Information & Management 51 (2014) 618–626Contents lists available at ScienceDirect Information & Management journal homepage: www.elsevier.com/locate/im Defining decision making process performance: Conceptualization and validation of an index Manon G. Guillemette a,*, Maxime Laroche b, Jean Cadieux b,1 a b PRISME Research Group, Universite´ de Sherbrooke, Faculte´ d’administration, 2500 Boulevard de l’Universite´, Quebec, Canada J1K 2R1 Universite´ de Sherbrooke, Faculte´ d’administration, 2500 Boulevard de l’Universite´, Quebec Canada J1K 2R1 A R T I C L E I N F O A B S T R A C T Article history: Received 5 March 2014 Received in revised form 20 May 2014 Accepted 23 May 2014 Available online 3 June 2014 Many studies have demonstrated the impact of information technology (IT) on decision making but few have used decision making process performance (DMPP) as a dependent variable. Our study proposes a rich formative conceptualization of DMPP, a valid and reliable measure for this construct, and studies its influence on the quality of decision making. The results show that DMPP is a formative second-order aggregate construct composed of procedural rationality, exhaustivity of the information analyzed, openness of spirit, and effort. This study illustrates the importance of building proper definitions of constructs and contributes to the development of shared meaning in IS. ß 2014 Elsevier B.V. All rights reserved. Keywords: Decision making process performance Formative construct Procedural rationality Exhaustivity of information Openness of spirit Decision-making effort 1. Introduction Information technologies (IT) have long been presented as useful tools that support structured, semi-structured and unstructured decision making. For example, expert systems have been associated with semi-structured decisions, enterprise resource planning systems have been associated with structured decisions, and business intelligence systems have been associated with unstructured decisions. It is now widely acknowledged that information systems contribute to the overall quality of decision making in organizations. Many studies have demonstrated the impact of IT on decision making. For example, group decision support systems (GDSS) have been shown to provide better access to electronic databases and to facilitate the sharing of information in group decisions [30]. Executive information systems have been shown to play an important role in gathering data for strategic decision making by top executives [34]. In this respect, the use of a data warehouse may result in superior performance compared to the use of either a * Corresponding author. Tel.: +1 819 821 8000x62983; fax: +1 819 821 7934. E-mail addresses:
[email protected] (M.G. Guillemette),
[email protected] (M. Laroche),
[email protected] (J. Cadieux). 1 Tel.: +1 819 821 8000x61925; fax: +1 819 821 7934. http://dx.doi.org/10.1016/j.im.2014.05.012 0378-7206/ß 2014 Elsevier B.V. All rights reserved. partial data warehouse (which contains no long-term history or aggregated data) or no data warehouse at all [24]. Moreover, ERP systems have been shown to increase business professionals’ satisfaction in their individual work by providing strong support for the design phase (evaluation of alternatives) of the decision making process [1]. As a last example, decision support systems have proven useful in risk planning by helping decision makers implement the most effective countermeasures for reducing the security threats faced by firms [28]. However, much like other researchers, we observed that these studies do not always measure the impact of IT on the same construct, sometimes creating confusion in how the results are interpreted [27]. For example, Barkhi and Kao [2] study the importance of psychological climate on decision making performance in a GDSS context. The dependent variable of their model is named performance of GDSS users and is built from decision quality, decision satisfaction and decision time. The authors state, ‘‘The decision quality and satisfaction measure the effectiveness of the user’s decision process and hence are critical measures for the impact of GDSS on decision-making.’’ The use of different names for similar constructs employed in different ways is a good example of the type of confusion that has been created through the years in attempts to develop a construct of decision-making performance. Thus an important distinction must be made between the performance of the decision making process and the quality of the decision itself or between the result of the process and the result of in a crisis-like context. As a result. Our study is a response to the call made by other researchers to focus on evaluating decision processes rather than the consequences of those decisions [21]. / Information & Management 51 (2014) 618–626 the decision. Theory development It has been argued that managers spend most of their working time communicating and making decisions. Developing the content of the DMPP construct In this study. Guillemette et al. In the business world as much as in research. these studies do not fully capture the complexity and diversity of the phenomenon of decision making process performance [13]. [33]) adopts a unidimensional conceptualization of the DMPP construct based on a reflective conceptualization. they are not used in a predefined temporal sequence [13]. Our results demonstrate that the DMPP construct is. paying less attention to other process characteristics. Although phases are used to define the decision making process. retrieving papers that were cited in the reviews and choosing those that discussed a potential ‘‘dimension’’ of process performance. High-impact decisions are likely to involve the use of information and knowledge in the decision making process to cope with uncertainty that is intrinsically related to the organizational context [11. Rather. politics and culture.3. this assumption suggests that the observed indicators reflect the construct that they are measuring such that all of the indicators move in the same direction. We also examined papers that cited these reviews.M. researchers must evaluate whether the construct is unidimensional or multidimensional. they tend to use a rational approach in their decision