded highest on love of challenge, commitment, initiative, independence, creativity, and persistence and explained 21% of the variance. The second factor: manager loaded highest on love of management, need for control, energy, and confidence and explained 19.7% of the variance. The third factor: rebellious dreamer loaded highest on tendency to dream, optimism, rebellion against authority, and risk-taking and explained 15.4% of the variance. The managers profiles and three success criteria were put into a matrix of correlations, first for the entire sample (see Table 2) and then for each of the three project types separately (see Table 3). As can be seen in Table 2, three significant negative correlations were found between personality measures and the success factor of customer satisfaction: introversion, an investigative occupational personality type, and an anxious ambivalent attachment style. Three significant correlations were found between personality measures Efficiency Customer New Satisfaction Opportunities Table 2: Correlations between personality and success dimensions (n=89) and the success factor of creating new opportunities: a positive correlation with the personality factor entrepreneur and negative correlations with the personality factor characterizing rebellious dreamer and an avoidant attachment style. No significant correlations were found between personality measures and the success factor of efficiency. Table 3 presents the correlations between managers profiles and the three success criteria for each of the three project types separately. Because of the small number of high-tech type projects (13), only one correlation came out statistically significant: the success indicators of efficiency were found to be significantly and negatively correlated with Type A behavior pattern and negatively, but not significantly, with all three risk-taking indicators, with openness to experiences and with the personality factor characterizing an entrepreneur. The success indicators of customer satisfaction were negatively but not significantly correlated with openness to experiences, with the personality factor characterizing a manager, and with the anxious-ambivalent attachment style. The success indicators of creating new opportunities were found to be highly and negatively correlated, even if not significantly so, with the avoidant attachment style, and positively correlated with all three risk-taking indicators and with the personality factor characterizing an entrepreneur. For the derivative type of projects, customer satisfaction was correlated negatively with two variables an investigative occupational personality type and an anxious-ambivalent attachment style of project managers. For the platform type of projects, the success factor of creating new opportunities was positively correlated with only one variable the personality factor characterizing an entrepreneur. The tendency of project managers with a certain personality to be attracted to projects with similar profiles was also examined by comparing the means of the personality variables in the three different project type groups. The results of a series of F tests for differences among the three groups are presented in Table 4 along with the means of all variables. Significant differences were found only for the following personality measures: perceiving, openness to experiences, and the rebellious dreamer personality factor. Project managers in high-technological uncertainty projects tended to be high in intuition (which includes being interested in possibilities rather than actualities, preferring principles to facts, and being innovative rather than practical) and in perceiving (which includes being flexible rather than pre-planned, disliking deadlines, and preferring unpredicted events) relative to the managers of the two other types of projects. They also tended to be relatively low in avoidant attachment and rate low on the rebellious dreamer personality dimension and on openness to experiences. Project managers in the derivative, less complex, and more certain type of projects, tended to be relatively low in intuition and perceiving and high in avoidant attachment style and on the rebellious dreamer personality factor, which is to say, the exact opposite of managers of high-technology projects. Project managers in platform-type projects were found to be higher than project managers in the other two types D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL 43

9 Intuition Perceiving Introversion Investigative Enterprising Type A Secure Avoidant Anxious-Ambivalent Open to Experiences Entrepreneurial Risk Investment Risk Organizational Risk Entrepreneur Manager Rebellious Dreamer Significant correlations (p<.05) appear in bold Derivative (n = 40) Platform (n = 36) High-Tech (n = 13) Efficiency Customer New Efficiency Customer New Efficiency Customer New Satis. Opport. Satis. Opport. Satis. Opport. Table 3: Correlations between personality and success dimensions for three project types of projects, but not significantly so, in the investigative personality dimensions, and in openness to experiences. Discussion The current exploratory interdisciplinary study combined psychological constructs and measures with research issues deriving from the field of project management. Based on the P-O fit theory it was hypothesized that (1) (from the projects perspective) projects managed by managers whose personality characteristics match their projects profiles will be more successful than projects managed by managers whose personality characteristics do not match their projects profiles; and (2) (from the project managers perspective) project managers will be attracted to and more successful when managing projects that fit their personality. In order to test these two hypotheses, the study examined the relationships among project profiles, project managers personality, and project success of 89 projects. The projects were found to be best grouped into three project types: derivative (projects producing new products that present only modest improvements relative to older products); platform (projects that produce a new generation of