Relationship Value in The Hardwood Lumber Industry. in U.S.

Transcription

1 Relationship Value in The Hardwood Lumber Industry in U.S. Sudipta Dasmohapatra Ronalds Gonzalez Forest Products Society Conference June nd, 2010

2 Introduction Commodity markets: Markets typified by the homogeneity of products and the virtual irrelevance of branding 1. Branding Price sensitive Hardwood Lumber = + What attributes can help Suppliers get higher customer share? 1

3 Product Service/ Promotion Relationship Price Past value literature indicate importance of relationships Placement

4 Purpose of this study Determine the role of relationships vis-à-vis other attributes in buyer-seller transactions or purchase decisions in the hardwood lumber industry; Provide insights about how buyers of hardwood lumber choose among suppliers; Examine the product, service and supplier dimensions that contribute to a higher customer perceived overall value in relationships, and higher customer satisfaction in the hardwood lumber industry. 4

5 Research methodology Determination of goals and objectives of the research Literature review Determination of sampletarget characteristics Research source for contact list Filtering contact list Survey design Data collection Analysis 5

6 Response rate Description Number Population 1,058 Filtered contacts* (347) Initial contact list 711 Returned ** (169) Adjusted populations 542 Completed responses 78 Response rate 14.4% * Sawmills and those located outside of U.S. ** errors, closed business, contacts no longer available 6

7 Respondent distribution by region in U.S. (n=78) MW =26% NE =14.3% W =5.2% S =54.5% 7

8 Percent of respondents by primary line of business (n=78) *Others include: Dimension stocks, stair parts, musical instruments and specialty wood working. 8

9 Respondent characteristics (n=78) Respondent characteristics Mean Standard Dev Range (Min-Max) No. of employees (1-5,500) Volume of HW lumber purchased in mmbf 25.8 mmbf (100,000 bf 200 mmbf) Oak accounted for 35% of species purchased, 19% maple, 15% yellow poplar, 9% black cherry, 5% ash, 17% other (hickory, walnut, beech, etc.) 9

10 Volume of hardwood lumber by top two suppliers for n=78 lumber buyers Paired Differences Mean Volume of purchase %** t Significance p-value* Supplier % (20% std dev) Supplier % (11% std dev) *Test of significance using paired sample t-test between supplier 1 and 2 at 0.05 significance level. **All other suppliers 46.7%` 10

11 Attributes driving hardwood lumber purchase decision Attributes Mean* Standard deviation Product quality Relationship with supplier Overall service Price On-time delivery Geographic closeness Availability range grades Availability range sizes Availability range species Volume discount Warranty on product Packaging Environmental certification Brand *Note: 7 point importance scale where 1 = not at all important and 7 = most important. 11

12 Years of relationship with top two suppliers for (n=78) buyers Mean length of relationship with buyer (years) t Significance p-value* Supplier (8.8 std dev) Supplier (8.5 std. dev) *Test of significance using paired sample t-test between supplier 1 and 2 at 0.05 significance level. 12

13 Buyer satisfaction and future share for top two suppliers (n=78) Mean rating** Attributes Supplier 1 Supplier 2 t p-value* Overall satisfaction Supplier will receive larger share We expect to expand our business with this supplier This supplier will be used more than it is now *Test of significance using paired sample t-test between supplier 1 and 2 at 0.05 significance level. **Note: 7 point agreement scale where 1 = strongly disagree and 7 = strongly agree. 13

14 Relationship dimensions between buyers and their top two suppliers (n=78) Mean Attributes Supplier 1 Supplier 2 t Significance p-value* Readily adjusts their inventories to meet your needs It would be disruptive to your company s operations to end the business relationship with this partner The switching costs to another partner for this product would be large You focus on long-term goals in this relationship You are willing to invest time and other resources into the relationship with this supplier You share costs with this supplier on common activities (such as distribution, promotion, handling, others) *Test of significance using paired sample t-test between supplier 1 and 2 at 0.05 significance level. **Note: 7 point agreement scale where 1 = strongly disagree and 7 = strongly agree 14

15 First (top) supplier compared to supplier 2 (Quality, service and supplier attribute, n=78) Supplier 1 compared to Supplier 2 Mean Std Provides you more consistent product quality over time Products are more reliable You reject less products from the main supplier Provides you with better quality Gives you a greater feeling of being treated as an important customer It is easier to work with the main supplier Responds faster when you need information There is a better interaction between the main supplier s people and ours Performs better in meeting delivery due dates *Note: 7 point agreement scale where 1 = strongly disagree and 7 = strongly agree 15

