Change-making in Environmental Impact Assessment (EIA): piloting changeology approach using England as a case study

ABSTRACT

Piecemeal changes to the Environmental Impact Assessment (EIA) process have to date not fully delivered EIA’s normative goals and met today’s environmental challenges. By regarding the to date approaches to change-making as a problem requiring a solution, this paper applies critical analysis to reflect upon current change-making based on England’s EIA system as a case study. The analysis identifies a lack of innovative ideas and sound evidence-based approaches to inform and support the change-making process. Consequently, we argue for an epistemology of change-making (changeology) so that the entire approach can be based on an empirically informed framework, to inform the journey (process) and destination (fit-for-purpose EIA) and make the EIA process fit-for-purpose and aligned to future expectations. Changeology should be viewed as more than informing one-time change-making but as a framework of well-studied practice for changing (or improving) EIA in the long term.

KEYWORDS:

• Change-making
• changeology
• Environmental Impact Assessment (EIA)
• England EIA

1. Introduction

Environmental Assessment (EA) practice, including both Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA), has often been challenged with the need to improve (Morrison-Saunders et al. 2014) and subjected to periodic reforms and incremental changes aimed at addressing ongoing and emerging environmental challenges (Vanclay 2015; Fonseca et al. 2017). Yet for some (Banhalmi-Zakar et al. 2018), the EA process has not fundamentally changed and questions about its effectiveness (Arts et al. 2012; Emerson and Baldwin 2019) and ability to fulfil its aims are being raised (Pope et al. 2018; Alberts et al. 2020). These include debates about whether and how EA should further develop or change to be fit-for-purpose and deliver its normative objectives (Bice and Fischer 2020); whilst avoiding maladjustments, which as a property of a process or system exemplifies a failure to develop, adjust or commensurately respond to the demands of its environment and deliver the required outcomes (Gazzola 2022). They also include calls for a paradigm change in EA from assessment as problem-identification to assessment as problem-solving (Castree et al. 2021).

Within this context, EA appears to be therefore at a crossroads, with the concept of change and of change-making at the centre of this junction. ‘Change’ is central to any process within which inputs are transformed into outputs to meet a specific aim (Hall and Fagan 1956), based on the philosophical stance that change is the actualisation of inherent potential (Feser 2017). EA is no different; as a process for identifying and evaluating the potential environmental impacts of proposed development policies and actions, it aims to ensure environmental protection for sustainable development. Other aims associated with EA include its potential to enhance transparency, reflexive learning and legitimacy in decision-making processes (Glasson et al. 2012). Further, like other processes, EA is neither perfect (design flaws) nor does it always deliver as expected (implementation flaws), as shortcomings (poor outcomes) can often occur as widely documented in the EA literature (Arts et al. 2012; Fonseca 2022). This emphasises the importance of change and of change-making in EA, particularly when considering whether purposeful design interventions aimed at further improving the EA process are needed, as highlighted by Gazzola (2022).

Change-making is a formal intervention aimed at improving a system or process by introducing or replacing something with another that is new or different (Serrat 2017); referring to the development and implementation of a change management strategy, undertaken to improve processes, technology, compliance, efficiency, productivity or customer service. Improvements are made to address flaws, particularly to eliminate inefficiencies, pinpoint redundancies and minimise waste in time, resources, or materials (Fryer et al. 2007), influencing in turn the evolution, nature, characteristics (boundaries, sensitivities), behaviours and performance of a set process over time (Vester 2007). Within the context of EA, Onyango (2016a, 2016b), using sensitivity analysis, we illustrated the complex nature of the SEA process as composed of interdependent interactions of individual parts; through ‘inputs and outputs’ underpinned by negative and positive feedback loops that regulate the achievement of environmental integration. Further, he highlights areas of uncertainty and leverage in influencing SEA process behaviour and outcomes, implying that attempts to change SEA require system-thinking analysis to know where to intervene and how to calibrate the change needed (ibid).

While change-making as a process is directionally neutral, the changes or improvements that occur are intended to be positive, though their success cannot be guaranteed as challenges and pitfalls may occur (Cameron and Green 2024) and should not be underestimated. Works by van den Bergh and Kallis (2009) and Witt (2016) on policy evolution further illustrate the importance of examining unintended pitfalls, and of the need for in-depth empirical studies to escape the lock-ins of current process trajectories driven by processes of incremental change. In this paper, we argue that change-making in EA has occurred without a clear epistemological (Wenning 2009) stance to guide ‘change-making’ as a phenomenon; including whether alternative approaches to change-making are contemplated and explored. This can be likened to published work identifying the lack of scientific rigour in assumptions in EA as a shortcoming hindering further developments of the EA process (Kågström and Richardson 2015; Jha-Thakur and Fischer 2016; Cashmore et al. 2020). Therefore, unless change-making in EA is re-imagined and built on a new ambition, vision, or methodology, a fit-for-purpose future EA may be challenging to deliver. Thus, future EA will remain ineffective, fraught, and hostage to unintended and adverse effects or maladjustments; perhaps follow a process of attrition, via political agreements and policy expediency, until a viable path, perhaps the only one left, is clear, risking costly maladjustments along the way. This is because choices during change-making comprise a crucial diverse basket of competing options, upon which evolutionary pressures work, thus fundamentally influencing the nature and direction of EA evolution.

Within this context, this paper aims to explore the process of change-making in the development of EA systems, by reflecting on the extent to which a change-making approach like changeology can enhance the delivery of more-fit-for-purpose EA. This is done by looking at change-making practice in England as a case-study. While not globally representative, several criteria make England suitable for drawing lessons: its EIA system is well covered in the international EA literature which enhances its familiarity to an international audience; its EIA regime has undergone change-making several times, making it a relevant source of data, and; its system was set within the European Union’s (EU) EIA framework, which is relevant to a number of countries. Altogether, these criteria contribute to making the findings potentially of interest to other jurisdictions. The research question being: what lessons can EA borrow from changeology? As a theory of change, changeology originated in the 1990s from John Norcross, who applied sophisticated scientific evidence from psychological research into practical, understandable and doable steps for changing behaviour. Robinson (2012) and Norcross (2013) present changeology as based on a synthesis of theories (e.g. diffusion of innovations, self-efficacy, social learning theory, risk perception theories) for understanding what it takes for new practices or products to be adopted by people in their social, technological and physical environments. Following the introduction and informed by reviews of the literature, key ideas about change and change-making are explored in further detail. Subsequently, the methodology is explained, and the case-study is introduced. The findings are then presented and discussed, followed by concluding remarks.