making process. managers tend to adopt a more straightforward approach [13. Such decisions are not usually made by a single individual in complete isolation. [26] underscore the importance of considering the focus of a study to ensure that its content reflects its theoretical orientation. colleagues and employees). We then develop a measure of this construct that we validate with a sample of 198 respondents. most extant studies have focused mostly on procedural rationality. These identified facets are then considered for inclusion as dimensions of the higher-order construct.1. exhaustivity of the information consulted. at the first-order level. performance is measured by only one aspect of the construct [26]. all decisions are not the same. although DMPP appears to be a multidimensional construct. In light of these considerations. decision makers are influenced by other people (top-managers.20]. The first step in defining a multidimensional construct is to identify the content domain under investigation. openness of spirit. In this respect.20]. but some highly cited papers published in lower-tier journals were also included in our review. we conceptualized it as a multidimensional construct. Indeed. this paper proposes a rich formative conceptualization of decision making process performance (DMPP) and studies its influence on the quality of decision making. This suggests a formative conceptualization rather than a reflective one. applying the same criteria. few reliable and valid measures have been proposed to accurately measure this construct and those that have been proposed have not been sufficiently tested. the decision to invest in the development of a new product or to abandon production of an existing one. We concluded this step once saturation was achieved. 2. due in part to the complexity of the analysis required but also because the construct is not always properly conceptualized. 2. Rational decision-making can be associated with a structured decision process that is grounded in the bounded-rationality concept proposed by Simon. of four reflective dimensions: procedural rationality. The results show that highimpact decisions. Our study focuses on important decisions for organizations that we call ‘‘high-impact decisions’’. although they may use heuristics or intuition to cope with bounded rationality at some points in this process [5]. Evaluating the performance of a process is not a simple task. decision makers tend to carefully reevaluate their implementation plans and use a structured decision making process to do so. which does not seem entirely appropriate for this type of problem. and decisions regarding the termination of a marketing campaign. an important issue in developing our DMPP construct was to select dimensions that would reflect the decision-making 2 A rational approach should not be confused with decisions that seek optimization. Even if managers are under the influence of 619 political forces. [26] to conceptualize the DMPP multidimensional construct. In fact. structures. we adopted the 7-step model proposed by Polites et al. Therefore. such as tactical and strategic decisions [34] or ethical decisions [15]. Examples of high-impact decisions include the decision to implement a new information technology. First. We conducted a literature review on decision making process performance by focusing on the fields of management and information systems. the positive impact of high-quality analysis on the quality of decision making is well documented [24. The second step consisted of making theory-driven decisions about the nature of the construct’s facets. However. in planning a new strategic initiative. decisionmaking process performance is an important prerequisite for a quality decision. However.22. Polites et al. relatively complex. design and choice. we observed that the DMPP construct appears to consist of a certain number of distinct factors that are actually the causes of the construct and therefore do not necessarily always move in the same direction [26].3]. It proposes a reusable tool for researchers that is a valid measure of this important dependent variable. We also extended our search laterally to include papers on the ‘‘dimensions’’ that used synonyms to present similar constructs. and effort. we have noticed that extant research (e. .G. and important for the organization (tactical or strategic decisions). Because our DMPP construct consists of a number of distinct yet interrelated dimensions.21]. Consequently. 13. we adopted a rational approach2 to the organizational decision making process. Past research has found that this type of decision is approached more carefully and rationally by managers compared to less important decisions. Papers published in top-tier journals were preferred. we conceptualize DMPP as a multidimensional construct in the form of a formative second-order aggregate construct [26] composed. We found relatively few studies in our literature review that use the decision making process performance construct. The adoption of this model is also in accordance with the use of IS to support managers’ decision making processes. and different decisions may require that managers adopt different decision making processes.g.g. As a result. These decisions are mostly ill-structured. in high-performing firms are taken in a more rational and less intuitive and political way than some have suggested [23]. and a relationship appears to exist between these two distinct constructs [33. or in reaction to a new uncertainty.14] and applied a snowball strategy. from a conceptual perspective. Instead. For example. In such a situation. In other words. basing our approach on Simon’s three-stage model of intelligence. Recent research has shown that the degree of structure of the decision making process is somewhat related to the degree of adaptation required by the context. a true formative construct with the above-mentioned four dimensions and that it is also an important and significant antecedent of decision quality. However. We began with reviews on decision making [e. 1). Exhaustivity of the information refers specifically to the ‘‘completeness’’ of the information available to the decision maker when following each step of the decision making process. As in any formative conceptualization. exhaustivity of the information analyzed. procedural rationality is a fundamental component of performance in the decision making process because it fosters a more rigorous analysis of the situation requiring a decision because the decision maker consciously follows a defined process [11. 