products, but with low technological uncertainty); and high tech (projects characterized by high level of technological uncertainty). Results revealed a higher number of high correlations for the separate project groups (36 correlations with r>.25) than for the entire sample (five correlations with r>.23). This suggests a different relationship among different types of managers and different dimensions of project success for different types of projects. Examining specific findings it can be seen that for the entire sample, three negative correlations were found between certain personality measures and the success criteria of customer satisfaction, all of them making psychological sense. The negative correlation between introversion and customer satisfaction makes sense because introversion reflects lack of interest in people. Similarly, an investigative occupational personality tends to be more focused on challenging ideas than on people, and a person with an anxious ambivalent attachment style is more focused on himself or herself rather than on others around. For all three types of projects, these personality characteristics are likely to be perceived by customers as less attentive and friendly, which could account for the lower levels of customer satisfaction. The two negative correlations and the positive correlation found between certain personality measures and the success criteria of creating new opportunities can also be easily explained: The positive correlation with the personality factor characterizing an entrepreneur makes sense in light of the traits associated with this factor love of challenge, commitment, initiative, independence, creativity, and persistence all likely to influence activities that are not directly related to the current project, but can establish the infrastructure for future projects. On the other hand, the negative correlation between an avoidant attachment style and creating new opportunities can probably be explained by the tendency of people (in this case, project managers) with an avoidant attachment style to avoid difficulties and challenges. Similarly, the traits associated with the rebellious dreamer a tendency to dream combined with rebellion against authority, risk-taking, and optimism are also negatively correlated with the ability to establish the infrastructure for future projects. 44 D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL

10 Table 4: Means of personality variables by project groups More interesting findings emerged from the comparison between the results of the three types of projects. The comparison revealed a much higher number of high correlations for the high-tech type projects than for platform or derivative projects. For the derivative, low-tech-type projects, customer satisfaction was correlated negatively with both an investigative occupational personality type and an anxious ambivalent attachment style of project managers. As noted earlier, the investigative occupational personality type that is characterized by a focus on challenging ideas rather than on people, and the anxious- ambivalent attachment style that is self-focused, are both likely to be perceived by customers as less attentive, which would account for the lower levels of customer satisfaction. For platform projects, the success criteria of creating new opportunities was positively correlated with the personality factor characterizing an entrepreneur. This finding can again be explained by the traits that are a part of this factor love of challenge, commitment, initiative, independence, creativity, and persistence all likely to contribute toward the creation of new opportunities in the future. For high-technological uncertainty projects, the success dimension of efficiency was found to be negatively correlated with Type A behavior pattern and with openness to experiences. These findings seem to suggest that driven project managers who feel oppressed by time and get overly impatient with employees who love solving complicated problems and tend to think differently from others are likely to be less efficient. The negative correlation between openness to experiences and customer satisfaction can also be explained as reflecting customers dissatisfaction with project managers who tend to think differently than they do and who prefer to spend their time improving the technological solution, rather than interacting and trying to understand the customers feelings and preferences. It should be noted that the hightech group of projects in this exploratory study was rather small (n=13). Many of the correlations that did not reach significance (29 correlations with r >.25) would have probably reached significance with a larger sample. Looking at the results from the perspective of the project managers rather than the perspective of the projects suggests that project managers tend to prefer to manage projects they like. An alternative explanation is that top management assigns them to projects they think will suit them best. Thus, the differences found among the three project group means suggest that managers who are high in perceiving (who tend to be flexible rather than pre-planned and prefer unpredicted events to programmed events) and who are high in intuition (who prefer the innovative on the practical and work on development rather than production) prefer high-tech projects as compared to low-tech platform or derivative projects. In contrast, managers who rate high on the rebellious dreamer personality factor (who have a tendency to dream and rebel against authority) and who have an avoidant attachment style, tend to avoid managing high-tech projects and prefer derivative (first) and platform (second) type projects. Taking all these findings together, it can be said that the exploratory study provided tentative support for its two hypotheses. Nevertheless, the study has a number of serious limitations that need to be taken into account. First is the sample size. Although 89 projects and 89 project managers seem to be a respectable sample, the sample did not cover the full spectrum of possible projects, and in one case (high-tech) included a very small number of projects (13). Future studies should make an effort to recruit project managers who represent the full spectrum suggested by the NCTP model and include more participants in each category. Another problem involves the methodology used, a self-report measure, with all the problems associated with it. The students who conducted the study reported that in several cases, project managers did not fill out the questionnaire properly. Future studies should add other methodologies (e.g., interviews). A third problem involves the personality measures used in the study. As noted earlier, no single personality construct and no single instrument seems to apply to all four project dimensions investigated in the study. Thus, several personality dimensions D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL 45