2. Setting the context

This section gives an overview of change by discussing some theories of change, types of change, and change-making models, including changeology.

2.1. Change and change-making

The term ‘change’ is often at the centre of scholarly debates in different disciplines, partly as a reflection of the increased complexity, unpredictability and vulnerability of the world that we live in, with political, socioeconomic, technological and environmental shifts determining the pace at which change takes place, and at which our processes need to adapt to. EA is no different. Since it was first introduced in the USA in 1969, EA has evolved in response to ongoing and emerging environmental challenges and changed through processes of incremental improvement (Glasson et al. 2012; Morrison-Saunders et al. 2014). Informed by reviews of the literature in the fields of process improvements (von Bertalanffy 1968; Deming 1986; Vester 2007; Langley et al. 2009), this section provides an overview of discussions on change and change-making, within the wider context of EA.

A review of the literature reveals that there are different, and sometimes overlapping theories of change, explaining how and why change occurs and targeting specific aspects of change, such as human psychology and behaviour, cultural, structural and framework changes at individual or organisational level (Atkinson et al. 2015). Dialectical theory, for example, states that change results from the conflict between opposing forces or ideas. In evolutionary theory, change is instead driven by variation, selection, and retention of the best practices. In teleological theory, change is guided by a purpose or goal that an organisation strives to achieve. Life cycle theory argues that change follows a predetermined pattern of stages or phases (Atkinson et al. 2015). For Cameron and Green (2024), a theory of change delineates and makes explicit both the pathway and outcomes of a change initiative (early, intermediate, and longer term) and the action strategies to achieve the outcomes. They add that the quality of a theory of change is judged by four explicit criteria: how plausible, doable, testable, and meaningful the theory of change is. As noted by Hiatt (2006) and Hicks (2022), change theories find expression and application in change-making models designed to deliver different types of change, according to what change and what type of change is needed, and the nature of the process being changed. Different types of change exist, albeit with overlaps, each requiring a different strategy for implementation (Langley et al. 2009), which might be of relevance to EA. For example (Atkinson et al. 2015; Serrat 2017):

• Strategic change: targeting policies, structures or processes to achieve goals, boost performance in EA, or respond to opportunities or threats.

• People-centric change: targeting working environments in EA systems, aimed at enhancing transparency, communication, effective leadership and an empathetic approach within the EA community.

• Structural change: targeting major shifts in organisational structure, e.g. management hierarchy, team organisation, responsibilities, and administrative procedures. This could refer to where EA sits in regulatory frameworks or where EA competencies and responsibilities sit in relation to different actors.

• Technological change: targeting new software or systems aimed at improving processes. Recent technological advancements in EA are highlighting the potential for automated data collection and/or AI (Sandfort et al. 2024; Bond and Dusik 2020).

• Unplanned change: a necessary action following unexpected events, such as a shift to remote working or the need for an unexpected succession plan. The recent COVID-19 global health pandemic required EA to adapt, as illustrated by Abbasi (2023) and Chen et al. (2024).

• Remedial change: reactionary and occurring when a problem is identified and an immediate solution is needed, e.g. in relation to customer satisfaction issues in EA.

Several change-making models, underpinned by different change theories to deliver various types of change, exist (Table 1). These include, for example, the Plan Do Check Act (PDCA) or the Deming cycle model, which is an iterative four-step model for improving processes and implementing change (Garza-Reye et al. 2018). Following the scientific method of ‘hypothesis-experiment-evaluation’, the PDCA model was used to underpin changes to the EU EIA Directive (Onyango 2016a), though no study has explored its effectiveness within EA.

Table 1. Fundamental elements of a selection of common change-making models (see Hiatt 2006; Atkinson et al. 2015; Hicks 2022).

Model	Focus	Key steps
ADKAR	Employees’ welfare	Awareness, desire, knowledge, ability, reinforcement
Lewin’s	Enabling organizational structure	Unfreeze, change, freeze
Kotter’s	Employees’ response & success factors to execute change	Increase urgency, build team, form strategic vision, communicate, enable action, short-term goals, reinforce change, embed change
McKinsey 7-S	Organization’s design for change management	Strategy, structure, systems, shared values, style, staff, skills
Kübler-Ross Five Stage	Employees in change management process	Denial, anger, bargaining, depression, acceptance
Bridges’ Transition	On transition (internal), rather than change (external)	Ending, losing, letting go; neutral zone; new beginning
Rogers Technology Adoption Curve	Categories of people: innovators, early adopters, early majority, late majority, laggards, leap-froggers	Spread people along S-Shaped curve and make them more willing & active for change.
PDCA	Planning activities	Plan, Do, Check, Act
ToC	Outlining causal linkages in a proposed initiative or policy, to promote desired change	shorter-term, intermediate, and longer-term activities and outcomes, mapped
Changeology	Vast body of theory & practice into key steps	Clarifying purpose, defining the project, enabling action, fast prototyping, feedback & evaluation.

Another model is The Theory of Change (ToC), outlining causal linkages in a proposed initiative or policy, i.e. its shorter-term, intermediate, and longer-term outcomes, then mapping backwards to identify necessary preconditions to promote the desired change (Taplin and Clark 2012). The links between outcomes are explained by rationales or statements of why one outcome is thought to be a prerequisite for another. Based on a ToC model, Alberts et al. (2020) identifies 19 key assumptions within the causal logic between the design, inputs, activities, output, outcome and impact evaluation components through which EIA in South Africa works, which they argue should be tested and for which a critical rethink is required to make EIA fit-for-purpose.

