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Are ‘Green Brides’ More Attractive? An Empirical Examination of How Prospective Partners’ Environmental Reputation Affects the Trust-Based Mechanism in Alliance Formation

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Abstract

There is theoretical and empirical evidence that firms’ environmental performance has ramifications for their appeal to various stakeholders. Yet, we know little about how this plays out in the context of strategic alliance formation. Stated differently, research is lacking on how ‘green’ prospective alliance partners are estimated by the initiating firm. This article employs strong environmental reputation as a proxy for high environmental performance and explores implications for the well-established alliance formation trust-based mechanism, under the strategic cognition perspective. The ensuing hypotheses are subjected to empirical scrutiny through an experimental method. A random sample of 138 CEOs and top managers of Norwegian manufacturing firms completed a scenario-based questionnaire. The results show that two out of three trust dimensions are affected and, moreover, that two out of three—but not the same—trust dimensions influence partner attractiveness. Several theoretical and managerial implications, and future research opportunities, are derived from the findings.

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Notes

  1. Mayer et al. (1995) conceptualize perceived trustworthiness based on a review of the dimensions identified by other researchers. Their paper has been cited by almost 9,400 (Source Google Scholar). Schoorman et al. (2007), revisiting the paper, is cited by over 900. There is acceptance and deployment of their conceptualization in the strategic alliance literature (Becerra et al. 2008).

  2. Defined as “firms’ effectiveness in meeting and exceeding societal expectations with respect to concerns about the natural environment” (Chan 2005, p. 632). “It is about the firm’s proactive stance concerning future environmental considerations, and extends beyond mere compliance with existing regulations” (Ibid.).

  3. This article does not consider conditional trust as an antecedent to perceived trustworthiness (Daellenbach and Davenport 2004); justified in this quote: “How does an initial assessment arise when neither prior experience nor reputation provide suitable knowledge? In such cases, Jones and George (1998) suggest that the potential partners may initially suspend beliefs [emphasis added] about the others’ actual trustworthiness and assume that the other firm can be conditionally trusted” (Daellenbach and Davenport 2004, p. 193). Factors identified in negotiations or the implementation of an alliance (Ibid.; Nielsen 2011) are equally excluded.

  4. Key partner selection criteria have been identified in prior studies (Shah and Swaminathan 2008), and do not include environmental reputation. Thus, this article assumes that environmental reputation is only attributed a ‘starring role’ in environmental collaborations (Wassmer et al. 2012). However, partner selection is a complex decision, and many factors influence partner attractiveness. Identifying secondary factors—especially those affecting key selection criteria (e.g., trust)—contributes to a more fine-grained understanding.

  5. This article contrasts strong environmental reputation with a neutral (not negative) reputation. Firms failing to comply with environmental regulations will likely be eliminated in the due diligence process (Mitsuhashi 2002).

  6. Source http://sloanreview.mit.edu/reports/sustainability-innovation/introduction/.

  7. The complete measurement instrument was translated into Norwegian by the author and back-translated into English by a certified translator.

  8. Due to space constraints, the full instrument cannot be included in Appendix. Further information can be requested from the author.

  9. The list was obtained from Proff Forvalt; a company which delivers paid information services and cooperates with organizations such as the Norwegian Statistics Bureau and the Brønnøysund Register Centre.

  10. The random sample was taken region-by-region (in total five) in order to ensure representativeness of the full population of firms. When the random number gave a firm not having a website (very few…), the subsequent firm on the list was selected; the same was done for a few seemingly irrelevant industries for the purposes of this study. The sample includes both firms presently having and not having strategic alliances, allowing for uncovering eventual differences between these groups. Most importantly, the sample represents a broad range of industries.

  11. A separate CFA was done for some of the control variables; equally showing excellent goodness of fit values (Chi square = 91.434, p = .1798; RMSEA = .032, CI .000–.060; CFI/TLI = .991/.988; SRMR = .047).

  12. Prior studies have established that the perceived trustworthiness dimensions are theoretically and empirically distinguishable constructs. CFA analyses were conducted for confirmation in this study’s setting. A one-factor (all items together), two-factor (integrity + benevolence) model, and three-factor model were formed. The three-factor model was the only one with acceptable fit values.

  13. Not controlling for geographic origin of the prospective partner was a consciously made trade-off. Additional scenario versions would allow for more generalization, but would demand a larger sample size. For the same reason, the scenario does not include controls for other reputational issues. Besides, describing the prospective partner as having good product quality, innovative skills, and a solid financial situation is appropriate/more realistic, since the respondent is assumed to estimate such aspects first (consistent with anecdotal evidence from pretest interviews).

