Abstract:In markets where buyers and suppliers negotiate, supplier costs, buyer willingness to pay, and competition determine only a range of potential prices, leaving the final price dependent on other factors (e.g., negotiating skill), which I call bargaining ability. I use a model of buyer demand and buyer-supplier bargaining, combined with detailed data on prices and quantities at the buyer-supplier relationship level, to estimate firm-bargaining abilities in the context of the coronary stent industry where differe… Show more
“…A companion paper, Grennan (2012), explores this issue further, but data limitations prevent more than a high-level, descriptive analysis. Anecdotal evidence from industry professionals suggests that there are economic forces such as human capital and organizational structure/incentives underlying these firm-level bargaining abilities.…”
Section: Summary and Discussionmentioning
confidence: 99%
“…With standard deviation of 0.07, however, there is significant variation around this mean. A companion paper, Grennan (2012), uses the panel structure of the data and hospital characteristics to further explore this bargaining ability variation. Importantly for this study, the panel data allows for a regression of ln( β jh ν jht ) on manufacturer and hospital dummy variables, and the coefficients on each firm dummy variable ( β j , β h ) provide a measure of the average bargaining ability of each firm across bargaining partners and over time.…”
Section: Bargaining Distribution Estimatesmentioning
Many important issues in business-to-business markets involve price discrimination and negotiated prices, situations where theoretical predictions are ambiguous. This paper uses new panel data on buyer-supplier transfers and a structural model to empirically analyze bargaining and price discrimination in a medical device market. While many phenomena that restrict different prices to different buyers are suggested as ways to decrease hospital costs (e.g., mergers, group purchasing organizations, and transparency), I find that: (i) more uniform pricing works against hospitals by softening competition; and (ii) results depend ultimately on a previously unexplored bargaining effect. (JEL C78, L13, L14, L64)
“…A companion paper, Grennan (2012), explores this issue further, but data limitations prevent more than a high-level, descriptive analysis. Anecdotal evidence from industry professionals suggests that there are economic forces such as human capital and organizational structure/incentives underlying these firm-level bargaining abilities.…”
Section: Summary and Discussionmentioning
confidence: 99%
“…With standard deviation of 0.07, however, there is significant variation around this mean. A companion paper, Grennan (2012), uses the panel structure of the data and hospital characteristics to further explore this bargaining ability variation. Importantly for this study, the panel data allows for a regression of ln( β jh ν jht ) on manufacturer and hospital dummy variables, and the coefficients on each firm dummy variable ( β j , β h ) provide a measure of the average bargaining ability of each firm across bargaining partners and over time.…”
Section: Bargaining Distribution Estimatesmentioning
Many important issues in business-to-business markets involve price discrimination and negotiated prices, situations where theoretical predictions are ambiguous. This paper uses new panel data on buyer-supplier transfers and a structural model to empirically analyze bargaining and price discrimination in a medical device market. While many phenomena that restrict different prices to different buyers are suggested as ways to decrease hospital costs (e.g., mergers, group purchasing organizations, and transparency), I find that: (i) more uniform pricing works against hospitals by softening competition; and (ii) results depend ultimately on a previously unexplored bargaining effect. (JEL C78, L13, L14, L64)
“…Our models are unique in this. The value is assessed purely in terms of financial data, rather than the value of the company for consumers wider Grennan, 2014), nor does it attempt to quantify the value for other entities, which we can call such as stakeholders (Charreaux, Desbrières, 2001).…”
Purpose of the article: The subject of this article is the construction of a model which is able to measure whether an enterprise is creating or destroying value. In the light of our previous research, we are not seeking to create a universal model, instead we want to create a set of special models that consider the specificities of different sectors. Therefore, we have created three models especially for the food industry, engineering and transportation. Methodology/methods: We used the financial analysis, portfolio analysis and logistic regression. Scientific aim: The aim of the article is to construct value-measuring models in various sectors of the manufacturing industry. We start from the premise that it is very difficult to construct a universal model that is able to measure the value in different sectors equally well. Therefore, using the example of three manufacturing industries (namely the food industry, engineering and transportation), we constructed three models and then compared and discussed the differences observed.
Findings:The results confirmed that there are significant differences between the models of value creation within the three sectors which we studied. The main difference in each sector is its capital structure. For each model, we selected a different number of indicators using statistical methods to create the optimal model. Conclusions: The first research limitation is that the focus is only on three sectors. As part of further research, it will be necessary to construct different models in other sectors as well. The second limitation of the research is that it focuses purely on finance, which does not allow many options to identify and discuss the internal and qualitative differences of the enterprises and sectors under examination, which could contribute to increasing the accuracy of the model. The model is constructed from publicly available data, which is both a limitation and an advantage.
“…Their study shows that power structure makes impact on the efficiency of the supply chain and the impact is dependent on both expected demand and demand shock. Grennan [23] empirically analyzed the relationship between power dynamics, more specifically, firms' bargaining ability and competitive advantage in the context of hospitals and medical device supplier. His findings indicate that the variation in purchasing prices of the same device is mainly due to the difference in bargaining ability.…”
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