The Bridges Transition Model (Atkinson et al. 2015) makes a distinction between change and transition. While change results from and is determined by external forces, transition is the psychological process whereby those involved learn to adapt to change. It deals with change through a three-step approach including: the End, where people openly acknowledge the change and the reason for change; the Neutral Zone, where people come to terms with losses from change, and; the New Beginning, where people accept the purpose and understand how the organisation will change. The Prosci ADKAR Model, developed in 1998 using research from over 300 companies undergoing major changes, is goal-oriented and focuses on an individual and business results (Cameron and Green 2024). The Kotter change management model, based on the analysis of 100 different organisations going through change, describes eight stages to support change managers understand how people accept, engage with, and maintain successful organisational change (Kotter and Cohen 2012).

Finally, a relatively new model or better approach, is that of changeology (Prasad 1996). Based on the simplification of a vast body of theory and practice into key steps, changeology can help contemplate interactions and enable relationships between people, offering scope for modifying technological and social contexts, e.g. in EA regulatory frameworks, procedures, and stakeholders’ engagement. It is topic neutral and has been applied in different settings, including mechanical systems and set ups such as when considering change in/to factory manufacturing; and non-mechanical and more complex processes and set ups, where aspects of human psychology and human behaviour are central, such as when designing and addressing change in relation to climate change, obesity, AIDS, nutrition, road safety and workplace changes (Robinson 2012). What the selection of models presented in Table 1 have in common is that they: are supported by an empirical body of knowledge to guide change-making; are underpinned by a competent understanding of the nature and behaviour of the process at the heart of change-making, and; offer tested and verified methods for effecting desired change. While most models are specific and targeted to certain issues and types of change, changeology is distinct in that it has the advantage of being topic-neutral and has the potential of being underpinned by any range of relevant theories and where necessary, work with other change-making models too. Moreover, more than the other models and due to its inherent empirical nature, changeology can help break inertia and ‘lock-ins’ and open opportunities for change. For these reasons, changeology will be the preferred framework for analysing and evaluating the change-making processes in this research. Subsequently, changeology is explored in more detail.

2.2. Changeology

Changeology is a step-by-step approach based on a synthesis of theories for understanding what it takes for new practices or products to be adopted by people in their social, technological and physical environments. At its core, it acknowledges: 1) factors which must be present in actors’ lives for sustained adoption of change, and; 2) the principle that scientific examination is at the heart of evolutionary public policy change and design. Robinson (2012) conceptualises changeology as having three pillars. The knowledge base, referring to a store of information or underlying set of facts, assumptions, and rules available to solve a problem. The theoretical base, referring to the foundational framework from which the knowledge is constructed for understanding a phenomenon, serving as the structure and support that links all elements and rationale for the phenomenon. The process base, which is a series of interrelated tasks taken to achieve an end, encompassing the understanding and application of the fundamental principles and laws that govern that transformation. In practice, these pillars are operationalised following five rigorous steps:

• Clarifying the purpose of change-making, i.e. setting or agreeing to future conditions.

• Defining the project, i.e. clarifying the scope in terms of who does what, pivotal actions and testing feasibility.

• Enabling action, i.e. identifying innovative methods and tactics to deliver desired actions.

• Fast prototyping, i.e. mobilising from a small, low-risk scale, allowing for reflexive learning and improvisation, to learning what makes a successful change-making project.

• Feedback and evaluation, using indicators and monitoring to actively manage the change project.

The steps can be based upon a synthesis of approaches from many disciplines, incorporating the diverse real-life experiences, concerns and challenges of the participants.

3. Methodology

This section presents the methodology adopted in the research: encompassing a case-study method and its rationale, followed by an overview of the changeology framework as applied to the case-study.

3.1. Case-study method and selection

To explore the potential of changeology in understanding the process of change-making in EA, the EIA system in England is adopted as an instrumental case-study, which is effective in investigating and providing insight into a particular phenomenon within a given context (Yin 2017). As a well-known method for conducting exploratory inquiry (Stake 1995), case-studies are frequently adopted in EA research (Dilay et al. 2020; Kor et al. 2022). In this study, the change-making approach culminating in reforms to England’s (UK) the Town and Country Planning (EIA) Regulations 2017 (UK Government 2017) (Hereinafter the Regulations), applying the EIA Directive 2011/92/EU (EC European commission 2011) as amended by Directive 2014/52/EU (EC European Commission 2014), was selected as the case study. The 2017 Regulations, one among over 20 introduced to cover EIA in England, is of interest as most EIAs in England are undertaken within its remit (Glasson et al. 2012) (see section 4).

3.2. Data collection and analysis

To collect data a 3-phase approach was adopted. Phase one aimed to map changeology’s steps onto the case study and assess the level of coherence between them. This required access to descriptions of the approaches to change-making that culminated in the Regulations. As this information was distributed across several sources, we used Boolean operations (‘UK EIA regulations’ AND ‘amendment’ OR ‘change’ OR ‘studies’ OR ‘reviews’) as conjunctions to combine keywords in the Google Scholar, Web of Science and Scopus databases, to identify potentially relevant sources. This returned 12,173 hits. To refine the search, a staged review process (Torraco 2016) (i.e. title, abstract, body, and conclusion) was applied to eliminate irrelevant documents, based on several inclusion criteria (Figure 1).

Figure 1. Steps in the search for relevant documents to include in the data collection.

This led to 20 documents (reports and peer-reviewed articles) covering the change-making exercise, e.g. details of the process, inputs, analysis and associated narratives, attitudes and values that went into the change-making in the case study, being included (Table 2).

Table 2. Key documents from literature search containing the rationale, approaches and inputs that resulted in directive 2014/52/EU (EC European Commission 2014) and the regulations.