3. In sum. the better the quality of the decision making process [21].4. there is causality. Exhaustivity of the information The exhaustivity of the information taken into account by the decision maker is another important factor in the decision making process. defined as using one’s imagination and intellectual abilities to develop a new line of thinking. Taking this approach. / Information & Management 51 (2014) 618–626 process as it is conceptualized in this study.1.13]. Procedural rationality may be conceptualized as the extent to which the decision making process involves collecting information relevant to the decision and relying on analysis of this information when making one’s choice [9]. we wanted the dimensions to be theoretically consistent with our conceptualization of the decision making process as one that is largely rational and structured to ensure the internal coherence of the DMPP construct. Past research has shown that use of a nondirective decision support system (DSS) on a complex problem may increase the amount of effort invested by managers. 2. 2. a decision maker who invests more effort in the decision making process should have a better performance process than a decision maker who makes less effort.1. underscoring. and therefore engage in more effective decision making processes [31]. The purpose of the reflective measures at the first-order level is to reveal the presence of phenomena related to the latent constructs. sources of information and roles [31]. the proposed model is reflective at the first-order level and formative at the second-order level (see Fig. exhaustivity of the information analyzed. Four dimensions met these criteria: procedural rationality. Procedural rationality. In other words: Does the decision maker have enough information at the time that the decision must be made? 2. determining mathematical relationships between the dimensions. and they are used and tested in this study. 2. a change in the value of one of the four dimensions will not necessarily affect one of the other dimensions. Different types of information are required to make business decisions. The first-order.2. effort has been defined as the total use of the cognitive resources required to complete the task [21]. which affects the quality of the decision making process [21]. It refers to the broad rational cycle of decision making and measures the rigorousness and discipline with which the decision maker follows each step.3. For example. One would expect that performance can be interpreted in the same way because it generally consists of an aggregation of measures rather than a single observable measure. we conceptualized each of these dimensions as created from reflective measures. 2. Procedural rationality One of the components that has been most studied as a prerequisite for a quality decision is procedural rationality on the part of the decision maker [16].2. Therefore. and the more detailed this information is.G. Decision makers usually use a cost/benefit model and. effort. Effort Effort represents a critical dimension in the decision making process and has been found to be the most important factor influencing strategy selection [32]. exhaustivity of the information analyzed.1. we wanted dimensions that are central to the organizational and IT decision making literature. a decision maker who does not engage in a rational process may still review large quantities of information as part of his or her decision making process. and openness of spirit. effort and openness of spirit. seek a compromise between maximizing performance and minimizing effort. the fourth and fifth steps consist of determining the nature of the construct (aggregate or profile). the formative nature of the construct under study [17]. We expressed the DMPP construct at the second-order level as a formative model with four dimensions: procedural rationality. Second. We used three criteria to make this assessment. For example.1. More specifically. Extant research associates openness of spirit with creativity. Finally. our construct can be qualified as formative. decision makers who demonstrate openness of spirit in their decision-making processes are more inclined to make decisions that take all of the issues into account.620 M. Openness of spirit Openness of spirit refers to the extent to which decision makers are open to new ideas. This methodology entailed reproducing all of the questions of the first-order dimension and asking a few . more often than not. reflective items have already been developed. Many decision makers often choose solutions with which they are most familiar. from each dimension to the construct. Finally. and do not always explore new avenues as part of their decision making processes. if a decision maker is not following a rational process. In the context of decision making. Methodology A Q-Sort activity was carried out to establish the content validity of the reflective first-order dimensions of our second-order formative construct [25]. effort and openness of spirit may be conceptualized as the underlying dimensions of DMPP. if it is aggregate. It has been suggested that once a construct has several dimensions of the same order. Consequently. Because each of these first-order dimensions has been used in the past as reflective and observable measures. reflective nature of the measurement items is particularly appropriate because it targets manifestations of their main indicators. Guillemette et al. Generally. The main feature of these reflective items is that they are interchangeable. once again. Because the DMPP construct combines the four dimensions presented earlier in a way that creates meaning. Past research has shown that procedural rationality is associated with managers that expect rewards for a strong decision performance and decision makers that have high levels of accountability in their decision making process. the dimensions that are conceptually distinct. Formative