  14. Structural equation modeling (SEM) is suitable when there are latent constructs and for examining a series of dependence relationships simultaneously (Kline 2010). Yet, other statistical approaches were necessary for the following reasons. First, there should be strong theoretical support for the conceptual model (Ibid.). Given the fairly weak theoretical support for some hypotheses, this requirement is not fully supported. Second, although the sample size needed hinges on many factors, SEM generally requires large samples. According to Kline (2010), “reviewers of journal submissions routinely reject for publication any SEM analysis where N <200 unless the population studied is restricted in size” (p. 12).

Abbreviations

CI:

Confidence interval

CEO:

Chief Executive Officer

CFA:

Confirmatory factor analysis

CFI:

Comparative fit index

COO:

Chief Operating Officer

CSR:

Corporate social responsibility

GNP:

Gross national product

MBA:

Master of Business Administration

R&D:

Research and Development

RMSEA:

Root mean square error of approximation

SEM:

Structural equation modeling

SRMR:

Standardized root mean residual

TLI:

Tucker–Lewis index

VIF:

Variance inflation factor

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Acknowledgments

The author wishes to thank her advisor Pierre-Xavier Meschi, Editor Thomas Clarke, and three anonymous reviewers for their helpful comments and suggestions. Arild E. Hansen, Sally Kemble, Marie Koulikoff-Souviron, Isabella Soscia, and Ulrich Wassmer provided constructive remarks on the survey instrument. Thanks are also extended to the participating top executives.

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Correspondence to Anne Norheim-Hansen.

Appendices

Appendix 1

See Table 6.

Table 6 Sample description of alliance formation scenario

The alternative descriptions of the two manipulated variables are non-equity contractual alliance and ABC is perceived among its stakeholders as having a compliance-based environmental strategy. The firm is known for implementing environmental activities in its business operations only when these become mandatory by the law; it does not in any way strive to exceed such requirements in its environmental performance. Consequently, ABC has a rather neutral environmental profile among stakeholders.

Every respondent is presented with one scenario version only (randomly attributed).

Appendix 2

See Table 7.

Table 7 Scale items

Appendix 3: Pretests of Measurement Instrument

The measurement instrument (cf. Appendices 1, 2) was pretested on both academics and professionals (Krishnan et al. 2006). Four experienced academics were asked to comment on the entire questionnaire, which also includes questions on, e.g., alliances of the responding firms (cf. Appendix 4). Some changes were incorporated, mainly related to ambiguities or wording in the scenario and questions. Reducing item ambiguity is among the measures taken to reduce common method bias (Ibid.).

Subsequently, the questionnaire was administered to 34 CEOs, 1 COO and 2 divisional managers in manufacturing firms in the Western region of Norway during audio-recorded interviews (the Western region is responsible for ca 70 % of total GNP. A restricted geographical zone was selected due to research budget and time constraints). Here as well, some comments were incorporated. Preliminary statistical analyses showed the Cronbach’s alphas of the constructs to be acceptable, indicating that the constructs are reliable.

It should be noted that the hypotheses of this paper were developed strictly based on the literature, and not affected by the qualitative data obtained during the pretest interviews—treated as anecdotal evidence, as this is not a mixed-method study. Yet, these data provide some degree of informal triangulation; they have high consistency with the results.

Appendix 4: Descriptive Statistics on Final Sample Firms’ Alliances

  • 44 % reported presently having strategic alliances;

  • 64 % of the alliances are with a partner firm from the same industry;

  • 52 % of the alliances are with a Norwegian partner firm;

  • 10 % with other Scandinavian;

  • 28 % other European;

  • 10 % with partner firms outside of Europe;

  • 41 % of the alliances are equity alliances (joint venture or minority equity investment);

  • 56 % are non-equity contractual alliances (3 % did not report alliance governance type);

  • 12 % are R&D only;

  • 5 % manufacturing only;

  • 21 % marketing only;

  • 10 % R&D + manufacturing;

  • 11 % R&D + marketing;

  • 23 % manufacturing + marketing;

  • 13 % all three (5 % did not report alliance governance type);

  • Average age of the alliances is 6 years.

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Norheim-Hansen, A. Are ‘Green Brides’ More Attractive? An Empirical Examination of How Prospective Partners’ Environmental Reputation Affects the Trust-Based Mechanism in Alliance Formation. J Bus Ethics 132, 813–830 (2015). https://doi.org/10.1007/s10551-014-2342-1

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