Level	Documents
EU	Policy reports and academic articles: On the application and effectiveness of the EIA Directive (Directive 85/337/EEC, as amended by Directives 97/11/EC and 2003/35/EC) COM(2009) 378 final EC European Commission (2009b). The mid-term review of the sixth Community Environment Action Programme EC European Commission (2009a). On the Application and Effectiveness of the EIA Directive (Directive 85/337/EEC as amended by Directive 97/11/EC) COM(2003) 334 EC (2003). Implementation of Directive 85/337/EEC on the Assessment of the Effects of Certain Public and Private Projects on the Environment CEC (1997). Implementation of Directive 85/337/EEC on the Assessment of the Effects of Certain Public and Private Projects. COM(93) 28 final – Vol. 12. CEC (1993). Costs and benefits of the EIA Directive Oosterhuis (2007). Opinion of the European Economic and Social Committee on the ‘Proposal’ EC (2011). Arabadjieva (2016); Gunningham and Sinclair (2017); Lonsdale et al. (2017); Sheate et al. (2005).
UK	Policy reports and academic articles: Government response to the technical consultation on environmental impact assessment thresholds DCLG Department of Communities and Local Government (2016). Government response to the technical consultation on Environmental Impact Assessment (regulations on planning and nationally significant infrastructure) DCLG (2017). Better regulation framework: interim guidance (BEIS 2023). Fischer et al. (2016); IEMA (2011); Fischer (2023); Fischer et al. (2023); Fischer (2022a), (2022b).

In phase two, each document was downloaded and perused by the authors to assess extent to which changeology’s five steps (Review areas) (section 2.1) were evidenced; using five skills of critical analysis (see Foucault and Lawrence 1988; Cottrell 2017) as Review categories (RCs), i.e.:

• Issue-framing – ability to carefully examine something as a problem and clarify the key issues.

• Communication – ability to share conclusions more widely.

• Creative ability to think outside the box and apply different perspectives.

• Open-mindedness to other views.

• Problem-solving ability.

Critical analysis skills, driven by rational questions about framing a problem and how a solution might be approached, helps structure the questioning of meaning, conditions and goals, allowing one to view other scientific theories, political views, or contradictory enunciations as responses to the same situation. It allows new viewpoints, consciousness, hope and action (Crotty 1998) to emerge. Critical analysis is applied in approaches like SWOT analysis (Bell and Rochford 2016) or Force-field analysis (Thomas 1985), for evaluating and developing strategic planning and to aid decision-making. Crotty (1998) argues that while the answers are not obvious or known, critical analysis can throw up issues, which if further investigated, can provide an approach to resolving current problems. In relation to each step of changeology (Review area), the question asked was: how has each critical analysis skill e.g. ‘issue framing’ (Review category) been executed and is the output according to what is expected from ‘good practice’? A grade was awarded for the procedure and another for the output: then a mean grade was finally given as a comprehensive representation of the quality of the Review category. The grading used review criteria and qualitative rating scale based on the commonly acknowledged quality review package by Lee et al. (1999) (Table 3). Each researcher undertook this grading separately and then they compared grades and awarded a consensus grade after consultation.

Table 3. Grading scale to assess extent changeology’s elements were applied, making changeology the benchmark (Source: adapted from Lee et al. 1999).

Grade	Review criteria	Classification
A	Performed to a high standard/good practice; no omissions/expected output evident.	Satisfactory
B	Generally satisfactory and complete/good practice evident; but minor omissions and/or inadequacies in input.
C	Satisfactory despite some omissions and/or inadequacies/good practice alluded to but absent; moderate outputs available.
D	Some parts well attempted; overall, unsatisfactory with important omissions and/or inadequacies in input.	Unsatisfactory
E	Not satisfactory; significant omissions/inadequacies/no clear evidence in output.
F	Very unsatisfactory; important tasks poorly undertaken or no attempted; relevant outputs missing.

The results from this phase will feed into synthesis and reflection, in phase three, and help identify potential areas for improvement and generate considerations which can enhance change-making in our case study, from a changeology perspective. Figure 2 summarises how the problem statement, research design, data collection and analysis, are applied to address the research aim.

Figure 2. An outline of the methodological approach and steps in the study.

4. Change-making in England’s EIA system – setting the context

This section outlines the state of art in change-making in EA, based on EIA in England. Crucially, changes and change-making at the EU level sets the scope for subsequent changes in members states (MSs) as the EIA Directive (85/337/EEC) (EC European Commission 1985) adopted in 1985, amended in 1997, 2003, and 2009, sets an overarching framework and principles that MSs must adopt. While Directives are binding with respect to the intended result each MS chooses the form and method for national implementation, i.e. transposition. The amendments were codified by Directive 2011/92/EU and again amended in Directive 2014/52/EU to align with the EU’s international commitments and other legal developments, e.g. rulings of the EU’s Court of Justice. The legislative procedure for the Directive is complex, giving the European Parliament (EP) and the Council, equal power to co-legislate in a co-decision procedure, comprising one, two or three readings to agree on the same final text. Amending the Directive therefore involves extensive political bargaining across the EU and MSs; informed by a comprehensive review, consultation process, and impact assessment report (Fischer et al. 2016; Arabadjieva 2016); supported by reports on the effectiveness of the EIA Directives (see EC website Environmental impact assessment (europa.eu).

Narratives accompanying these amendments were driven mainly by the motive of reducing administrative costs and burdens in EIA. For Lonsdale et al. (2017), the reforms were about harmonisation of procedures across MSs; the focus of change often on procedural improvements to ‘fix’ identified flaws (Fischer 2022a, 2022b), without much attention on the extent to which these processes of change-making are leading to process trajectory lock-ins (Markard et al. 2012) and/or delivering improved EA outcomes, e.g. environmental protection. The broad intention was deregulatory: to simplify and clarify requirements in line with the drive for Better Regulation (EC 2023) without weakening existing environmental safeguards and with a view to making business decisions on public and private investments more sound, more predictable, and sustainable (van Gossum et al. 2010).

