ENVIRONMENTAL COMMUNICATIONS WITH LCA INFORMATION: AN EXPLORATORY - PowerPoint PPT Presentation

ENVIRONMENTAL COMMUNICATIONS WITH LCA INFORMATION: AN EXPLORATORY STUDY WITHIN THE BUILDING INDUSTRY Sergio A. Molina –Murillo Timothy M. Smith Post ‐ Doctoral Associate/Instructor Associate Professor Strategic Environmental Management & Policy Environmental Science, Policy & Management University of Minnesota ‐ Twin Cities University of Minnesota ‐ Twin Cities 3 rd International Conference on Life Cycle Management Zurich, Switzerland August 27-29, 2007

Environmental Messages are difficult to communicate • Environmental issues are themselves complex and require significant disclosures in light of many information asymmetries. • The legitimacy of multiple stakeholders, each one providing often conflicting expert information to an already crowed media marketplace. • Consumers and buyers function within a skeptical ‐ mode when exposed to environmental messages.

Our Footprint Label

British supermarket chain Tesco, would spend almost $1 billion over the next five years to lead "a revolution in green consumption” (New York Times, March 6 th , 2007). “ To create a mass movement in green consumption we must provide better information” ( Sir Terry Leahy, Tesco CEO 01/18/2007)

Environmentally Preferable Products • The end-consumer market size of sustainable products is over $200 billion in the U.S. (LOHAS 2005) • The U.S. Federal Government procures $200 billion annually and several executives’ orders encourage to give preference to “green” products. • Wal ‐ Mart’s recent announcement to aggressively encourage its 60,000 suppliers to create products that don't harm the environment (Hudson 2007).

Product: bundle of benefits Environmental communications are often considered in isolation and not Environmental communications are often considered in isolation and not in conjunction with functional product attributes/benefits. in conjunction with functional product attributes/benefits. Functional benefits: “ ingredients necessary for performing the product function as viewed by consumers ” (Keller 1993)

Research Question Does environmental information (non-functional) complement or impair functional product performance information?

Information processing & persuasion • Dual ‐ Process Models of Persuasion: (Petty and Cacciopo 1981,1984; Petty, Cacciopo and Schumman 1983; Chaiken 1980, 1994). 2 Routes of Persuasion • Central route: people examine most of the information presented to uncover the reasons in support of the proposal. • Peripheral route provides a quick accept or reject decision without deep consideration of the information content.

Conceptual Model

Methods Architects � Insulation Sample and product: Web ‐ based survey, architects randomly assigned to a single ad. • Dependent Variables: AAd, ABrand, ACompany, Purchase Intention, Credibility, Complexity • Independent Variables: Type of message (Functional/ Non ‐ functional) Explicit claim (Yes/No); Private disclosure (FUN, FIN, HEA) • Control Variables : Gender, Familiarity with product category, Environmental Concern, Ad message Involvement, Attitude towards Advertising, Familiarity with Energy Star program, Years of professional experience. • 8 Different Ads • Response rate= 21.5% (1,346); median = 10 minutes. • Included in analysis responses between 5 ‐ 20 minutes only respondents with English as the first language = 1,062). • No response bias.

Measurement Scales No. of References Construct Items Complexity (COM) 3 Keller and Block (1997). Cottle et al. (2005); Newell and Goldsmith Credibility (CRE) 3 (2001), Golberg and Hartwick (1990). MacKenzie and Lutz (1989); Muehling Attitude toward the ad (AAD) 3 (1987a). Attitude toward the brand (ABR) 3 MacKenzie and Lutz (1989); Muehling (1987a) Attitudes toward the company (ACO) 8 Newell and Goldsmith (2001). Yi (1990); Putrevu et al. (2004); MacKenzie, Purchase intention (PI) 3 Lutz and Belch (1986). Product knowledge (KNO) 3 Kent and Allen (1994). Energy Star’ familiarity (STA) 3 Oliver and DeSarbo (1985) Environmental concern (EC) 5 Cordano et al. (2003); Cordano et al. (2004) Attention devoted to the message (ATT) 4 Ha (1996); Laczniak and Muehling (1993). Obermiller and Spangenberg (1998); Attitudes toward advertising (ADV) 9 Muehling (1987b) • Reliability (Cronbach α ): .852 (CRE) ‐ .945 (ABR).

Functional Non-functional (Environmental) No Explicit Explicit

Regression results of all dependent variables. COM CRE AAD ABR ACO PI INDEPENDENT VARIABLES 4.082* 3.869* 3.358* 2.091* 2.077* -0.471* Intercept term (TDF) a Functional Disaggregated (TDFD) 0.214 -0.022 0.018 -0.084 0.057 0.125 Environmental Non-Disaggregated (TDE) 0.201 -0.206* -0.024 -0.035 -0.079 0.172* Environmental Disaggregated (TDED) 0.078 0.244* 0.239* -0.039 0.046 0.115* FIN 0.171 -0.034 0.068 -0.028 -0.014 0.010 HEALTH 0.20** 0.026 -0.035 0.033 0.096* -0.112** -0.321* -0.035 -0.004 -0.078* Complexity (COM) 0.349* 0.149* 0.320* 0.256* Credibility (CRE) Attitude toward the ad (AAD 0.356* 0.121* 0.168* 0.186* Attitude toward the brand (ABR) 0.348* Attitude toward company (ACO) CONTROL VARIABLES 0.099 -0.004 -0.080 -0.054 0.019 -0.072 Gender (GEN) 0.002 -0.077* 0.029 -0.049 -0.037* 0.051** Product Knowledge (KNO) 0.060 0.037 -0.017 0.065 0.039** 0.024 Energy Star Familiarity (STA) 0.071** 0.019 0.001 -0.054 0.013 0.062* Environmental Concern (EC) -0.320* -0.004 0.113* 0.005 -0.048* 0.014 Processing effort (ATT) 0.007 -0.014* -0.009* -0.004 -0.005* -0.008* Professional Experience (EXP) -0.100* 0.319* 0.099* 0.078* 0.073* 0.061* Attitude toward Advertising (ADV) 0.095 0.154 0.362 0.282 0.450 0.546 Adj. R 2 a The base line advertisement includes a Functional Non-Explicit theme disclosure (TDF) with a Functional Private Disclosure (FUN). * Significant (p ≤ 0.05)  ** Significant (p ≤ 0.10)