16 Quality, service and supplier attributes rating of main (best) supplier compared to supplier 2 (continuation) Supplier 1 compared to Supplier 2 Mean Std You have less delivery errors with the main supplier Provides you with better services You can address problems more easily with the main supplier Provides you with better access to his know how Helps you in getting your products to market faster Knows better how to improve your existing products Performs better at presenting you with new products Performs better in helping you speed up product development Knows better how to assist you in new product development *Note: 7 point agreement scale where 1 = strongly disagree and 7 = strongly agree 16

17 Factors analysis* of attributes Attributes Interaction w/supplier Factor 1 Supplier know-how Factor 2 Product quality Factor 3 Supplier performance Factor 4 There is a better interaction between the main supplier s people and ours You can address problems more easily with the main supplier It is easier to work with the main supplier Gives you a greater feeling of being treated as an important customer Performs better in helping you speed up product development Knows better how to assist you in new product development Performs better at presenting you with new products Helps you in getting your products to market faster Knows better how to improve your existing products Reliability (Cronbach 's Alpha) *Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. 17

18 Factors analysis* of attributes (continued ) Interaction Supplier Product Supplier Reliability Attributes w/supplier know-how quality performance (Cronbach' Factor 1 Factor 2 Factor 3 Factor 4 s Alpha) You reject less products from the main supplier Products are more reliable Provides you with better quality Provides you more consistent product quality over time You have less delivery errors with the main supplier Performs better in meeting delivery due dates Provides you with better services Responds faster when you need information *Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. 18

19 Overall relationship value of first supplier versus second supplier (n=78) Attributes Mean rating* Standard deviation Offers higher value when comparing all benefits and costs of this relationship Adds more value to the relationship, overall *Note: 7 point agreement scale where 1 = strongly disagree and 7 = strongly agree 19

20 Regression model (Prediction of relationship value using factors (Linear Regression-ANOVA)) Model Sum of Squares df Mean square F p-value* Regression a Residual Total *Test of significance at 0.05 significance level. Predictors: (Constant), Regression factor score for: personal interaction with supplier, product quality, supplier know-how and delivery performance/service support. Dependent variable: overall relationship value 20

21 Regression coefficients and significance for the regression model. Model B Standard Error t Significance p-value* Constant Personal Interaction w/supplier Supplier Know-how Product Quality Delivery Performance/Service *Test of significance at 0.05 significance level. 21

22 Relationship value model (Hardwood lumber industry) Note: Relationship value = (Supplier know-how) (Personal interaction with supplier) (Delivery performance/service support) ( Product quality). 22

23 Conclusions 23

24 The top two suppliers for hardwood lumber buyer represent about half of their purchase transactions Supplier 1 is 1/3 rd so strive to be the first supplier. The top supplier (in terms of volume) is perceived as better than the second supplier on delivery of product quality, service, relationship value, customer s satisfaction and other supplier performance attributes. 24

25 Purchase decisions of hardwood lumber buyers are very sensitive to product quality, relationship with buyer-supplier, overall service and price (presented in order of importance). 25

26 The value of relationship in the hardwood lumber industry can be explained through four main dimensions (as determined in this study) of supplier know-how, personal interaction with supplier, product quality and delivery performance/service support Suppliers engaging in attributes related to Supplier know-how factors will result in a higher perceived relationship value from hardwood lumber buyers 26

27 Thank you for your attention

28 Buyer sensitiveness to price change 28

29 Limitations Sample size from the National Hardwood Lumber Association (NHLA) The lack of sufficient responses from a single industry. Only one respondent from each company was contacted for survey, which may have created a single respondent bias 29

30 Recommendations Future studies should include commitment and trust variables in addition to satisfaction Future researches may consider attribute supplier comparison between main suppliers (first two) against the other set of suppliers 30

31 Recommendations Future research could re-test the attributes with a wider sample size so that differences between different businesses categories can be noted (e.g. furniture vs. cabinets vs. flooring). 31

32 Acknowledgements Dr. Sudipta Dasmohapatra Dr. Michael Kocurek Dr. Daniel Saloni Dr. Robert Handfield Wood and Paper Science Department 32