The UK’s devolved administrations of England, Wales, Scotland and Northern Ireland have their own EIA regulations. In England, EIA is spread across several policy sectors and EIA regimes, e.g. town and country planning, nationally significant infrastructure, electricity, agriculture, forestry, transport and fisheries. Each regime has its own EIA legislation which must be reformed to transpose the EIA Directive 2011/92/EU, as amended. England’s transposition of the EIA Directive was guided by several principles: retaining as far as practical the existing approach to EIA as it was well understood by stakeholders; not exceeding the minimum requirements of the Directive (HM Government 2018); and, following the government’s Better Regulation agenda (proportionality; consistency; accountability; transparency; and targeted regulation), in assessing the burdens government regulatory decisions placed on business and civil society organisations (BEIS Department for business, energy & industrial strategy 2023). Notably, the England government was not an ardent fan of EIA and anything that might be perceived as a ‘constraint on economic development’ (Fischer 2023) or adding ‘financial burdens to ordinary people’ (Harvey et al. 2023). Overall, the above context implies that future change-making approaches must carefully consider and evaluate the barriers and opportunities inherent in such a complex and political process.

5. Results

Section 5.1 presents the extent to which changeology’s five steps (review areas) were evidenced in the case study. Where similar results exist for the review categories, they have been combined for brevity in presentation. Section 5.2 synthesises the results along changeology’s three pillars, benchmarking the state of art, followed by reflection on alternative viewpoints for potentially viable options, approaches, attitudes, values and thoughts, which could enhance performance in change-making. Ideas, which if further considered, could generate a more robust evidence-based and methodology-driven approach to change-making in our case study. As this discourse is driven by the authors’ perspectives different results may come from a similar exercise undertaken by others.

5.1. Case study performance

5.1.1. Clarifying the purpose

5.1.1.1. Issue framing

The justification, aims and objectives of making changes to the Regulations were clearly framed as transposing the amended Directive’s objectives: achieving harmony, strengthening the quality of EIAs, improving coherence and synergies with other EU laws and simplifying of procedures. The Better Regulation objectives were also listed as core considerations in delivering the reforms. [A].

5.1.1.2. Communication

England’s relevant authorities for generating policy and regulations, e.g. the Department for Communities and Local Government (DCLG) sent out several communications to potential stakeholders about the purpose of the change-making and the proposed changes. Supporting materials, e.g. impact assessment report on the proposed changes, a summary of consultation and government responses, were publicly available on websites. [A].

5.1.1.3. Creativity and open-mindedness

Although views were sought from various stakeholder consultation exercises, the views were limited to areas where MSs have discretion. Ambition about what to change and achieve was constrained by the proposals presented by DCLG and not open to adjustment by the stakeholders. [C].

5.1.1.4. Problem-solving

The change-making aimed to solve mostly transactive issues, e.g. efficiency, or cost-effective procedures, timelines, burdens and costs, via harmonisation and streamlining. The solutions were framed in terms of avoided risks, e.g. of environmental and public health damages, and savings by various beneficiaries (Citizens – better, more transparent EIA procedures and project approval decisions; Industry – simplified and streamlined EIA procedures, reduced costs, level playing field; Public authorities – clearer legal framework). It was however not clear how these terms were explicitly linked to EIA outcomes like environmental protection. While some changes were intuitively beneficial, e.g. clarifying terminologies (‘EIA’, ‘Human Beings’ replaced with ‘Population and Human Health’, ‘Flora & Fauna’ replaced with ‘Biodiversity’); other changes required more evidentiary basis as they could have far-reaching, cummulative, and different impacts across MSs. For example, changing the applicable thresholds of criteria in Schedule 2 in relation to Industrial Estate Development Projects, from 0.5 to 5 hectares. However, no robust analysis demonstrated the extent to which these changes were commensurate to the perennial challenge of substantive effectiveness of EIA. It was assumed that ‘streamlined’ and/or ‘cost-effective’ EIA procedures would lead to a fit-for-purpose EIA. [C].

5.1.2. Defining the project

5.1.2.1. Issue-framing and communication

The scope and responsibilities of various actors were clearly stated as were the procedures (timetables and means) and steps. The feasibility of the change-making project was framed in two main ways. One, solving defined problems, e.g. addressing the factors limiting environmental and socio-economic benefits of EIA; addressing EIA shortcomings (and their underlying causes using a problem tree) e.g. insufficiencies of the screening process, quality of analysis and of the EIA report, and inconsistencies in the EIA process. Two, an administrative interest reflected in the institutional harmonisation across MSs rather than effectiveness of EIA per se, whilst limiting adverse impacts on businesses. Notably, this was accompanied by very low awareness amongst contemporary policymakers on the lessons of past reforms (see Fischer 2022b), as well as evidence on how the changes enhance EIA effectiveness beyond harmonisation and streamlining. [A].

5.1.2.2. Creativity, open-mindedness and problem-solving

Ambition and scope were limited to addressing only those issues that would bring the Regulation in line with the EIA Directive, following a top-down approach, albeit with input from stakeholders. Better Regulation agenda played a key role, ideologically and practically. At EU level, problem-solving tools involved analyses of intervention logic linking 1) problems, drivers and specific/operational objectives; 2) interdependence between objectives and consistency with EU policies; 3) revision of the Directive and sustainable growth, and; 4) amendments with problems and objectives. However, none of this was repeated at the MS level, raising the question whether EU level analysis would suffice for MS level (England). [D].

5.1.3. Enabling action

5.1.3.1. Issue framing

Support and buy-in was engendered by the authority of the official change-making organs and stakeholder consultations, at EU and MS levels. In England, the DCLG invited comments on its proposals for implementing the Directive, as applied to the Regulation. The consultation questions identified impacts to businesses and EIA practice, and opinions about proposed approaches to the transposition, albeit covering ONLY areas where MSs had discretion over how the changes are implemented (DCLG Department of Communities and Local Government 2017): receiving 72 responses from developers, local planning authorities, statutory consultees, representative organisations, and EIA consultants. The government considered the arguments in support of or against any proposal, rather than reaching a view based on the number of respondents for or against. Comments on the substantive purpose of environmental protection and how the changes would support it were missing in most responses: likely due to the scope of the consultation. Mostly, single EIA elements, e.g. screening were targeted for intervention with no robust analyses aggregating the cumulative and synergistic implications to the holistic EIA process, e.g. via systems thinking. [C].

