General deterrence in the waste industry in the Netherlands. Research seminar on qualitative methods in environmental compliance research Karin van Wingerde Faculty of Law/ Criminology Wednesday, April 23, 2008

Research question How important is the fear of sanctions in motivating companies in the waste industry in the Netherlands to comply with environmental legislation?

Theoretical framework Shift towards a more punitive model of corporate crime control Severe penalties necessary for compliance General deterrence theory

Proposed methods Inspired by Thornton, Gunningham, Kagan (2005) In depth interviews with environmental managers ‘Signal cases’ –Variety of violations, media attention –Criminal and administrative penalties Confrontation of interview data with interviews with enforcement agencies and data to indicate level of compliance

Potential problems How to obtain acces? –Also another study on experiences with regulators –Waste industry Closed Large cases of environmental misconduct –Environmental managers Busy people No interest in participation

Potential problems How to obtain reliable data? –Managers’ ‘respectability’ Rationalisation Socially accepted answers –Sensitivity towards: Compliance issues “Criminology”

Trade organisations (letter of recommendation) 2 ‘signal cases’ presented anonymously A cautious approach

Data gathering In depth interviews with environmental managers of 23 companies in the waste industry (work in progress) –High response –21 tape recorded Reasons for participation –Transparency –Professional branch of industry

Problems Signal cases – anonymously –Awkward situations: No clear expectations Guesses Involvement with either one of the cases –Reaction: changed presentation of the cases

Advantages Very detailed and comprehensive descriptions of perceptions towards sanctions Openness External validity: not in terms of generalisation but range of results Reliability enhanced by standard topic list; results confronted with other data

Lessons Accessibility is not necessarily an issue: Companies are willing to participate Cautiousness might be counterproductive Openness and transparency rather than socially accepted answers and rationalisations

Discussion Approachability ‘Respectability’ Caution

Preliminary results Little knowledge of penalties against other companies –Either large or minor cases –Case is remembered, not the penalty –Incorrect estimation of penalty Risk perceptions –Risk of detection –Risk of penalties

Preliminary results Threat? –Negative publicity Social license Image of the industry Reputation of the individual company Compliance related behaviour? –Check –No proactive measures

Overcoming inaction through collective institutional entrepreneurship Research seminar on qualitative methods in environmental compliance research Frank Wijen Rotterdam School of Management Wednesday, April 23, 2008

Kyoto: The development of a global regulatory institution Collaboration of dispersed agents required Need to overcome inertial forces: - Free-rider problem - Start-up problem - Actor apathy problem

Theoretical perspectives Combined insights from: - Institutional theory - Regime theory

Conceptual framework Drivers of institutional entrepreneurship: - Manipulating power configuration - Creating common ground - Mobilizing bandwagons - Devising appropriate incentive structures - Applying ethical guidelines - Using implementation mechanisms

Empirical setting Kyoto regime: collaboration of most nation states to provide global public good despite strong inertial forces Institutional entrepreneurship drivers used to establish Kyoto regime

Empirical method Case study: why and how questions

Empirical analysis 1. Deductive categorization plus emerging categories 2. Integral coding of all data (with Atlas/ti) 3. Checking of coded chunks to correct miscoded chunks, remove redundancy, and merge categories 4. Sense-making per category 5. Sense-making across categories

Methodological headaches How to reduce data without throwing away the baby with the bath water? How hard is soft data? How to disentangle contextual and causal factors? How to rule out alternative explanations?

Hypotheses H1: A clear conceptual framework is instrumental in reducing data without killing babies H2: Soft data is as soft as hard data (even though most quantitative researchers have not yet ‘come out’) H3: Conceptual frames and further empirical studies help to disentangle causal and contextual factors H4: Alternative explanations cannot be ruled out, only acknowledged