conceptualization of DMPP (steps 3–5) The third step in the conceptualization of a multidimensional construct is deciding whether the construct is reflective or formative in nature. and then.1. the DMPP construct is conceptualized as a Type II formative construct [17]. all of the measures used for this dimension will be weak because they act as reflective measures. facilitating comprehension of the problem and encouraging the assessment of multiple alternatives [21]. The more information that is available to and used by a decision maker. At the first-order level. First. the dimensions can be aggregated into an index [35]. we wanted the dimensions to be logically and empirically distinct. Openness of spirit allows decision makers to make decisions by going beyond their usual limitations. The results showed that the use of procedural rationality in the decision making process by these managers is associated with improved decision performance [29]. distribution. Once this decision had been made. We let the students make one decision (one round of the simulation) before we disclosed the objectives of our study. 1 1 e3 0. was performed by three professors from our business school with a success rate of 92%. To estimate the MIMIC model.18] [31] 7 5 5 5 under study. 0. Concerning the convenience sample and the generalizing process.5 1 0. The purpose of this additional constraint is to give the latent construct a scale. 0. Questions were listed in random order to minimize the risk of common method bias. A single Q-Sort activity with only one association phase.1 Q1. 0. 0. 0. To be able to mathematically estimate the formative construct’s parameters. production operations. the additional measures (at the top of the formative model) are observable items related to the construct under study or constructs with nomological links to the construct Table 1 Measures of DMPP. Reflecve 0.5 Q3. OS Q2.5 e7 1 Q4.G. 10] states that ‘‘The statistical methods allow us to generalize from our sample to an idealized population from which it could have been sampled. it is common to include. individuals unfamiliar with the study to classify them based on the second-order formative structure. our DMPP construct had 22 items. All aspects of the simulation mirrored a real-world market.6 e8 1 Q4.4 RQ3.4 1 e24 1 e25 Q2. Keppel and Wickens [19. Topics such as marketing. so our approach should not interfere with the generalization of the results. A pretest was performed with 37 respondents to ensure that the questions were clear but also to demonstrate that any colinearity between the second-order indicators and the first-order indicators would be limited.4 e6 1 Q4. Guillemette et al. 0. 0. thus allowing the students to think about what to do next and the potential consequences of each decision.3 EF EI PR 0. 1 0. and the extrastatistical generalization let us conclude that this hypothetical population is similar to the actual population that we want to study. e11 Q1. Data collection Data were collected from a sample of undergraduate business students3 [19].2 1 0. 1 0. Formative model of DMPP. All of the students were randomly assigned to groups.6%.1 e4 1 Q4. human resources and financial aspects were targeted. According to the literature review.2 Q1. This study is based on a self-administered questionnaire. As part of the students’ business strategy class (final year). using experts who grouped the items based on their similarities. and the groups were randomly selected from the sample. The procedure was also used to eliminate items unrelated to the expected first-order dimension. and 10 uncompleted 3 It is typically acknowledged that the performance of students from one university compares with that in other universities. they were enrolled in an online simulation in which they had to run a digital camera company in head-to-head competition against companies run by their classmates. e10 1 Q4.7 e9 1 Q4. / Information & Management 51 (2014) 618–626 621 0. In total. 0.2 0.M. 0.2 e5 1 Q4. shown in Table 1 and in Appendix A. 1). 0. 3. and the students were asked to complete our questionnaire anonymously. e1 e2 1 1 Q21 DMPP2 Q23 0.10] [27. at the second order level. The technique combined validation of content and construct. Variable name Indicator References # of items PR EI EF OS Procedural rationality Exhaustivity of information Effort Openness of spirit [11. e20 e19 e18 e17 e16 e21 Q2.1 Q3. e12 1 0. quality control. The resulting model is called a MIMIC model. 1 0. p.3 1 0. 0. at least two additional reflective measurement items (see Fig.4] [21. 1. We decided to include perceptual measures for the DMPP construct and perceptual measures of the decision quality construct (nomological validity) to estimate our MIMIC model. 0.’’ . The activity resulted in the removal of some measurement items unrelated to any of the four fundamental dimensions of the DMPP construct and a rewriting of ambiguous formulations to make the questionnaire clearer.1.3 1 e22 Q2. This effectively associated each of the first-order items with the appropriate dimension. 1 0. Four questionnaires were removed from the sample due to visible biases in the answers. e15 e14 e13 Q3.4 Q1. product design. the objectives of the study were presented. 1 0. 0. DMPP Formave 0. the four selected first-order dimensions cover the most important and fundamental aspects of DMPP.5 1 e23 Q2. We created our measures by adapting the measures used in the references presented in Table 1.1 Q3.9. Fig. 1 0.8. A total of 212 students completed the questionnaire for a response rate of 98.3 Q1. Cronbach’s alpha VIF 5.1 and.35 1 0. 2.135 1.05. a MIMIC model was created by adding two global measurement items (DMPP1 and DMPP2) to analyze the relationship between the indicators and the DMPP model. students acted as managers and had to make highimpact decisions in a simulated ‘‘real-world’’ context.659 questionnaires were also removed. Moreover. students were graded for this exercise and thus they faced consequences for not exercising care in their decisions. Table 3 shows that the measurement model’s chi-square statistic is 4. 