Energy efficiency in small and medium-sized manufacturing firms: Order effects and the adoption of process improvement recommendations

Manufacturing and Service Operations Management

Volumn 15, Issue 4, 2013, Pages 596-615

  Muthulingam, Suresh ^a   Corbett, Charles J ^b   Benartzi, Shlomo ^b   Oppenheim, Bohdan ^c  

^a The Samuel Curtis Johnson Graduate School of Management   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c LOYOLA MARYMOUNT UNIVERSITY   (United States)

Author keywords

Behavioral operations; Econometric analysis; Empirical research; Energy efficiency; Energy related operations; Environmental operations; Order effects; Process improvement

Indexed keywords

BEHAVIORAL OPERATIONS; ECONOMETRIC ANALYSIS; EMPIRICAL RESEARCH; ENERGY-RELATED OPERATIONS; ENVIRONMENTAL OPERATIONS; ORDERING EFFECTS; PROCESS IMPROVEMENT;

INDUSTRY; INVESTMENTS; MANUFACTURE;

ENERGY EFFICIENCY;

EID: 84886021990     PISSN: 15234614     EISSN: 15265498     Source Type: Journal    
DOI: 10.1287/msom.2013.0439     Document Type: Article

References (48)

1. Aflaki S, Kleindorfer PR, de Miera Polvorinos VS (2012) Finding and implementing energy efficiency projects in industrial facilities. Production Oper. Management 22(3):503-517.
2. Allcott H, Mullainathan S (2010) Behavior and energy policy. Science 327(5970):1204-1205.
3. Anderson NH (1971) Integration theory and attitude change. Psych. Rev. 78(3):171-206.
4. Anderson ST, Newell RG (2004) Information programs for technology adoption: The case of energy-efficiency audits. Resource Energy Econom. 26(1):27-50. (Pubitemid 38256932)
5. Benartzi S, Thaler RH (2007) Heuristics and biases in retirement savings behavior. J. Econom. Perspect. 21(3):81-104.
6. Bernstein L, Roy J, Delhotal KC, Harnisch J, Matsuhashi R, Price L, Tanaka K, Worrell E, Yamba F, Fengqi Z (2007) Contribution of Working Group III to the fourth assessment report of the Intergovernmental Panel on Climate Change. Metz B, Davidson OR, Bosch PR, Dave R, Meyer LA, eds. Climate Change 2007: Mitigation of Climate Change (Cambridge University Press, Cambridge, UK), 456-460, 475-477.
7. Bierman H Jr, Smidt S (2007) The Capital Budgeting Decision (Macmillan, New York).
8. Bureau of Labor Statistics (2008) Producer price index highlights- Finished goods (WPUSOP3000). Back data. Accessed June 2, 2010, http://www.bls.gov/xg-shells/ro4xgppihi.htm.
9. Cachon GP, Olivares M (2010) Drivers of finished-goods inventory in the U.S. automobile industry. Management Sci. 56(1):202-216.
10. Carney DR, Banaji MR (2012) First is best. PLoS ONE 7(6):e35088.
11. Charles D (2009) Leaping the efficiency gap. Science 325(5942): 804-811.
12. Chernev A (2003a) When more is less and less is more: The role of ideal point availability and assortment in consumer choice. J. Consumer Res. 30(2):170-183. (Pubitemid 37374303)
13. Chernev A (2003b) Product assortment and individual decision processes. J. Personality Soc. Psych. 85(1):151-162. (Pubitemid 37189370)
14. DeCanio SJ (1998) The efficiency paradox: Bureaucratic and organizational barriers to profitable energy-saving investments. Energy Policy 26(5):441-454. (Pubitemid 28358988)
15. Deshpande V, Cohen M, Donohue K (2003) An empirical study of service differentiation for weapon system service parts. Oper. Res. 51(4):518-530.
16. De Reyck B, Grushka-Cockayne Y, Lockett M, Calderini SR, Moura M, Slopper A (2005) The impact of project portfolio management on information technology projects. Internat. J. Project Management 23(7):424-537.
17. Dierderen P, Tongeren FV, Der Veen HV (2003) Returns on investments in energy-saving technologies under energy price uncertainty in Dutch greenhouse horticulture. Environ. Resource Econom. 24(4):379-394.
18. Evans WN, Schwab RM (1995) Finishing high school and starting college: Do Catholic schools make a difference? Quart. J. Econom. 110(4):941-974.
19. Expert Group on Energy Efficiency (2007) Realizing the potential of energy efficiency: Targets, policies, and measures for G8 countries. Expert report, United Nations Foundation, Washington, DC, 9-19.
20. Fair Labor Association (2012) Sustainable management of Nestlé's cocoa supply chain in the Ivory Coast-Focus on labor standards. Accessed December 14, 2012, http://www.fairlabor.org/sites/default/files/documents/ reports/cocoa-report-final-0.pdf.
21. Gino F, Pisano G (2008) Toward a theory of behavioral operations. Manufacturing Service Oper. Management 10(4):676-691.