Structural Equations Model Gender Gender GEN1 GEN1 ξ 1 ξ 1 KNO1 KNO1 COM1 COM1 COM2 COM2 COM3 COM3 KNO2 KNO2 Knowledge Knowledge ξ 2 ξ 2 KNO3 KNO3 CO1 CO1 CO2 CO2 KNO4 KNO4 STA1 STA1 Energy Star Energy Star STA2 STA2 Complexity Complexity γ 1 1−14 γ 1 1−14 ξ 3 ξ 3 η 1 η 1 STA3 STA3 Β 51 =0.03 Β 51 =0.03 EC1 EC1 EC2 EC2 Β 61 = −0.08∗ Β 61 = −0.08∗ A. Company A. Company EC EC EC3 EC3 η 5 η 5 ξ 4 ξ 4 ε 1 ε 1 AAD1 AAD2 AAD3 AAD1 AAD2 AAD3 EC4 EC4 EC5 EC5 Β 31 = −0.47∗ Β 31 = −0.47∗ ATT1 ATT1 ε 5 ε 5 ATT2 ATT2 Β 53 = 0.17∗ Β 53 = 0.17∗ Β 65 =0.33∗ Β 65 =0.33∗ ATT ATT ξ 5 ξ 5 ATT3 ATT3 ATT4 ATT4 EXP EXP PI1 PI1 EXP1 EXP1 ζ 21 ζ 21 ζ 54 ζ 54 ξ 6 ξ 6 A. Ad A. Ad PI PI γ 2 1−14 γ 2 1−14 Β 63 = 0.28∗ Β 63 = 0.28∗ AAD1 AAD1 PI2 PI2 η 3 η 3 η 6 η 6 A. Advertising A. Advertising AAD2 AAD2 ξ 7 ξ 7 PI3 PI3 AAD3 AAD3 Β 41 = −0.02 Β 41 = −0.02 Β 64 =0.15∗ Β 64 =0.15∗ TDF TDF TDF1 TDF1 Β 43 = 0.42∗ Β 43 = 0.42∗ ε 4 ε 4 ξ 8 ξ 8 Β 52 = 0.72∗ Β 52 = 0.72∗ Β 32 = 0.30∗ Β 32 = 0.30∗ TDFD TDFD TDFD1 TDFD1 ξ 9 ξ 9 A. Brand A. Brand η 4 η 4 ε 2 ε 2 Β 62 = 0.18∗ Β 62 = 0.18∗ TDE TDE Β 42 = 0.18∗ Β 42 = 0.18∗ TDE1 TDE1 ξ 10 ξ 10 TDED TDED Credibility Credibility TDED1 TDED1 γ 3 1−14 γ 3 1−14 ξ 11 ξ 11 η 2 η 2 FUN FUN FUN1 FUN1 ξ 12 ξ 12 ABR1 ABR2 ABR3 ABR1 ABR2 ABR3 FIN FIN FIN1 FIN1 ξ 13 ξ 13 CRE1 CRE1 CRE2 CRE2 CRE3 CRE3 CRE4 CRE4 HEA HEA HEA1 HEA1 ξ 14 ξ 14 •915 observations with a total of 45 observed variables specified for 20 latent variables

LVSEM standardized coefficients of exogenous variables. Specified relationship Parameter Estimate t Value γ 18 TDF � Complexity -0.02 -0.03 γ 28 TDF � Credibility 0.05 0.07 γ 38 TDF � AAD -0.01 -0.01 γ 19 TDFD � Complexity 0.03 0.86 γ 29 TDFD � Credibility 0.01 0.07 γ 39 TDFD � AAD -0.01 -0.05 γ 110 TDE � Complexity 0.02 0.03 γ 210 TDE � Credibility -0.05 -0.07 γ 310 TDE � AAD 0.01 0.01 γ 111 TDED � Complexity -0.02 -0.50 γ 211 TDED � Credibility 0.14 4.11 γ 311 TDED � AAD 0.08 2.74 χ 2 (806) = 1,564.61 (p=0.001) Root Mean Square Error of Approximation (RMSEA) = 0.031 Normed Fit Index (NFI) = 0.97 Incremental Fit Index (IFI) = 0.99

Estimated Structural Model standardized coefficients (cont.) Specified relationship Parameter Estimate t Value Complexity � AAD Β 31 -0.47 -14.48 Complexity � ABR Β 41 -0.02 -0.63 Complexity � ACO 0.03 0.87 Β 51 Complexity � PI Β 61 -0.08 -2.54 Credibility � AAD β 32 0.30 8.88 Credibility � ABR β 42 0.18 5.01 Credibility � ACO β 52 0.72 15.16 Credibility � PI 0.18 3.47 β 62 AAD � ABR β 43 0.42 9.25 AAD � ACO β 53 0.17 4.18 AAD � PI β 63 0.28 7.09 ABR � PI β 64 0.15 5.08 ACO � PI 0.33 5.59 β 65 χ 2 (806) = 1,564.61 (p=0.001) Root Mean Square Error of Approximation (RMSEA) = 0.031 Normed Fit Index (NFI) = 0.97 Incremental Fit Index (IFI) = 0.99