دانلود مقاله ISI انگلیسی شماره 19264
عنوان فارسی مقاله

اثر ارائه هزینه کل اطلاعات مالکیت بر وزن شاخص در تصمیم گیری خرید

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
19264 2011 11 صفحه PDF سفارش دهید 9800 کلمه
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عنوان انگلیسی
Effects of providing total cost of ownership information on attribute weights in purchasing decisions
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Purchasing and Supply Management, Volume 17, Issue 2, May 2011, Pages 132–142

کلمات کلیدی
هزینه کل مالکیت - تصمیم گیری خرید - انتخاب تامین کننده
پیش نمایش مقاله
پیش نمایش مقاله اثر ارائه هزینه کل اطلاعات مالکیت بر وزن شاخص در تصمیم گیری خرید

چکیده انگلیسی

Total Cost of Ownership (TCO) involves the monetary quantification of nonfinancial attributes and the subsequent aggregation of these attributes into a financial summary measure. We consider monetary quantifications that are not perfect, because some attributes are missing from the TCO information. We investigate how the provision of TCO information affects attribute weights, and how this effect is moderated by the Comprehensiveness of quantification and the decision-maker’s experience. We conducted experiments with 817 participants, both students and managers. We found that student participants were more inclined to give a higher weight to the attribute missing from the TCO information, while the practitioner participants tended to give less weight to the missing attribute. Within the group of practitioners, the pattern was strongest for the most experienced practitioners. The results suggest that experienced decision makers might be less mindful of the imperfections of monetary quantification.

مقدمه انگلیسی

Purchasing decisions involve choices between alternative supplier offerings, characterized by different attributes, such as acquisition price, product quality, and the supplier’s delivery reliability. Often these different attributes are non-comparable, because their measurement units are not commensurable, making multi-attribute decision-making exceedingly difficult for managers (Bettman et al., 1998). Total Cost of Ownership (TCO) information can potentially support purchasing decision makers through the monetary quantification and aggregation of attributes. Specifically, attributes that are not initially expressed as a financial unit of measure are “translated” into financial numbers. These financial numbers are subsequently aggregated into a summary measure (Anderson and Dekker, 2009b, Carr and Ittner, 1992, Degraeve et al., 2000, Degraeve et al., 2004, Ellram and Siferd, 1998 and Wouters et al., 2009). Not every consideration that matters in a business setting, however, may be quantifiable in monetary terms (Galbraith, 1973 and Chapman, 1997). We investigate what happens when some nonfinancial attributes are monetarily quantified and included in the TCO information, while other nonfinancial attributes are not monetarily quantified and therefore not included in the TCO information. Do the attributes that are not included in the aggregate financial TCO information receive more or less weight as a result of providing the purchasing decision maker with imperfect TCO information? Financial information is particularly influential in decision-making ( Reck, 2001, Kadous et al., 2005 and Nollet et al., 2008). As a result, monetary quantification may inadvertently draw attention away from attributes that are not expressed financially. We will investigate the Comprehensiveness of quantification and experience as moderating variables. Comprehensiveness refers to the number of attributes that are included in the overall TCO summary measure. Experience refers to general professional experience that leads to an understanding of purchasing, operations, and the usage of cost information in organizations. Experience does not refer to specific, technical accounting knowledge. Experiments were conducted with students and managers, 817 participants in total. The purchasing decision involved making a choice between two brands (A and B) for a similar new machine in a production department; the selection of Brand B was the dependent variable (Choice B). The experiment used a 2×2×2×2 between-participants design: the three manipulated, independent variables are availability of Total Cost Information (TCO info), the Comprehensiveness of the information provided (Comprehensiveness), and the uptime of Brand B (Uptime B); Experience was a measured, fourth independent variable. Thus, there were 16 cells with different experimental conditions. This study did not consider incentives, and no information about reward structures related to this purchasing task was provided. We found that decision-makers adjusted their strategy depending on the situation. When few attributes were included in the TCO measure (Comprehensiveness is low), we found that students put more weight on the attribute that was not included in the TCO measure, consistent with Hypothesis 1. For practitioners this condition did not yield a statistically significant result. When more attributes were included in the overall TCO measure (Comprehensiveness is high), we found that practitioners put less weight on the missing attribute, consistent with Hypothesis 2. However, students still put more weight on the missing attribute, contrary to Hypothesis 2. We also conducted further analyses by splitting the group of practitioners into more and less experienced subgroups. We found that the results for the less experienced subgroup resembled the students’ results more than the results of the more experienced subgroup. Taken together, these findings suggest that Experience is an important factor, and providing TCO information to experienced decision makers may lead them to put less emphasis on attributes that are not incorporated in the cost information. The remainder of this paper is structured as follows. In the next section, the background of this paper is introduced in more detail and our hypotheses are developed. Subsequently, the resea