11 and measures that seemed to be conceptually relevant were selected. The results of this exploratory study demonstrated the applicability of a number of these personality dimensions. Future research will need to focus on those constructs and measures that were found to be more appropriate and add other constructs and measures that may prove relevant. Summary and Conclusions The current exploratory interdisciplinary study focused on the complex relationships among projects types, project managers personality, and projects success. Based on the P-O fit theory, it was hypothesized that projects managed by managers whose personality characteristics match their projects profiles will be more successful and that managers will be more successful managing projects that fit their personality characteristics. The study s results lend tentative support to these hypotheses. They reveal for three types of projects, different patterns of correlations between certain aspects of managers personalities and certain dimensions of project success. Despite the limitations of the study as an exploratory study, these findings have important theoretical and practical implications. On the theoretical level, the findings demonstrate the value of a truly interdisciplinary collaboration between project management and personality psychology and provide additional support for the P-O fit theory. On the practical level, the findings can be translated into guidelines for managers on how to create a better fit between project managers and the projects assigned to them so as to ensure greater project success. References Abernathy, W. J., & Utterback, J. M. (1978). Patterns of industrial innovation. Technology Review, June/July, Atkinson, R. (1999). Project management: Cost, time and quality, two best guesses and a phenomenon, its time to accept other success criteria. 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13 new product success and failure in U.S. and Japanese electronic firms. The Journal of Product Innovation Management, 14(1), Thompson, J. D. (1967). Organizations in action. New York: McGraw-Hill. Tishler, A., Dvir, D., Shenhar, A., & Lipovetsky, S. (1996). Identifying critical factors of defense development projects: A multivariate analysis. Technological Forecasting and Social Change, 51, Tushman, M., & Anderson, P. (1986). Technological discontinuities and organizational environments. Administrative Science Quarterly, 31, Van Gigch, J. P. (1978). Applied general systems theory. New York: Harper & Row Publishers. Wallach, M. A., Kogan, N., & Bem, D. J. (1964). Diffusion of responsibility and level of risk taking in groups. Journal of Abnormal and Social Psychology, 68, Wheelwright, S. C., & Clark, K. B. (1992). Revolutionizing product development, quantum leaps in speed, efficiency and quality. New York: The Free Press. Wilde, D., & Labno, D. B. (2002). Personality and the creative impulse. The Journal of Creative Behavior. Yap, C. M., & Souder, W. E. (1994). Factors influencing new product success and failure in small entrepreneurial high-technology electronics firms. Journal of Product Innovation Management, 11(5), Zaleznik, A. (1966). The managerial mystique: Restoring leadership in business. New York: Harper & Row. Zaltman, G., Duncan, R., & Holbek, J. (1973). Innovations and organizations. New York: John Wiley & Sons. DOV DVIR is the head of the management department at the Ben-Gurion University in Beer Sheba, Israel. Previously, he was the head of the Management of Technology (MOT) department at the Holon Center for Technological Education. He holds a BSc in electrical engineering from the Technion - Israel Institute of Technology; MSc in operations research and an MBA from Tel Aviv University; and PhD in management from Tel Aviv University. Prof. Dvir has accumulated more than 25 years in management of large-scale projects and consulting in the government and private sectors. He has published more than 70 papers in the areas of project management, technology management and technological entrepreneurship, in refereed journals and scientific conferences. ARIK SADEH earned his PhD at Texas A&M University in He worked for an American-Israeli high-tech company in financial and business planning of huge scale projects. He held a research position in the Department of Statistics and Operations Research of the Agricultural Research Organization (ARO) in Israel. Dr. Sadeh is a senior lecturer in the Management of Technology Department at Holon Institute of Technology. His research areas are project management, operations management, economics, finance, and decision-making. AYALA MALACH-PINES, PhD, is a clinical, social and organizational psychologist and head of the Department of Business Administration at the Ben-Gurion University School of Management in Israel. Professor Pines is one of the pioneers in the study of burnout and has published extensively on the subject including numerous research articles, book chapters, and a book entitled Career Burnout: Causes and Cures, coauthored with Elliot Aronson. She has published 10 books, 20 book chapters, and more than 80 research articles. Her books have been translated into many languages including Hebrew, French, German, Spanish, Hungarian, Greek, Turkish, Chinese, Japanese, and Korean. 48 D ECEMBER 2006 PROJECT M ANAGEMENT J OURNAL

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