5.1.3.2. Communication

DCLG provided online guidance with clear timelines, roles for stakeholders, including results of impact studies (environment, socio-economic), though limited to administrative costs and burdens. Other sources of information included 34 studies and reviews, a Business and Regulatory Impact Assessment, which considered how changes would impact on businesses. Government responses to the stakeholder views were publicly available. [A].

5.1.3.3. Creativity, open-mindedness, and problem-solving

Although the knowledge used came from a wide spectrum of stakeholder and qualitative experts-driven sources, robust understanding of cause-effect, including levels of error or uncertainty in the analysis feeding into the change-making process, was limited. There was little curiosity as to what previous PDCA exercises had achieved and how it could be enhanced or explicit analysis of how the external EIA environment, e.g. various ideologies (neoliberalism, environmentalism, populism) and actors (house builders, EA practitioners and scholars, media, politicians, government) affected change-making and its outcomes. Focus was on transposing the Directive’s objectives rather than addressing root causes to EIA’s ineffectiveness. Several reports and documents containing useful information for the exercise were used (e.g. annual number of EIAs and screenings carried out; costs and duration of the EIA procedures): often not quantifying the wider economic, social and environmental costs and benefits attributable to EIA. While these studies at the EU level did not fully differentiate analysis per MS, England did not undertake its own impact assessment to further inform its position. Perhaps, because the initial efforts to amend the Directive already benefitted from political and stakeholder input from MSs such as the UK. [C].

5.1.4. Fast prototyping

5.1.4.1. Issue framing and communication

Prototyping, widely used to test ideas, solutions, and enhance validation by evaluating a new design, its precision and usability (Vester 2007), was the weakest aspect in the case study. It helps manage requisite knowledge for a purpose, by avoiding the improper identification of the type and nature of knowledge needed; unclear goals; improper identification of the characteristics of knowledge; and poor understanding of the relationships between sources and users of knowledge and their associated enablers and resistors (Al-Ghassani et al. 2006). It can model or simulate several scenarios addressing relevant knowledge management issues. Prototyping can be simple to use and cost-effective, but challenging to apply, due to data or methodology problems caused by the complex nature of the holistic EIA process, or accommodating various interests of MSs, or the comfort of familiar approaches. Yet it would provide robust evidence to underpin the feasibility of and calibration of various change parameters (e.g. scoping, screening, costs, impacts), revealing in advance the likely cause-effect (Perdicoúlis et al. 2007) and outcomes of proposed interventions, especially in a complex process such as EIA (Perdicoúlis 2016). [E].

5.1.4.2. Creativity, open-mindedness, and problem-solving

Cases of good practice and scenario analysis were evident, often about an aspect of EIA procedure e.g. monitoring, but not the holistic EIA process. Although alternative changes and decisions were compared against each other e.g. through Multi Criteria Matrix Analyses, there was little evidence of comprehensive testing of the effectiveness or suitability of the whole proposed EIA. This could include process visualisation which crucially gives an overview of the current state of your process, making it easier to spot bottlenecks and opportunities for considerable improvement. Furthermore, process simulation and sensitivity analysis can help to quickly evaluate process improvement options or pathways within a virtual environment before carrying out a live rollout, possessing zero real-life risks. [E].

5.1.5. Feedback and evaluation

5.1.5.1. Issue framing

The main opportunity for feedback during the change-making process was provided by the consultation exercise. There were no pre-set outcomes, standards, or indicators for monitoring performance of the change-making approach; lack of explicit lessons from how past change-making exercises sleeved into EIA’s long-term evolution, and how this relationship could be benchmarked and enhanced. Nevertheless, the current EIA regulations require to be conducted a post-implementation review (PIR) every five years to understand their effect on business. [D].

5.1.5.2. Communication

The case study used a major consultation exercise for communicating feedback from stakeholders, which were publicly available online. [A].

5.1.5.3. Creativity, open-mindedness and problem-solving

This was largely limited to the England’s structuration of the changes to transpose the Directive. However, one wonders what an external independent council of NGOs, the public, or a citizen’s assembly including the youth, would have offered as proposed changes. While PDCA’s proper application is stage by stage, using feedback from the previous stage to inform the subsequent stage, this did not happen, perhaps because the PDCA works best in linear, e.g. factory rather than more complex processes like EIA. At a more theoretical level, it was unclear how transformative changes in EIA could be conceived and approached considering prevailing realities, e.g. neoliberalism, state capture, populism, post-truth and aggressive capitalism, which are known to generally thwart environmentalism (see Humphreys 2016; Onyango et al. 2019). [D].

5.1.6. Summary

The change-making exercise modal grade was C, with clear patterns of performance in changeology’s five steps, discernible (Table 4). Clarifying of purpose, Defining of project and Enabling action, were the best done; Feedback was poorly done, and Fast prototyping, worst done. These areas of poor performance are noteworthy because they generate insight that is crucial to influencing the four criteria (plausibility, doability, testability, and meaningfulness) that determine the quality of a theory of change, as explained in Cameron and Green’s (2024) Making Sense of Change Management.

Table 4. How the review areas (rows) and review categories (columns) were scored.

