Information Collection Strategic Design in Experts-assisted Decision Making Paradigm

In an experts-assisted decision making paradigm, the information collection design becomes a strategic variable under a weak assumption that the final decision is dependent on the design used to collect information as well. As a result, the same information of the experts and the decision maker about the problem can potentially produce different final decisions for different information collection designs. The implication is that a decision maker can strategically select a design which serves his/her objective. This paper uses a Bayesian estimation methodology for combining experts' information with the decision maker's prior. An information collection process is designed by setting constraints on this model. Several designs are developed here using such controlled factors as a one-stage versus a two-stage decision process, experts' rank ordering, and group versus individual lobbying/consultation. An example is provided to illustrate the applicability of the concept. It is shown that the information produced in the process of producing a decision can also give insights into the impacts of the decision maker and the experts on the decision.     

The effects of relationships and justification in an interdependent allocation task

Two factors, the type of relationship between the involved parties and the justification of the decision maker for being in his or her position, are predicted to influence resource allocation decisions. These predictions are based on a synthesis of several forces, including self-interest, a politeness norm, and a norm of reciprocity, that we argue underlie the selection of allocation norms that guide interdependent resource allocation decisions. An ultimatum bargaining game, in which player 1 divides a resource ($10) and player 2 decides to either reject or accept this division, is employed in a laboratory study to test the hypotheses. For subjects in the player 1 position, subjects with friends as player 2 or those assigned to their position randomly allocated lower amounts of money to themselves than did subjects with strangers as player 2 or those who earned their position. Friends in the player 2 position demanded significantly less to reach an agreement than strangers. These and other results are discussed in terms of the various allocation norms, particularly equity and equality, that appeared to influence subjects' decisions.     

A Study on Aggregation of TOPSIS Ideal Solutions for Group Decision-Making

The technique for order preference by similarity to ideal solution (TOPSIS) has become a popular multi-criteria decision making (MCDM) technique, since it has a comprehensible theoretical structure and is able to provide an exact model for decision making. For the use of TOPSIS in group decisions, the common approaches in aggregating individual decision makers’ judgments are the geometric and the arithmetic mean methods, although these are too intuitive and do not consider either preference levels or preference priorities among alternatives for individual decision makers. In this paper, a TOPSIS group decision aggregation model is proposed in which the construction consists of three stages: (1) The weight differences are calculated first as the degrees of preferences among different alternatives for each decision maker; (2) The alternative priorities are then derived, and the highest one can be denoted as the degree to which a decision maker wants his most favorite alternative to be chosen; (3) The group ideal solutions approach in TOPSIS is used for the aggregation of similarities obtained from different decision makers. A comparative analysis is performed, and the proposed aggregation model seems to be more satisfactory than the traditional aggregation model for solving compromise-oriented decision problems.     

New product decision making: How chance and size of loss influence what marketing managers see and do

This article empirically examines, in a new‐product decision context, the relationships among risk propensity, perceived risk, and risky choice decisions, when risk is operationalized as the chance of loss and the size of loss. The results indicate that perceptions of chance of loss directly influence choice among alternatives possessing different chances of loss and gain, whereas risk propensity directly influences choice among alternatives that differ in their size of loss and gain. The findings extend previous research by identifying dimension‐specific effects (a) between who the decision maker is and the size of an investment's potential loss, and (b) between what the decision maker sees and the chance that an investment will experience a loss. These results not only contribute to theory, but also provide marketing managers with guidance for their risky choice decisions. The composition of a new product's risk has implications for the decisions marketing managers make, for the placement of managers in risk‐sensitive positions, and for the presentation of information to individuals with oversight responsibility for the firm's product strategy decisions. © 2002 Wiley Periodicals, Inc.     

Managerial judgment and forecast combination: An experimental study

This paper examines the role of managerial judgment in forming a final forecast, or judging the achievability of a critical level of sales, when multiple forecasts or opinions are available to the decision maker. Several factors that can help improve the quality of human intervention are identified and incorporated in a decision aid. Experimental results show that aided combination can help the decision maker exploit her relevant private information and mitigate the generally observed negative effects of human intervention. Further, the results suggest that emphasizing expected sales, even when the organization is primarily interested in go/no-go decisions, helps improve performance. Several suggestions for future research are presented.

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A lack of insight: do venture capitalists really understand their own decision process?