4.56 0.208 1 result nevertheless confirms internal consistency among the firstorder dimensions.69 0.51 0.1859 0. and the general fit index (GFI) must exceed 0. which is based on Fig.255 EI 4 DMPP22 DMPP DMPP PR 3 1 1 0. and the value for R2 is 0.817 Correlations 0. Although students are not organizational decision makers.M.688 1.7 threshold. with three degrees of freedom.834 0. the Cronbach’s alpha values are all greater than or equal to 0.72. In addition.05.76960 0.06182 0.193 0. CFI and GFI are equal to or greater than 0. / Information & Management 51 (2014) 618–626 622 Table 2 Analysis of indicators of DMPP. 2. Guillemette et al. In our study.53 e2 DMPP 1 0.72535 1.482.674 1. The right part of the table presents correlation values between the four indices.783 0. OS .33. under 0. 0. Because we focused on the decision making process and not on the quality and impacts of the decision. The values for NFI. 2. and the root mean square error of approximation (RMSEA) and the square root mean residual (SRMR) must be below 0.688. The variance inflation factors (VIFs) were analyzed to find signs of multicolinearity among the first-order indices [6]. which satisfies the standard proposed by Diamantopoulos and Siguaw [12] of a maximum VIF of 3. The maximum observed VIF is 1. created by averaging the related items at the reflective first-order level.47 1 e3 0. As seen in Table 2. if possible.9. We therefore have no reason to believe that the students did not perform business simulations as seriously as real managers would have. The weights were: 0. Cronbach’s alpha was used to analyze the internal consistency of the first-order reflective dimensions. Table 3. the coefficients of the four major components of DMPP were what was we expected. the values for SRMR and RMSEA are less than or equal to 0. presents the MIMIC model’s goodness of fit. This resulted in 198 usable questionnaires. 1 0. 0. The threshold values of the normed fit index (NFI). Cenfetelli and Bassellier [6] suggest assessing the weights of indicators as an initial analysis of a formative model. Estimating the measurement model Table 2 presents various statistics relating the items to the latent dimensions and relationships between the indices (variance inflation factors).992.382 2 1 0.811 0. This e1 1 0. which is not significant.520 1.75212 0. the four components explain a significant amount of the variance in DMPP.200 EF Fig. Results 4.208 for procedural rationality. 2. In sum.4610 5.1. Other indicators also suggest a good fit between the model and the data.G. The formative measure consists of our four dimensions that use reflective measures. As shown in Fig. MIMIC model of DMPP. which is slightly less than the usually accepted 0. the students’ lack of experience in assessing complex situations should not have played an important role in their decision making processes. As seen in Fig.0071 5.255 for exhaustivity of information. the comparative fit index (CFI).67.7980 5.382 for effort.735 1 0. PR EI EF OS Average of items Standard dev. we believe that the sample is appropriate given the objectives of our study. 3. Our approach consisted of analyzing the entire construct using a single integrated measure with four fundamental dimensions: procedural rationality. which.997 0. we noticed several different dimensions that have been used to assess various aspects of DMPP. We argued that the DMPP construct is formative in nature and based on four fundamental distinct components. Guillemette et al. the DMPP index explains a good portion of the variance in the decision quality construct (R2 = 0. CFI and This paper proposed a comprehensive definition of DMPP. all of the non-standardized regression coefficients were significant at a level of 0. 5. The statistics suggest external validation of the DMPP index and that the relationship between DMPP and decision quality is significant (R2 = 0.817 0. By way of comparison.2. The model’s goodness of fit statistics also suggest strong goodness of fit between the model and the data. Following extant literature. provide an appropriate definition of all of its distinctive components.482 (3. 4 presents a concurrent reflective model.200 Reflective measurement items in the MIMIC model DMPP1 DMPP2 0.817 DQ 1 1 DMPP PR EI EF 0. shows that the R2 for the index is higher than those for the reflective measures.M. the formative index is superior to the reflective measure in terms of criterion validity. the nature of the construct is additive because it takes into consideration different aspects of this performance that are theoretically distinct but. Because all four components are relevant in this context and their e1 e4 e5 e6 e7 e8 1 1 1 1 1 DQ1 DQ2 DQ3 DQ4 DQ5 1 DMPP 1 0.993 0. these approaches did not provide an overview of the entire construct and all of its dimensions. 0. We used a MIMIC model to assess the goodness of fit of this conceptualization of DMPP. Discussion and 0. when taken together.208 0. e6 . The standardized regression weights suggested that each component is an important determinant of DMPP. and the SRMR and RMSEA statistics were equal to or greater than 0.382 0. as measured by their R2. This definition of the construct was validated by performing a statistical analysis of the model. These results suggest that the proposed formative measure provides a better fit but also that it predicts decision quality better than the various reflective measures used in the past. effort and openness of spirit.992 0. constructs. An analysis of the explained variances for decision quality.362).214) 0. MIMIC model Beta Measures of goodness of fit X2 (df. However.012 0. the estimated model used DMPP as an antecedent to the construct of decision quality (DQ). p value) R2 NFI CFI GFI SRMR RMSEA 4.601 OS Fig.919.362 1 e3 0. We validated this premise by showing that each of the dimensions makes a positive contribution to the index. Formative model of the external validity of DMPP. In our review of the literature. the index of DMPP should feature significant correlations with other.735 623 GFI statistics were all equal to or greater than 0. according to the literature. should be related. / Information & Management 51 (2014) 618–626 Table 3 Goodness of fit of the MIMIC model of DMPP. Fig.102. In addition. 4.601). the statistics support external validity of the DMPP index. 