Changeology’s steps → Critical analysis steps	Issue framing	Communication	Creativity	Open mindedness	Problem-solving	Satisfied % (unsatisfied %)	Modal grade
Clarify purpose	A	A	C	C	C	100(0)	C
Define project	A	A	D	D	D	40(60)	D
Enable action	C	A	C	C	C	100(0)	C
Fast prototyping	E	E	E	E	E	0(100)	E
Feedback	D	A	D	D	D	20(80)	D
Satisfied%(unsat%)	60(40)	80(20)	40(60)	40(60)	40(60)
Modal grade	A	A	C&D	C&D	C&D		C&D

High grades were achieved in elements entailing procedural aspects (e.g. statements clarifying purpose or describing nature and details of project), while elements requiring deeper analytical power (e.g. prototyping, cause-effect or distilling lessons from past change-making) performed relatively poorly. Within the review criteria, the best performance was in Communication and Issue-framing, while Creativity, Problem-solving and Open-mindedness, the worst done (unsatisfactory), revealing areas of significant scope for robust research, innovativeness, ambition, and thinking out of the box. Most changes were about implementation and enforcement – seldom was there a deeper interrogation as to the nature and structure of EIA, giving the impression it was assumed to be fit-for-purpose. Thus, key arena for generating a spectrum of competing ideas upon which deeper reflection for solutions can occur, supported by empirical enterprise that tests the assumptions underpinning the change-making, and; integrates societal values and attitudes. Higher scores in our assessment framework would mean that changeology’s factors have been more effectively followed, and that more empirical analyses have been undertaken and guided the change-making enterprise. The outcome would be a change-making approach that is better fit-for-purpose; following more scientifically derived knowledge while engaging with questions around EA’s raison d’etre, or normative, substantive or transactive dimensions, which according to Banhalmi-Zakar et al. (2018), have fundamentally not changed since EIA’s inception.

6. Discussion

Our case study revealed a change-making process that is complex, layered, and inter-dependent between supra national and national jurisdictions – driven by pragmatic considerations and narratives, e.g. streamlining and supporting business, but not adequately guided by empirically justified claims or supported by assurance of cause and effect. Firstly, at EU level, MSs played a political and strategic role via negotiations to set the ambition and scope for change. Here, interests within the co-decision procedure can change between and within MSs, with debates and agreements becoming subject to different actors and rationale. Secondly, the EU’s bureaucracy and institutions co-generated amendments to the Directive which once adopted set obligations to MSs. Thirdly, via transposition, MSs like the UK focused on change that was constrained in scope to deliver the least deviation from the amended Directive. Within this context, our findings highlighted several areas in EIA change-making (e.g. assumptions about PDCA, Better Regulation’s effectiveness, and burden-reducing objectives and narratives) and showed how their representations afflicted the process and outcomes. Overall, missing in all this were three key tenets typically applied to change-making in other sectors (von Bertalanffy 1968; Deming 1986; Vester 2007) and change-making models (Langley et al. 2009; Atkinson et al. 2015; Serrat 2017), i.e.: competent understanding of the nature and behaviour of the process at the heart of change-making, and; tested and verified methods for effecting desired change.

Consequently, to avoid maladjustment (Gazzola 2022) or unintended pitfalls, a changeology approach can steer change-making via empirically informed strategies; instead of being unduly driven by assumptions and interests which cannot be shown to equate to delivering EA’s normative goals, e.g. environmental protection. Thus, be a bulwark against unjustified dilution of radical offers to reform EA (see Fonseca et al. 2017), promoting evidence-informed and evidence-driven change-making practice. Crucially, concerns about EA (in)ability to change and be fit-for-purpose (Banhalmi-Zakar et al. 2018; Bice and Fischer 2020); whilst pursuing the disparate proposed changes to EA (Vanclay 2015; Pope et al. 2018; Chanchitpricha and Bond 2020; Bond and Dusik 2020; Castree et al. 2021; Kamijo 2022; Sinclair et al. 2022; Kørnøv and Lyhne 2023), can be scientifically tested for their efficacy, while assuring that the applied change-making methods are appropriate. Thus, regardless of the objective(s) for change, changeology can guide the successful delivery of change, thereby addressing the problem and knowledge gap that motivated this study (section 1); i.e. lack of an epistemology to guide change-making in EA.

This paper proposes that changeology can enhance change-making and the potential for evolution of EA towards fitness-for-purpose, as part of addressing a complex problem of persistent ineffectiveness in EA despite many efforts at change-making. By asking key questions around change-making, from temperament, e.g. ambition in pursuing what EA is maximally capable of; to strategy, e.g., generating a framework for engineering the changes despite the headwinds that constrain environmental protection, e.g. neoliberal hegemony (Onyango et al. 2019). Most significantly, supporting an epistemology of change-making, which will ensure that the change-making approach is based on an empirical framework (Table 5), to inform the journey (process) and destination (fit-for-purpose EIA) and make EIA aligned to the future expectations.

Table 5. How changeology can enhance change-making in EA (competent understanding of the nature of EA process, sound methods for effecting desired change), focusing on scientific methods and the evidence base.

Changeology’s steps	Contribution examples
Clarifying purpose	Approaches e.g. EPB & practical research to distil desired future conditions, backed by sound and balanced evidence from literature and stakeholders.
Defining the project	Systems thinking techniques (Modelling, Sensitivity analysis) can help establish pivotal actions to bring desired changes in a complex process; appropriate techniques for quality assurance identified.
Enabling action	Complex nature of EA process/system understood, including key factors and actors at play and how they dynamically interact and influence EA outcomes; Ideologies, roles, fears and needs of all stakeholders captured; Sound data collection and analysis applied; Efficaciousness and effectiveness of approach demonstrated empirically; Lessons from past change-making exercises integrated e.g. PDCA evaluated; Appropriate change model, data needs and techniques explored.
Fast prototyping	Ex ante potential success and impact of change, via models, simulations, sensitivity analysis, allowing for reflexive learning and improvisation.
Feedback and evaluation	Two-way avenues to quality assurance about procedures and stakeholders captured and balanced appropriately; performance of change-making process monitored and evaluated throughout.

