Stakeholder pressure, eco-control systems, and firms’ performance: empirical evidence from UK manufacturers

ABSTRACT

This study investigates whether stakeholder pressure directly intensifies the extent of eco-control systems’ use, and thus indirectly affects economic and environmental performance. Cross-sectional data was collected from 93 UK manufacturers belonging to industries of high pollution propensity, and analysed using structural equation modelling. This study provides a broader understanding of environmental management control systems (EMCS) development, responds to calls in the literature for extending prior empirical research to both the antecedents and consequences of EMCS, and offers further evidence from the UK context (one of the leading countries in tackling environmental-related issues). Our findings reveal that the pressure from organisational stakeholders is significantly and positively associated with all eco-control systems’ constructs. Interestingly, our findings indicate a lack of significant indirect relations between stakeholder pressure groups and firms’ performance (economic or environmental), and only eco-control incentives influence UK firms’ environmental performance.

KEYWORDS:

• Eco-control systems
• economic performance
• environmental performance
• manufacturing firms
• stakeholder pressure
• UK

Acknowledgments

The authors thank the editors and the two anonymous reviewers for their constructive feedback. The authors extend their gratitude to participants at the American Accounting Association 2016 Annual Meeting (New York, USA); as well as Dr Wael Hadid; for their valuable feedback on an earlier version of this paper. The authors are grateful for the financial support received from summer research grant, College of Business and Economics, United Arab Emirates University, United Arab Emirates (Fund Code #: SRG-CBE-2012).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 For brevity, the discussion of these frameworks is summarised in Appendix A (A1). All appendices are included in the supplementary materials.

2 For more details, please refer to Appendix A (A3).

3 For more details, see Section (3).

4 www.qualtrics.com

5 These are: reduction in costs of regulatory compliance (EnvP3); filters and controls on emissions and discharges (EnvP14); and residue recycling (EnvP15); see, environmental performance items, Appendix B (B3).

6 Ten times the number of independent variables in regression in the model is set to be the minimum sample size for PLS analysis (Chin & Newsted, 1999). In our model, the largest multiple regression incorporates five independent variables; hence a minimum of sample size of 50 is implied.

7 For the first two indices, the null hypotheses are APC = 0, ARS = 0; against the alternative hypotheses that they are ≠ 0.

8 For AVIF and AFVIF results, values equal to or lower than 3.3 are accepted as threshold for models with constructs consisting of two or more indicators (Kock, 2019).

9 See, Meier et al. (2015).

Additional information

Funding

The authors are grateful for the financial support received from summer research grant, College of Business and Economics, United Arab Emirates University, United Arab Emirates [Fund Code #: SRG-CBE-2012].