3 presents the relationship between the DMMPP index and the decision quality construct. As anticipated. as seen on the left side of Table 4. we ensured that the links between the constructs would be in the expected directions.05. By conceptualizing DMPP as a formative second-order structure. Fig.72 0.G. Moreover. In sum. Nomological and external validity To achieve external validity.050 DMPP index Procedural rationality (RP) component Exhaustivity of information (EI) component Effort (EF) component Openness of spirit (OE) component N = 198 0. exhaustivity of information. theoretically related. The gap between DMPP and decision quality is greater with the formative index.200 for openness of spirit.255 0. The NFI. These behaviors may help explain why rationality is so firmly anchored in organizations [5]. following Cabantous and Gond [5]. by taking this approach. Keppel and Wickens [19] states.M. Other views of the decision making process exist in the literature.291 1 0.066 0. people intentionally ignore some information. .944 0. Other researchers have shown that heuristics are sometimes as effective at accurately predicting an event as optimization models. 4) Estimated standardized parameters DMPP ! DQ R2 0. 0.911 0. making trade-offs when necessary and acting accordingly. etc. hypothesis testing. make a deliberate effort in making this decision. However. It is typically acknowledged that the performance of students from one university compares with that in other universities. / Information & Management 51 (2014) 618–626 624 e7 e8 e9 e10 e11 1 1 1 1 1 DQ1 DQ2 1 DQ3 DQ4 DQ5 DQ 0. This highlights the crucial role played by IT tools in day-to-day decision making [7]. Formative model (Fig. Researchers who work on making the index more complete will be able to continue to assess the generalizability of the construct in different contexts. but rather to use a structured approach to making a decision. Thus. Rather. our conceptualization does not ask the decision maker to use all of the available information. It also opens some interesting and important research avenues in terms of identifying specifically how DSS supports the decision making process in organizations.107 of the problem. and the extrastatistical generalization let us conclude that this hypothetical population is similar to the actual population that we want to study. we contend that even in these highly political contexts. Most of the research in this stream compares the use of statistical models (called rational models) with many parameters to human decision makers using only a limited quantity of information.053 RMSEA 0.00) NFI 0.362 Measures of goodness of fit X2 (df.’’ (p. they should be seen as forming a relevant and generalizable list of measures of the construct between decision contexts and types. managers are somewhat rational in their choices. use enough information to have a clear idea Table 4 Goodness of fit of the formative and reflective models of external validity. p value) 85. subject to the influence of other stakeholders. our approach should not interfere with the generalization of the results. ‘‘The statistical methods allow us to generalize from our sample to an idealized population from which it could have been sampled.805 (28. It is likely that both heuristics and political pressures will be intertwined with rationality in the decision making process of managers.539 DMPP e2 1 PR EI 1 1 e3 e4 EF OS 1 1 e5 e6 Fig. Other researchers may identify other dimensions that may be relevant in some contexts or for some types of decisions and will need to make judicious choices to ensure the completeness of the index and its theoretical parsimony. Our measure benefits from this theoretical parsimony and offers significant explanatory power concerning decision quality.G. they may not constitute an exhaustive list of potential indicators. We know that managers make considerable use of information technologies to guide their decision making (such as in information searches.768 (26. Concurrent reflective model of DMPP. significant contributions are in the expected direction.291 84.). analyze enough information to identify and analyze alternatives. Our DMPP measure may help them assess the impacts of IT on the decision making process. Concerning the convenience sample and the generalizing process. For example. Consequently.923 0. 10).601 0. We do not find this incompatible with our own conceptualization. Even though the four dimensions of DMPP were based on an exhaustive review of the literature. and inject some creativity into the process. 0. 3) Concurrent reflective model (Fig. scenario analyses. 4. political models view decision making as non-rational and propose that decisions are made by bargaining and negotiating with powerful actors.539 0.951 GFI 0. In fact. We made a conscious choice in this study to relate our DMPP measure to a rational decision making process.00) 0. Guillemette et al.931 CFI 0. in fact. Our decision to conceptualize decision making as a rational process was grounded in the managerial and information systems literature and represents continuity in this respect. Researchers interested in these interactions may find this a promising area of research.919 SRMR 0. coping with their bounded rationality.102 0. we suggest that they are good indicators of our DMPP construct. Our study acknowledges that decisions are not made in isolation but are. we would like to thank the Social Sciences and Humanities Research Council of Canada: 4102009-1653 and the Fonds de recherche sur la socie´te´ et la culture du Que´bec: 145092 for their support during this study. DMPP – perceptual measure In general. We have shown that DMPP should be conceptualized as a formative construct. our formative index is conceptually superior to previous approaches that used reflective measures and includes four components that make significant contributions to DMPP and appear to be generalizable to many contexts. To what extent were innovative ideas considered as alternatives? To what extent were you creative in your decision making? Did you take into account new possibilities in your decision making? What was the importance of novelty in your decision making? To what extent did you use unusual approaches to make your decision? Exhaustivity of information I had enough information to analyze the alternatives. I had enough information to understand the problem. Our study has made