This will require changes to how we bridge different kinds of knowledge and systems of knowledge production (e.g. how we balance different stakeholder perspectives), including episteme and phronesis, to which changeology can be tasked. While the former refers to systems of understanding, i.e. knowledge, the latter is a type of wisdom or intelligence relevant to practical action in particular situations, implying both good judgment and excellence of character and habits (see McEvilley 2012). The aim is to adopt more empirical investigations of the theories, vagaries and boundaries of change-making: engage with questions around EA’s raison d’etre, or normative, procedural, substantive or transactive dimensions, which have fundamentally not changed since EA’s inception. At the EU level, changeology could help determine the process of change-making at a framework and system level when far-reaching strategic options are still open. At MS level, changeology could help to explore and demonstrate cause-effect at EIA process level, whilst accounting for contextual factors, e.g. interests and roles of various actors. As copious literature exists on EA effectiveness and its future directions, sifting through the evidence may be challenging. However, this can be addressed within changeology, via approaches like evidence-based assessment (EBA) or evidence-based practice (EBP), underpinned by meta-analysis involving statistical analysis that combines results from multiple studies, which can be considered to increase inferential or statistical power over individual studies (Greenland and O’ Rourke 2008).

As metascience or meta-research, EBP uses research and theory to guide the selection of constructs (methods and measures) for an assessment process (Walker et al. 2008). Thus, how research is done and where improvements can be made; an approach that can be turned towards enhancing the practice and validity of claims for change-making in EA. Results from EBP can be generalised to a larger population; precision and accuracy of estimates can be improved, increasing the statistical power to detect an effect; inconsistency of results across studies can be quantified and analysed; hypothesis testing can be applied; moderators can be included to explain variation between studies and the presence of publication bias can be investigated. This can benefit change-making by guarding against, e.g. ‘policy-based evidence-making’, the converse of ‘evidence-based policy-making’ which refers to the commissioning of research to support a policy which has already been decided upon (e.g. reducing cost-burdens in EIA is a necessary priority).

Following the UK’s withdrawal from the EU, the UK Government decided to replace the EU-based EA system with a domestic framework emphasising speeding up project development via a ‘reformed and improved EA’. This would see traditional EA reports replaced with Environmental Outcome Reports (EoRs) to address the outstanding issues with the current system of EA: e.g. reduce the number of borderline cases subject to legal challenge which results from unclear criteria, and reduction in costs and delays. While the government’s narrative was that EoRs align with delivery of an improved system for protecting its environment, the proposed changes are not yet supported by an evidentiary basis (Fischer 2022a). As EoRs are yet to be formulated in detail changeology can help England consider its key issues about change-making within a more scientific framework. If not carefully done, we fear that these new changes via EoRs may replicate the same failures that have underpinned EA to date. Arguably, without the EU level of constraints, England’s EIA change-making process can have a wider scope for changeology to re-envision its approach – based on England’s understanding of what its purpose for changing its EIA regulations should be. Perhaps, break away from the EU’s tradition of change-making in EIA (Reid 2021). Changeology should be viewed as more than informing one-time change-making but as a framework of well-studied practice for changing (or improving) EA processes in the long term (Figure 3).

Figure 3. Role of changeology in informing change-making to deliver fit-for-purpose EA, from the start (EA¹) to the long term (EAⁿ), following cumulative effects of several iterations. EAⁿ can be revolutionary when compared to EA⁰ if the intermittent change-making have been consistently pursuing fitness-for-purpose.

7. Conclusion and recommendations

This paper has scratched the surface of a complex problem and highlighted issues around change-making which are amenable to the scientific method. Based on a case study, where one jurisdiction (EU) sets the changes required by another one (MS), it identified a lack of robust evidence-based approaches to inform and support the change-making process. Our findings pointed to deficit in the acquisition and application of sound knowledge: as the knowledge applied in our case study was largely drawn from qualitative and experts-driven sources, often using multi-criteria analysis, with intuitive and well-intentioned aspirations but without robust empirical insight to support decision-making. Pragmatism and expediency of ‘at the moment’ (harmonisation and costs to business of EA process) and ‘partial knowledge’ (assumed understanding of holistic EIA process behaviour) was at the heart of the change-making. For example, insight on the role of various actors, including barriers and opportunities from them, was not empirically adduced to inform the balancing between losers and winners from the changes proposed. Truisms like ‘streamline-driven’ regulatory reforms in EIA or the effectiveness of Better Regulation approach to enhance EA, also requires empirical examination. Thus, as change-making poses challenges and risks, and requires careful attention to make it successful whilst avoiding pitfalls, this has not sufficiently occurred in our case study.

The findings strongly harken to caveats that assumptions in EA need to be rigorously tested and cause–effect, e.g. effectiveness of PDCA in EIA change-making, and other narratives leading to the changes made in the Regulations, be ascertained, empirically. While PDCA offered a theoretical and procedural framework for the change-making process, evaluation of its performance would generate useful insight for its enhancement. This can target more objective selection of constructs, methods and measures, shifting the change-making from tradition and intuition to approaches firmly grounded in scientific approaches. This could help draw valid distinctions between failures rooted in the change-making process, e.g. PDCA, and those rooted in the EIA practice, structure or its context e.g. within the Directive, or predominant government ideology. This could cover analyses of the framing of policy evidence to show how the evidence supports the proposed changes, the policies of change-making, and the framing of policy implementation to show how the change-making implementation processes are steeped in empirical evidence.

Following reflective analysis driven by data from practice (case study) and informed by lessons from theory (changeology) and heuristics (change-making models), we conclude that a changeology approach can help establish an epistemology of change-making to inform the journey (process) and destination (fit-for-purpose EA) for a future EA process or system. As a pilot study, our findings are tentative and prescriptive, leaving room for testing and validating the concept of changeology in EA across several case studies and contexts, to establish the conditions under which it is feasible. Limitations in our study are worth noting. Firstly, we relied on secondary data gleaned from published documents which alone may not provide a complete coverage of the issues at play during the change-making in our case study. As the evidence base in this paper was limited to the data collected, studies drawing on stakeholders’ (involved in the change-making exercise) perspectives are required. Secondly, quantitative methods can supplement our support for changeology, by testing the convergence between process improvement (change-making) and EA effectiveness (fitness-for-purpose), as a productive tension of two still incongruent movements. For future research, we recommend exploring if current EA is indeed capable of meaningful change or must it be re-imagined anew; and how changeology can help internalise a commitment to learning from past change-making experiences in systematic ways, to deal with the unpredictability of decision processes.

Disclosure statement

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