What decision criteria do venture capitalists (VCs) use to make their investment decisions? This question has received much attention within entrepreneurship literature (i.e.,Wells 1974; Poindexter 1976; Tyebjee and Bruno 1984; MacMillan, Seigel, and Subba Narasimha 1985; MacMillan, Zeman, and Subba Narasimha 1987; Robinson 1987; Timmons et al. 1987; Sandberg, Schweiger, and Hofer 1988; Hall and Hofer 1993; Zacharakis and Meyer 1995) for a number of reasons. First, VC-backed ventures achieve a higher survival rate than non-VC-backed businesses (Kunkel and Hofer 1990; Sandberg 1986; Timmons 1994). Second, a better understanding of the decision process may lead to even better survival rates. Finally, entrepreneurs seeking venture funding benefit if they understand what factors are most important to the VC.Although past research has greatly contributed to our understanding of the decision, it may be biased and somewhat misleading. The majority of past studies rely on post hoc methodologies (e.g., interviews and surveys) to capture the decision process. Post hoc methods assume that VCs can accurately relate their own decision processes, but studies from cognitive psychology suggest that people, in particular experts, are poor at introspecting. Introspection is subject to rationalization and post hoc recall biases. Using social judgment theory and the associated lens model as a framework, the current study investigates how well VCs introspect about their own decision process and, by extension, whether the past research efforts are biased.The current research uses policy capturing, a real-time method common in cognitive psychology, to capture the VC's “actual theories in use” versus their “espoused theories” (Hitt and Tyler 1991). Policy capturing requires that VCs make a series of real-time decisions based on various information factors. Regression analysis of each VCs' decision captures how important each of the information factors is to her/his actual decision process. After the VCs make their decisions, they provided a weighting of how they believe they used the information factors. Comparing the captured decision policies to stated decision policies provides a measure of VC insight.The findings suggest that VCs are not good at introspecting about their own decision process. Even within the confines of a controlled experiment, which greatly reduces the amount of information considered, VCs lacked strong understanding of how they made decisions. Most decision-makers would like to have all relevant information available for their decision. However, as more information becomes available, insight diminishes. Finally, this study finds that VCs are very consistent in their decision process, even though they do not necessarily understand how they make their decisions.VCs face a plethora of information when making an investment decision (i.e., business plan, outside consultants, due diligence, etc.). It may be difficult for VCs to truly understand their intuitive decision process because of all the noise caused by this information overload. This lack of systematic understanding impedes learning. VCs cannot make accurate adjustments to their evaluation process if they do not truly understand it. Therefore, VCs may suffer from a systematic bias that impedes the performance of their investment portfolio. The methodology used in this experiment can be modified and used as a training tool for active VCs. In addition, the consistent nature of VC decision-making (even if they do not have a strong understanding of that process) is favorable to the development of decision aides. Decision aides can minimize the danger of salient information (e.g., the lead entrepreneur is a winner) clouding the VC's judgment.Past research also needs to be interpreted in a new light. Although VCs undoubtedly use some of the information cited in past studies, the relative importance of that information needs to be reevaluated. VCs may not, for instance, rely most on the background of the entrepreneurial team. In addition, it is likely that the past studies provide more information factors than VCs actually use. People have a tendency to overstate the information they believe they relied upon and to use far less information (typically three to seven factors) to make a decision than they actually think they use. The methodology used in this experiment has the potential to identify the more relevant information factors cited in previous work.Even though VCs are experts in the new venture funding realm, their decision process has room for improvement. Almost 40% of all backed ventures fail to provide a return to the VC. Considering the billions invested each year, a modest improvement in the failure rate can have a substantial impact on venture portfolio returns. That improvement starts by better understanding the decision process. This study is a step in that direction.     

Window displays and consumer shopping decisions

Window displays are an ubiquitous and prominent but under-researched element of retail strategy. This paper explores how the store and product category information communicated by a store's windows are related to consumers’ shopping decisions, such as store entry and product purchase, and how these relationships vary for consumer segments that differ in terms of their knowledge of the retailer's product(s). Results of a study conducted in the context of clothing retailers demonstrate that the store entry decision is related both directly as well as indirectly (through acquisition of inferred, store-related information) to the acquisition of observed, store-related information from window displays. However, it is product category-related information (e.g. fashion and product-self fit) rather than store-related information (e.g. merchandise and store image) that is more strongly associated with the product purchase decision. Moreover, consumers with medium levels of clothing knowledge are more influenced by windows in their shopping decisions than those with low or high levels.     