نتیجه گیری انگلیسی

Alternative purchasing options can be described by several attributes. Some are financial in nature, while other attributes describe functionality, performance, or another nonfinancial characteristic. Deciding which option to choose, involves multi-attribute decision-making, which is cognitively challenging for human decision-makers. They adjust their decision strategies to the particular decision they have to make. We looked at purchasing decisions where participants, in an experimental setting, had to choose between two alternatives (Brand A or B) that were both characterized by several attributes. In one half of all conditions, TCO information showed the total cost per hour of each brand, but one of the attributes was not included in the TCO information. We investigated the weight of this missing attribute. As a result of TCO information availability, would participants primarily look at the TCO numbers and pay less attention to the missing attribute (“ignore” strategy), or would they instead tradeoff the TCO information against the non-included attribute, hence, giving more weight to that attribute (“tradeoff” strategy)? The “tradeoff” strategy is more difficult than the “ignore” strategy. According to Hypothesis 1, when Comprehensiveness is low, we expected that the “tradeoff” strategy would be used and the weight of the not-included attribute would increase. According to Hypothesis 2, when Comprehensiveness is high, we expected that the “ignore” strategy would be used and the weight of the not-included attribute would decrease. The decision strategy would be adjusted, because the more comprehensive TCO information encompasses a larger number of attributes, which makes the information more convincing, and leads to use of the “ignore” strategy with a lower weight of the not-included attribute. For low Comprehensiveness ( H1), the hypothesis was not supported by the results for all participants. However, separate analyses showed support within the student group. As a result of providing them with TCO information, students put more weight on the attribute that was not included in the TCO. There were no significant results for practitioners—not even in the more and less experienced practitioner subgroups. For high Comprehensiveness ( H2), the results supported the hypothesis for the practitioner group as a whole, as well as for the most experienced subgroup of practitioners. As a result of providing the experienced practitioners with TCO information, these decision makers put less weight on the attribute that was not included in the TCO. Results were not significant for the less experienced practitioners, and H2 was rejected for students. The consistency in this pattern is remarkable. Taken together, the results strongly suggest that experience is an important determinant of the use of TCO information in complex multi-attribute decisions. They also suggest that experienced decision makers, when provided with TCO information, become more likely to give a lower weight to attributes that are not compounded in the TCO information. The bottom line is that, as summarized in H3b, experience may lead decision makers to focus more on TCO as the overall decision criterion with less sensitivity to the fact that such information may be imperfect. The results of this study have managerial implications for the introduction and use of TCO information. Improved costing information that captures financial impact by aggregating financially quantifiable attributes may be helpful for the decision maker, but care should be given to unintended effects—the aggregate financial information may draw attention away from those elements that are not included in the aggregate measure. This suggests that when introducing TCO information, the limitations should be clearly explained to managers. It is also important to give a prominent position in costing reports to the excluded attributes. It might also be helpful to organize discussions about the newly recognized tradeoffs that are involved, in addition to holding managers accountable for recognizing the tradeoffs between financial and nonfinancial considerations in purchasing decisions. Several limitations of this study should be mentioned. One limitation is that no quantitative data were gathered regarding the decision process, such as how many seconds it took to make the decision. Qualitative data (such as impressions of the load imposed by the task) were also not gathered. We did not require participants to think aloud or explain their decision. Although this might have given more insights into the decision strategies that participants followed, with a more time-consuming design we would not have been able to attract the same number of participants. Another limitation of the paper is that the role of financial incentives was not investigated. Because the theoretical motivation for the hypotheses did not depend on such incentives, these were excluded from the experimental task. However, practitioners are more likely to face financial incentives based on financial results, potentially leading them to focus on the “bottom-line” effect of any purchasing decisions in the experiments—despite the fact that financial incentives were not included in the experiments. This may be different for students, who have not been exposed to such incentives. In future research, this issue could be addressed explicitly. If TCO information is Comprehensive, do practitioners place less weight on attributes not included in a TCO report because of the perceived Comprehensiveness of the TCO information, or because they are focused on the financially quantified attributes due to performance evaluation and/or financial incentives? An obvious avenue for future research would be to test cognitive process explanations for the effects we obtained. This would require a research plan in which thought processes are either traced or manipulated, and choices are recorded for the same participants. Only such a design would allow investigating whether and how these thought processes mediate the relationships between the experimental conditions and the participants’ choices. A direct examination of the decision making process would be very interesting, and would require a different and much longer experimental task with better control of random environmental noise, probably only obtainable in a lab study with students or other non-expert participants. Furthermore, future research could address other variables that affect decision processes using TCO information, or other ways in which TCO information is not “perfect”. Finally, while individual decision-making was investigated in this study; future research could also investigate the use of imperfect costing information in decisions that are made in a social context. For example, the weight of attributes not included in TCO information may also depend on the need to justify purchasing decisions to senior management or to obtain support from other functional areas (e.g., Tetlock, 1983).

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