22. Gourville JT, Soman D (2005) Overchoice and assortment type: When and why variety backfires. Marketing Sci. 24(3):382-395. (Pubitemid 41409332)
23. Greene WH (2008) Econometric Analysis, 6th ed. (Prentice Hall, Upper Saddle River, NJ).
24. Hassett KA, Metcalf GE (1995) Energy tax credit and residential conservation investment: Evidence from panel data. J. Public Econom. 57(2):201-217.
25. Iyengar SS, Lepper MR (2000) When choice is demotivating: Can one desire too much of a good thing? J. Personality Soc. Psych. 79(6):995-1006.
26. Jaffe AB, Stavins RN (1994a) The energy-efficiency gap: What does it mean? Energy Policy 22(10):804-810.
27. Jaffe AB, Stavins RN (1994b) The energy paradox and the diffusion of conservation technology. Resource Energy Econom. 16(2):91-122.
28. Jaffe AB, Stavins RN (1995) Dynamic incentives of environmental regulations: The effect of alternative policy instruments on technology diffusion. J. Environ. Econom. Management 29(3):S43-S63. (Pubitemid 3006264)
29. Keizers JM, Bertrand JWM, Wessels J (2003) Diagnosing order planning performance at a navy maintenance and repair organization using logistic regression. Production Oper. Management 12(4):445-464.
30. Kleindorfer PR, Singhal K, Van Wassenhove LN (2005) Sustainable operations management. Production Oper. Management 14(4):482-492. (Pubitemid 43625027)
31. Landis JR, Koch GG (1977) The measurement of observer agreement of categorical data. Biometrics 33:159-174. (Pubitemid 8054849)
32. Li Y, Epley N (2009) When the best appears to be saved for last: Serial position effects on choice. J. Behavioral Decision Making 22(4):378-389.
33. Maddala GS (2003) Limited Dependent and Qualitative Variables in Econometrics (Cambridge University Press, Cambridge, UK), 22-27.
34. Mantonakis A, Rodero P, Lesschaeve I, Hastie R (2009) Order in choice: Effects of serial position on preferences. Psych. Sci. 20(11):1309-1312.
35. Martin M, Tonn B, Schmoyer R, Overly J, Schexnayder S, Johnson D (1999) Industrial Assessment Center program impact evaluation. ORNL/CON-473. Oak Ridge National Laboratory, Oak Ridge, TN.
36. Mueller S (2006) Missing the spark: An investigation into the low adoption paradox of combined heat and power technologies. Energy Policy 34(17):3153-3164. (Pubitemid 44204086)
37. Mulder P, de Groot HLF, Hofkes MW (2003) Explaining slow diffusion of energy-saving technologies; A vintage model with returns to diversity and learning by-using. Resource Energy Econom. 25(1):105-126. (Pubitemid 36186289)
38. Muller MR, Muller MB, Glaeser FW (2004) The DOE Industrial Assessment Database Manual: User Information Version 8.2. Accessed June 3, 2010, http://iac.rutgers.edu/manual-database.php.
39. Murray MP (2006) Avoiding invalid instruments and coping with weak instruments. J. Econom. Perspect. 20(4):111-132.
40. Olivares M, Cachon GP (2009) Competing retailers and inventory: An empirical investigation of General Motors' dealerships in isolated U.S. markets. Management Sci. 55(9):1586-1604.
41. Philips (2011) Supplier sustainability involvement program. Accessed January 12, 2013, http://www.philips.com/about/sustainability/ oursustainabilityfocus/suppliersustainability.page.
42. Stern PC, Aronson E (1984) Energy Use: The Human Dimension (W. H. Freeman & Co., New York).
43. Tversky A, Sattath S, Slovic P (1988) Contingent weighting in judgment and choice. Psych. Rev. 95(3):371-384.
44. U.S. Department of Energy (2011) Department of Energy FY 2011 Congressional budget request. Accessed June 17, 2011, http://www.cfo.doe.gov/ budget/11budget/Content/Volume3.pdf.
45. U.S. Department of Energy Industrial Technologies Program (2004). Energy use, loss, and opportunities analysis, U.S. manufacturing and mining. Accessed September 18, 2012, http://www1.eere.energy.gov/manufacturing/ intensiveprocesses/pdfs/energy-use-loss-opportunities-analysis.pdf.
46. U.S. Department of Energy Industrial Technologies Program (2009) Impacts-Method of calculating results for the IAC program. Accessed January 12, 2012, http://www1.eere.energy.gov/industry/about/pdfs/impacts2007-appendix4.pdf.
47. U.S. Energy Information Administration (2012) Annual energy outlook, early release overview. Accessed October 9, 2012, http://www.eia.gov/forecasts/ aeo/er/pdf/0383er%282012%29.pdf.
48. Wooldridge JM (2002) Econometric Analysis of Cross Section and Panel Data (MIT Press, Cambridge, MA), 83-113.