Retail Centres: Location and Consumer's Satisfaction

Analysts rarely consider that commercial malls offer a global service to the consumer. It is commonly assumed that the consumers' decision concerning the place they choose usually for shopping depends essentially on the distance to the mall. This paper shows that, for such decisions, the consumer's satisfaction (an indicator widely used for evaluating the quality of a service) plays at least an equally important role in metropolitan areas where commercial zones are numerous enough to lead consumers to choice decisions. How the consumer builds up his/her satisfaction is the second point of this article. Different aspects (perception of shopping possibilities, expected pricing practices, general global environment) of each commercial zone do combine in the consumer's mind producing satisfaction or dissatisfaction. In these combinations, access conditions appear clearly to play a secondary role. It confirms that the two variables (access and satisfaction) are independently assessed by consumers. The city centre pedestrian streets are generally evaluated by the consumers with the same criteria as the outer commercial malls but they differ on some important aspects. These differences distinctly arise from specific consumers expectations towards the two kinds of commercial zones.     

The nature of information and overconfidence on venture capitalists' decision making

Venture capitalists (VCs) are considered experts in identifying high potential new ventures—gazelles. Thus, the VC decision process has received tremendous attention within the entrepreneurship literature. Yet, most studies on VC decision-making focus on which decision criteria are central to selecting gazelles. Although informative, the majority of these studies has neglected cognitive differences in how VCs make decisions. This is surprising considering the influence cognitive differences are likely to have on the exploitation of an opportunity as well as its influence on likely success. The current study investigates whether VCs are overconfident, as well as the factors surrounding the decision that lead to overconfidence.Overconfidence describes the tendency to overestimate the likely occurrence of a set of events. Overconfident people make probability judgments that are more extreme than they should, given the evidence and their knowledge. In the case of the new venture investment decision, overconfident VCs may overestimate the likelihood that a funded company will succeed.The results of the current study indicate that VCs are indeed overconfident (96% of the 51 participating VCs exhibited significant overconfidence) and that overconfidence negatively affects VC decision accuracy (the correlation between overconfidence and accuracy was 0.70). The level of overconfidence depended upon the amount of information, the type of information, and whether the VC strongly believes the venture will succeed or fail.As more information becomes available, people tend to believe they will make better decisions; they are making a “more informed decision.” More information ideally should enable the VCs to assess any potential pitfalls. However, additional information makes the decision more complex. Information factors may contradict and relate to other information in unexpected ways. Even if more information is available, people usually don't analyze all of it (even though they believe they do). Thus, more information creates greater confidence, but it also leads to lower decision accuracy.The type of information that is available also impacts overconfidence and decision accuracy. VCs are intuitive decision makers. When people are familiar with a decision and the structure of the information surrounding that decision, they resort to automatic information processing. On the other hand, if information surrounding the decision is structured in an unfamiliar way, people need to decipher what each piece of information means and how that impacts their overall accuracy. In the case of expert VCs, that means they must deviate from their intuitive style. It seems that forcing them outside their “comfort zone” has a negative effect on their confidence and has an even greater effect (negative) on their accuracy.There is evidence of an “availability bias” in VC decision-making; VCs rely on how well the current decision matches past successful or failed investments. VCs are overconfident in their prediction of venture success when they predict a very high level of success. VCs are also overconfident in their prediction of venture failure when they predict a very low likelihood of success. This high level of overconfidence in success predictions (or failure predictions) may encourage the VC to limit information search and fund a lower potential investment (or prematurely reject a stronger potential investment).Although overconfidence in itself does not necessarily lead to a wrong decision, the bias is likely to inhibit learning and improving the decision process. Overconfident VCs may not fully consider all relevant information, nor search for additional information to improve their decision. Moreover, the natural tendency for people to recall past successes rather than failures may mean that VCs will make the same mistakes again. VCs can take simple steps to reduce the effect of overconfidence, including counterfactual thinking (i.e., imaging scenarios where current assumptions might not hold), formally recording how past decisions were made at the time of the decision (versus trying to recall how that decision was made from memory), and using actuarial decision aids that decompose decisions into core components. Reducing overconfidence may lead to stronger decisions. It is hoped that this study illustrates the power of cognitive theories for understanding VC decision-making.     