a significant contribution to information systems research by proposing a reliable and valid measurement model of an important construct in information systems. I had enough sources of information to make the best possible choice. it appears important for the decision maker to have a full understanding of this context to arrive at a good decision. being aware of personal weaknesses may help a manager exercise more care in decision making. in the form of a questionnaire. I was completely immersed in solving this problem. Procedural rationality I evaluated all possible solutions before making my final choice. The information available was sufficient to solve the problem. Future research should examine this issue more closely. Such studies will allow researchers to explore the relative contributions made by each of the DMPP dimensions on variables that are theoretically linked. Finally. . the organization’s overall performance. and openness of spirit) that ensure better coverage of the construct. Moreover. we made a similar observation. I have considered the challenges associated with implementing the final decision. I was focused on decision making. Although these measures simplify the assessment of the measurement model. I used a high-performance approach to make my decision. 6. which is less complex in measuring objectively. The development of a simple instrument. 625 In conclusion. effort. Additional research will be required to determine how (and if) the weights of these dimensions vary from one context to the next and if this depends on the type of decision taken. I used enough decision criteria to arrive at the final solution. I analyzed each choice. thereby contributing to the advancement of knowledge and the construction of shared meaning. particularly in the DSS area. Conclusions Openness of spirit This study illustrates the importance of building proper definitions of constructs. I did not have enough information to reach a decision (reversed). which could lead to specific training in these areas.e. This improved definition of DMPP should lead to more accurate results in future studies by eliminating some biases that may have affected past results and conclusions. the construct may prove particularly useful to managers interested in studying the performance of their decision making process. Overall. and by validating this index according to best practices and its relationship with decision quality. these studies will help build a shared knowledge base that will provide a better understanding of various phenomena associated with decision making. Future studies. Additional research will be necessary to measure the relative impact of the components of DMPP on other external variables related to decision making. they nevertheless have some important limitations because it is understood that participants may be biased when evaluating their own problem solving approaches and the quality of their decisions. Items Decision Making Process Performance – Formative Construct Effort I put much effort into achieving this task. encouraging knowledge creation through the reuse of common tools. this study has mainly been based on the use of some perceptual measures in terms of both DMPP and decision quality. the exhaustivity of the information analyzed. I considered the risks associated with each alternative. consisting of four dimensions that capture its different characteristics (i. I made the required effort to solve the problem. We argue that the conceptualization of a construct must reflect its nature and the context of study. However. I identified the entire problem and its implications. such as the objective quality of the decision and corporate performance. I have considered the objectives related to each choice. / Information & Management 51 (2014) 618–626 This study has not examined how DMPP varies in different decision making contexts. Additionally. this study has added to the literature by proposing a grounded formative definition of the DMPP construct by identifying its main components. The same cannot be said for decision quality. procedural rationality. I have shown my eagerness to address the problem. Guillemette et al.M. indicating that our conceptualization of DMPP benefits from a certain nomological logic. Additionally. will benefit from a validated and well conceptualized construct. thereby improving personal performance in this area and. It has been empirically demonstrated that DMPP is a significant antecedent of decision quality. By drawing on a reliable and valid measure of the DMPP construct.G. Using our formative measure. and the costs of making this measurement are likely greater than its benefits. ultimately. represents an attractive self-assessment tool for managers who want to make sure that they build on each DMPP component to make the best possible decision. Appendix A. This will ultimately help the manager avoid continuously making the same mistakes. Acknowledgements We would like to thank our reviewers for their useful comments. Our measure will also help them identify weaknesses in the decision-making process. Arriving at an objective measure of the performance of a decision-making process would be complex. Manage. pp. I completely agree with the decision. Syst. 2004. Stud. Flexibility in strategic decision making: informational and ideological perspectives. cognitive effort. Bennett Thatcher. pp. MIS Quart. 787–803. [9] J. R. Technol. R. N. Inform. [23] M. 573–586. Wright. Manage. Lilien. Manage. 640–655. 203–214. 2011. 39. 105. D. T. J. Siguaw. Dean. 28. Decision support for cybersecurity risk planning. Process. Manage.F. Decis. Diamantopoulos. G. A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Rev.D. [6] R. A. 40. Improving decision making by means of a marketing decision support system. Evaluating the impact of DSS.W. Meyer. L. Barkhi. M. pp.L. Wickens. 34. Decis. 1997. [34] B. 2009. my decision-making process has been successful. In recent years. 21. 623–656. 2004. pp. 1993. pp. Roberts. Strategic decision-making: process perspectives. 30. Holder of a Master of Strategy Business Intelligence. Syst.d.W. MIS Quart. B. J. Support Syst. pp. 2003. Manage. Spires. J. Elbanna. 2003. Zimmermannb. pp. Jiang. 41–60. 2011. 