Energy Efficiency in Small and Medium-Sized Manufacturing Firms: Order Effects and the Adoption of Process Improvement Recommendations

Published Online:https://doi.org/10.1287/msom.2013.0439

References

  • 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.CrossrefGoogle Scholar
  • Allcott H, Mullainathan S (2010) Behavior and energy policy. Science 327(5970):1204–1205.CrossrefGoogle Scholar
  • Anderson NH (1971) Integration theory and attitude change. Psych. Rev. 78(3):171–206.CrossrefGoogle Scholar
  • Anderson ST, Newell RG (2004) Information programs for technology adoption: The case of energy-efficiency audits. Resource Energy Econom. 26(1):27–50.CrossrefGoogle Scholar
  • Benartzi S, Thaler RH (2007) Heuristics and biases in retirement savings behavior. J. Econom. Perspect. 21(3):81–104.CrossrefGoogle Scholar
  • 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.Google Scholar
  • Bierman H Jr, Smidt S (2007) The Capital Budgeting Decision (Macmillan, New York).Google Scholar
  • 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.Google Scholar
  • Cachon GP, Olivares M (2010) Drivers of finished-goods inventory in the U.S. automobile industry. Management Sci. 56(1):202–216.LinkGoogle Scholar
  • Carney DR, Banaji MR (2012) First is best. PLoS ONE 7(6):e35088.CrossrefGoogle Scholar
  • Charles D (2009) Leaping the efficiency gap. Science 325(5942):804–811.CrossrefGoogle Scholar
  • 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.CrossrefGoogle Scholar
  • Chernev A (2003b) Product assortment and individual decision processes. J. Personality Soc. Psych. 85(1):151–162.CrossrefGoogle Scholar
  • DeCanio SJ (1998) The efficiency paradox: Bureaucratic and organizational barriers to profitable energy-saving investments. Energy Policy 26(5):441–454.CrossrefGoogle Scholar
  • Deshpande V, Cohen M, Donohue K (2003) An empirical study of service differentiation for weapon system service parts. Oper. Res. 51(4):518–530.LinkGoogle Scholar
  • 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.CrossrefGoogle Scholar
  • 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.CrossrefGoogle Scholar
  • Evans WN, Schwab RM (1995) Finishing high school and starting college: Do Catholic schools make a difference? Quart. J. Econom. 110(4):941–974.CrossrefGoogle Scholar
  • 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.Google Scholar
  • 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.Google Scholar
  • Gino F, Pisano G (2008) Toward a theory of behavioral operations. Manufacturing Service Oper. Management 10(4):676–691.LinkGoogle Scholar
  • Gourville JT, Soman D (2005) Overchoice and assortment type: When and why variety backfires. Marketing Sci. 24(3):382–395.LinkGoogle Scholar
  • Greene WH (2008) Econometric Analysis, 6th ed. (Prentice Hall, Upper Saddle River, NJ).Google Scholar
  • Hassett KA, Metcalf GE (1995) Energy tax credit and residential conservation investment: Evidence from panel data. J. Public Econom. 57(2):201–217.CrossrefGoogle Scholar
  • 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.CrossrefGoogle Scholar
  • Jaffe AB, Stavins RN (1994a) The energy-efficiency gap: What does it mean? Energy Policy 22(10):804–810.CrossrefGoogle Scholar
  • Jaffe AB, Stavins RN (1994b) The energy paradox and the diffusion of conservation technology. Resource Energy Econom. 16(2):91–122.CrossrefGoogle Scholar
  • 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.CrossrefGoogle Scholar
  • 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.CrossrefGoogle Scholar
  • Kleindorfer PR, Singhal K, Van Wassenhove LN (2005) Sustainable operations management. Production Oper. Management 14(4):482–492.CrossrefGoogle Scholar
  • Landis JR, Koch GG (1977) The measurement of observer agreement of categorical data. Biometrics 33:159–174.CrossrefGoogle Scholar
  • 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.CrossrefGoogle Scholar
  • Maddala GS (2003) Limited Dependent and Qualitative Variables in Econometrics (Cambridge University Press, Cambridge, UK), 22–27.Google Scholar
  • Mantonakis A, Rodero P, Lesschaeve I, Hastie R (2009) Order in choice: Effects of serial position on preferences. Psych. Sci. 20(11):1309–1312.CrossrefGoogle Scholar
  • 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.Google Scholar
  • 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.CrossrefGoogle Scholar
  • 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.CrossrefGoogle Scholar
  • 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.Google Scholar
  • Murray MP (2006) Avoiding invalid instruments and coping with weak instruments. J. Econom. Perspect. 20(4):111–132.CrossrefGoogle Scholar
  • 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.LinkGoogle Scholar
  • Philips (2011) Supplier sustainability involvement program. Accessed January 12, 2013, http://www.philips.com/about/sustainability/oursustainabilityfocus/suppliersustainability.page.Google Scholar
  • Stern PC, Aronson E (1984) Energy Use: The Human Dimension (W. H. Freeman & Co., New York).Google Scholar
  • Tversky A, Sattath S, Slovic P (1988) Contingent weighting in judgment and choice. Psych. Rev. 95(3):371–384.CrossrefGoogle Scholar
  • 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/Volume 3.pdf.Google Scholar
  • 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.Google Scholar
  • 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.Google Scholar
  • 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.Google Scholar
  • Wooldridge JM (2002) Econometric Analysis of Cross Section and Panel Data (MIT Press, Cambridge, MA), 83–113.Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.