The relative importance of time and dollar values in new product introduction decisions

This study investigates managerial sensitivity to timing differences in new product introduction decisions. Using a case scenario as the research setting, the study finds that in managerial decisions involving a choice between two-attribute alternatives (dollar value and time), respondents shifted their emphasis between attributes when they were personally affected by the decision outcome. Specifically, it was found that an additive constant manipulation (adding a constant to the dollar amount of each alternative) caused respondents to place more emphasis on the time attribute, and a multiplicative constant manipulation (multiplying the dollar amount of each alternative by a constant) caused them to place more emphasis on the dollar-value attribute.The study asks 108 subjects to assume the role of product manager in a case scenario and choose from among three two-attribute alternatives proposed by the case. The personal relevance of the decision was manipulated by telling respondents that the CEO in the decision scenario had stated publicly that the career of the decision maker would be (would not be) affected. The results show that the additive constant and multiplicative constant effects were only found when the decision outcomes would affect the respondents' career.     

Material Distortion of Economic Behaviour and Everyday Decision Quality

Misleading information and unfair commercial practices have to be viewed against the background of what consumers otherwise do, i.e., what their purchase decisions look like when no misleading information or no unfair commercial practices are in place. This article provides some of this background by studying how consumers sample information when making an in-store purchase decision. This was done by an eye-tracking study which reveals to what extent consumers succeed in purchasing the products that best meet their purchase intentions when only a representative amount of misleading information is present. The study shows that decisions were suboptimal in relation to what the consumers claimed they wanted to purchase. Only in one product category did consumers in this study actually look at products that were slightly better than average, and as a result, they mainly selected products that were just as often poor as good. If the proportion of bad purchase decisions based on misleading information is small enough, perhaps it might be better to direct the authors’ attention to other ways of improving the decision environments that consumers encounter. In addition, the eye-tracking study provides some insight into how consumers sample information when making an in-store purchase decision. The present data show that consumers invested on average of less than 1 s to look at products.     

A Calibrated Group Decision Process

In practice most organisational decisions are made by groups that bring into the problem multiple perspectives, both complementary and contradictory. When having a group of decision makers, usually individuals’ preferences are either led to consensus or are aggregated with the use of some function like the median, the arithmetic or geometric mean. We focus in the second case, where individual’s preferences need to be aggregated. Our approach is based on the fact that when two decision makers are asked to give their preference between a pair of criteria using a specific scale, it is possible that they will give slightly different answers, even when they actually have the same opinion. This difference will not affect the case of a single decision maker, as it will be consistent throughout the whole process. However, it can affect a group decision when the values will be used as an input for the aggregation function. A novel approach is presented that enhances group decision making through a group calibration process. The proposed process adjusts individuals’ preferences based on their answers on a set of standardized questions prior to the aggregation phase. The method focuses The whole concept is applied to the group analytical network process method and it is illustrated through a telecommunications project case. The decision under examination concerns the selection of the right place for deploying a new telecom service of a multinational-based telecommunications company where a group of geographically dispersed decision makers form an ad-hoc virtual team in order to select the location for a new technical support centre.     

Entrepreneurs in the making: Six decisions for fostering entrepreneurship through maker spaces

Maker spaces—shared production facilities offering access to basic and advanced manufacturing technologies—have quickly become the latest must-have for universities, large corporations, and communities looking to foster entrepreneurship and innovation. While the entrepreneurial and educational prospects of maker spaces are certainly intriguing, questions remain concerning their design and effectiveness. Drawing primarily on case evidence and conversations with five maker spaces located across the U.S., we identify and present six key decisions for maker space leaders looking to foster entrepreneurship in their organizations. We conclude with a decision framework for maker space leaders and a series of questions for entrepreneurs as both groups work to pursue entrepreneurship through and in maker spaces.     

A hierarchical utility model for the dynamic acquisition of heterogeneous items

This paper develops a model for situations in marketing and elsewhere in which an individual decision maker acquires multiattributed items that belong to several classes over time. The model captures the dynamic acquisition of heterogeneous items. Measurement and parameter estimation methods are described and illustrated with a small set of experiment data involving the acquisition of durable goods by households. Future research steps are also outlined.     

Diversification and market entry choices in the context of foreign direct investment

Multinational enterprises (MNEs) consider many factors when making decisions in the context of foreign direct investment (FDI). The MNE must decide whether to diversify or to concentrate on its main line of business (LOB). It must also decide whether to enter into a foreign market through a greenfield or acquisition strategy. This paper analyzes both decisions. The international business literature has generally treated these strategic choices as independent. This paper introduces a more realistic selection model, in which the diversification choice and the entry mode choice are made sequentially, and are therefore related. The model is tested using a data set of FDI into the United Kingdom by MNEs in engineering and related industries. The analysis indicates a strong relationship between the diversification choice and the entry mode decision. In virtually all cases, the statistical significance of the selection model is higher than that of the independent model, indicating an improvement over previous research. Overall, the results indicate that the decisions on product diversification and foreign mode of entry are related. Diversified firms are more likely to enter through acquisition. Firms focusing on their main LOB are more likely to enter through greenfield entry. The paper also identifies a number of managerially relevant factors affecting these relationships.     