10. Sci. 487–495. Manage. Oper. pp. Starke. Managerial perceptions of information technology and their impact from a transaction cost perspective. Straub.H. Inform. Behav.R. Smidts. Todd. Baets.A. M. 2008. 48. 48. 1–20. 481–489. Regret aversion and decision process quality: effects of regret salience on decision process carefulness. [19] G. Manage. Sci. 645–658. 2005. pp. Perceptions of accuracy and effort of decision strategies. Academic Press.W. Thatcher. S. pp. J.W. 313–320. my problem solving approach was effective. Res.-T. Manage.P. 169–182. Specifying formative constructs in information systems research.B. [14] G.B. Keppel. Gaissmaier. and the creator of the Master’s Degree in Business intelligence strategy. Organ.626 M.J. [30] C. Van Bruggen.A. Syst. at Universite´ de Sherbrooke.M. [28] L.d.B. I have adequately covered the entire issue with a complete analysis process. Saunders.L. 1999. 1069–1083. [29] D. Antonelli. J. Park. Manage. pp. Strategic information and strategic decision making: the EIS/CEO interface in smaller manufacturing companies. Reb. [15] R. Decis. Manage. Manage. Podsakoff. Strat. Psychological climate and decision-making performance in a GDSS context. 2006. Canadian Journal of Administrative Sciences. the International Journal of Business Intelligence Research. Nooraie. Polites. [12] A. Organ. pp. Becoming aware of the unknown: decision making during the implementation of a strategic initiative. Bassellier. Overall. Johnson. Manage. pp. Sharfman. Perolsb. Assoc. L. Ko¨nig.A. Rational decision making as performative praxis: explaining rationality’s E´ternel Retour. Klein.P. L. Bernd-Mathias. 2011. [26] G. is a Professor and Researcher of Information Systems Management at the University Sherbrooke (Canada). 24–36. Decision-making as a simplification process: new conceptual perspectives. [35] R. Communications of the Association of Information Systems. P. C. 1998. J. Behav. 30. Rangaswamy. Guillemette et al. Martin-Smith. 587–611. [11] J. 51. Manage. pp. [16] J.S. 2012. Syst. [2] R. Dean. N.P.H. J. Van Bruggen. I am sure that the decision will work well. 15. 451–482. 51–61. Longhi. 2012. 199–218. 2011. 2007. G. 493–505.Business Intelligence Research Group. p. Syst. 1993. An empirical investigation of the effects of data warehousing on decision performance. Eur. 2011. Sci. Roberts. 31. McKenna. Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. Judgment. Gigerenzer. [31] M. Business professionals’ perceptions related to the influence of information technology in individual work. Inform. Hum. A.L. [13] S. Riedla. Almeida. Psychol.K. and Decision Making. I used a comprehensive problem solving approach to make my decision. Inform. [4] M. 43. [24] Y. 24. 30. Int. 34. Inform. pp.. 10. Miranda. Sci. 2003. 157–165. Organ. 1996. Payne. W. Heuristic decision making. D. He recently co-editor a book on sustainable development for canadian businesses. Baker. . Petter. [10] J.C. 133–153. [18] E. Measurement. pp. F. Jean Cadieux Ph. Decision quality – perceptual measure I am satisfied with the decision. I.G. Manon G. 1998. Interpretation of formative measurement in information systems research. Travel Tourism Mark. Guillemette Ph.A. is an associate professor of Information Systems. 368–396. [21] G.T. 191–217. Sharfman. Res. Kaufmanna. PMP works in Montreal. 46. Manage. The decision is of high quality. pp. J. 17. perception. Gond. IT management and IT governance. Manage. 395–414. pp. J. Res. Information acquisition in group decision making. Organ. Inform. K. 2006. [32] P. pp. 2003. pp. Dean. MacKenzie.-C. he has experience in the areas of transportation. He also managed projects portfolios in accordance with business strategies. Decis. Cenfetelli. M. 2012. Does decision process matter? A study of strategic decision-making effectiveness Acad. 62. Inform. pp. Findings from her work have recently appeared in MIS Quarterly. G.D.K. [8] P.J. S.P. J. Birnbaum. pp. Br. Annu. Jarvis. A. Her work has been received with great interest by both the academic and professional communities. [25] S. I like the decision. Decis. 22–48. Espejo. E. Situational influences on ethical decision-making. pp. Rev. pp. J. 91. pp. pp. Pearson Prentice Hall. Walters. pp. Design and Analysis: A Researcher’s Handbook. [27] J. Process. pp. Leonard.M.D. the Director of PRISME . and Syste`mes d’information et Management. pp. Manage. Operationalizing multidimensional constructs in structural equation modeling: recommendations for IS research. [33] G. 33.B. implementation and use of KPE for executives and managers. M. J. J. San Diego. J. Deane. White. B. Reducing uncertainty in supplier selection decisions: antecedents and outcomes of procedural rationality. Haines. 263. Inform. J. [3] A. 24. pp.K. Rees. W. Klingebiel. Inform. 216–235.P. 1998. Conceptualizing models using multidimensional constructs: a review and guidelines for their use. Benbasat.T. Procedural rationality in the strategic decision making process. 31. A.B. pp. 1985. 8. Inform. Overall. 4th ed.W. Decis. Chu. Decision magnitude of impact and strategic decision-making process output.E. 2007. DSS effectiveness in marketing resource allocation decisions: reality vs. Manage. / Information & Management 51 (2014) 618–626 Overall. 356–374. Her research interests include organizational aspects of business intelligence. Stud. Canada as a senior advisor IT performance management. Hough. The relationship between procedural rationality and political behavior in strategic decision making. Kao. 24.-P.L. Dean.H. 125–134. 689–707. 821–836. [22] R. Inform. Y. Sharfman. References [1] R. Hum. J.J. manufacturing and financial services. J. Rai. Cabantous. 2013. Overall.H. Manage. His current research interest include Information system and sustainable development. Environmental dynamism and strategic decision-making rationality: an examination at the decision level.E. Wierenga. Campbell. New Jersey. [7] P. 2006. 44. Information & Management. Commun. 2008. Maxime Laroche M. 43. Canada. pp. Sharfman.Sc. J. 44. A complexity perspective on collaborative decision making in organizations: the ecology of group-performance. Law. Effort and accuracy in choice. J. and incentives on strategy selection. 2013. Sci.N. 22. 367–412. Chathotha. 55–74. [17] C. [5] L. J. 31. [20] R. 2011. W. M. he managed projects related to the definition. Consum.