A Hierarchical Clustering Approach Based on Three-Dimensional Gray Relational Analysis for Clustering a Large Group of Decision Makers with Double Information

Two types of information, collectively referred to as double information, are usually required in management decision-making. The first is preference information expressed in a judgment matrix. The second is reference information expressed in a multi-attribute decision matrix. In this paper, we investigate large-scale group clustering problems with double information in group decision-making. We first establish a novel three-dimensional gray correlation degree index, which integrates the alternative decision-making vector, index vector and alternative preference vector, to fully excavate the correlation between decision makers with double information. We then develop a new clustering procedure combining three-dimensional gray relational analysis and the concept of hierarchical clustering. Moreover, a model for determining clustering centers is established on the basis of the maximum gray correlation degree within each cluster and minimum gray correlation degree among clusters. A heuristic algorithm for the model to identify the core decision maker in each cluster is proposed. Finally, we illustrate the applications of the developed procedures with a practical case. The rationality of the proposed method is demonstrated by comparing results with results obtained using other methods, including the traditional gray clustering method and hierarchical clustering method with single information; i.e., preference information or reference information.     

Mixed Motives and Ethical Decisions in Business

Discerning the motives that lead businesspeople to make ethical decisions in economic contexts is important, for it aids the moral evaluation of such decisions. But conventional economic theory has for too long assumed an egoist model of motivation, to which many contrast an altruist view of ethical choices. The result is to see business decision making as implying dilemmas. On the other hand, we argue, if one assumes multiple motives, economic and ethical, in ordinary business decisions, a more fruitful model of ethical motivation in such decisions emerges. In this paper multiple motives are assumed to be the norm in a world of large organizations, complex decisions and stakeholder management. An example of a technology acquisition decision, with environmental overtones is presented in illustration of this approach. A method for discerning motives, primarily in terms of behavioural efficacy is presented. On this basis a two step approach to morally evaluating mixed motives in business decisions is proposed. First, the fit of motives with substantive ethical values should be ascertained, and then the efficacy of moral motives in yielding ethical behaviour and outcomes should be determined. This approach, we conclude, offers a much more concrete model of the actual role of moral motives in business decision making. It also signals the importance of moral learning in organizations.     

Capture and Dissemination of Specialized Knowledge in Network Organizations

I present a model for the capture and retrieval of organizational memory that can help overcome the information dissemination problem faced by network organizations. Network organizations are made of small, heterogeneous, product-oriented teams. In these organizations, the specialization of knowledge that has characterized functional hierarchies can be lost as the functional units in which this expertise was created and shared are dismantled. The preservation and dissemination of expert knowledge thus becomes a major issue to be addressed by these organizations, whose competitive advantage depends on this specialization. The problem of capturing project-related organizational memory is addressed with a 3 step solution: (a) the use of explicit work processes; (b) the development of models capable of representing these processes, the artifacts that are developed, and the rationale used during decision making; and (c) the implementation and deployment of computer tools that support the development processes selected and that, in doing so, record and document the project. I address the problem of accessing information from projects developed elsewhere in the organization and propose a solution based on monitoring the user's manipulation of information and creating hypotheses of his or her information needs. These hypotheses are then used as queries by a fuzzy information retrieval engine that produces a ranked list of documents that are suggested to the user as being relevant to his or her information needs. As the user manipulates these documents, the hypothesis is updated, triggering a new retrieval and the update of the list of suggested documents. The feasibility of the approach is demonstrated with the implementation of a prototype.     

Competitive judgments in a business simulation: A comparison between American and Chinese business students

A complex total business enterprise computer simulation was used as the setting for a study of judgments by Chinese and American business school students. The subjects were asked to make a series of decisions and give judgments about expected levels of competition for a new market opportunity in the simulation world. Decisions were compared across the groups based on the decision structure and content. The results confirm previous research as the American participants generated significantly more responses overall, and especially judgment-consistent responses than the Chinese participants. Analysis of the content of the decision representations found that the relative proportion of singular to distributional information in the responses was similar for both American and Chinese individuals when making decisions about their own teams, but the Chinese participants focused more heavily on distributional information when making judgments about the behavior of others. This implies that American and Chinese individuals focus on different aspects of similar information and this may influence subsequent judgments. © 1998 John Wiley & Sons, Inc.