From cleaner production to sustainable development: the role of academia

lable at ScienceDirect

Journal of Cleaner Production xxx (2014) 1e14

Contents lists avai

Journal of Cleaner Production

journal homepage: www.elsevier .com/locate/ jc lepro

From cleaner production to sustainable development: the role ofacademia

Nasrin R. Khalili a,*, Susanna Duecker a, Weslynne Ashton a, Francisco Chavez b

a Stuart School of Business, Illinois Institute of Technology, 10 W. 35th Street, Chicago, IL 60616, USAbUniversidad Centro Americana “José Simeón Cañas” (UCA), Autopista Sur, San Salvador, El Salvador

a r t i c l e i n f o

Article history:Received 27 September 2013Received in revised form2 January 2014Accepted 29 January 2014Available online xxx

Keywords:Cleaner ProductionEducationSustainable developmentAcademic programsLatin AmericaChinaU.S.A

Abbreviations: PC, pollution control; CP, cleanerdevelopment; MSMEs, micro, small and medium enSustainable Development; CPIAP-SD, cleaner productifor sustainable development; UN, United Nation;America; RM, Resource Management; SEDP, Socio-Prosperity; HCD, Human Capital Development;governance.* Corresponding author. Tel.: þ1 312 520 1768.

E-mail addresses: [email protected], nasrin.rasa

http://dx.doi.org/10.1016/j.jclepro.2014.01.0990959-6526/� 2014 Published by Elsevier Ltd.

Please cite this article in press as: Khalili, NCleaner Production (2014), http://dx.doi.org

a b s t r a c t

Cleaner Production (CP) strategies are fundamentally concerned with operations, environmental sus-tainability and maximization of waste reduction, recycling, and reuse at the enterprise level, and are thusmicroeconomic in scope. Sustainable development (SD), however, involves the design of integratedapproaches that are capable of addressing environmental sustainability and waste while ensuring socialand economic prosperity at the national or even global level implying a macroeconomic scope. Due to itsphilosophy, broad scope and long-term horizons, sustainable development necessitates capacity buildingvia advancement of sustainable societal patterns and the creation of a new set of visions, paradigms,policies, methodological tools and applicable procedures. The first and foremost step on this path is thedevelopment of human capital required to make such a transition. This paper proposes the application ofa methodology via which leaders in higher education could assess the necessity and the urgency fordesigning training programs that could assist with developing human capital needed to support SD. Themethodology evaluates the conditions and constraints that could control the effectiveness and ease ofimplementation of such programs. At its core, the proposed methodology utilizes expert judgment toassess importance of including CP and SD indicators listed in the questionnaire on the proposed aca-demic programs. During a pilot study which was conducted in the fall of 2013 at selected universities inthe USA, Latin America, and China, experts evaluated a series of proposed CP-infused academic programsaccording to a matrix consisting of SD indicators, and under consideration of the norms, culture, politicalsystems, regulations, resource availability, and local, regional and global economic development goalsand objectives. Results of data analysis in the pilot study suggested that inclusion of the resourcemanagement (RM) topics in designing academic programs is the most preferred approach in all threedifferent regions, followed by development of programs that could cover topics in areas of human capitaldevelopment (HCD), human system designs (HSD) and sustainable economic development and pros-perity (SEDP). Quantitative analysis of the data indicated existence of two clusters of preferences for CPeSD criteria: one for in the Americas (including Latin America) and one for China.

� 2014 Published by Elsevier Ltd.

1. Introduction

Environmental issues associated with developmental activitiesstarted to be of economic concern from the 1960s onward. Before

production; SD, sustainableterprises; ESD, Education foron infused academic programUS, United States; LA, LatinEconomic Development andHSG, human systems and

[email protected] (N.R. Khalili).

.R., et al., From cleaner prod/10.1016/j.jclepro.2014.01.099

then, waste, and wastemanagement topics, if addressed at all, wereaddressed on an ad hoc basis. Following formation of the USEnvironmental Protection Agency (EPA) in the 1970s, a wide rangeof environmental laws, regulations and guidelines were developedto manage waste in a guided, standardized and systematic fashion.Most if not all environmental policies and regulations of this erawere designed as “command and control” strategies, utilizingpollution control (PC) and a conventional “end-of-pipe” abatementapproach. Cleaner Production (CP), an approach to revising pro-cesses, management, and housekeeping practices through thebusiness cycle with an emphasis on reducingwaste and pollution atthe source was proposed in the 1980s. In contrast to the PCapproach promulgated in the 1970s, CP focused on developing

uction to sustainable development: the role of academia, Journal of

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N.R. Khalili et al. / Journal of Cleaner Production xxx (2014) 1e142

strategies for pollution prevention, waste minimization, and recy-cling and reuse; an approach that is congruent with leanermanufacturing (USEPA, 2013). The main objective of the leanerproduction strategies has been to shift the focus of waste man-agement from control to prevention as a voluntary approach tocomplement, when possible, pollution control practices.

The regulations, policies and guidelines for pollution control andcleaner production, respectively, aimed at managing environ-mental externalities of industrial systems. While focused on envi-ronmental sustainability, both PC and CP aim at managingenvironmental and ecological risks associated with a wide range ofindustrial and developmental activities. Although both PC and CPgrew out of a macroeconomic agenda, their outcomes have beenmeasured mainly at the enterprise level. This has obvious benefits:contributing towards macroeconomic goals, per se, is usually nothigh on enterprises’ agendas. Improving their profit margin or theircompetitive position, however, is. Since macroeconomic objectivescannot be achieved without enterprises’ contribution towardsmeeting them, it is critical that enterprise and macroeconomicobjectives are aligned.

In theory, this alignment is achieved through signals includingraw material and energy prices and regulation. In practice, thisalignment is often flawed because signals do not sufficiently ac-count for economic, environmental and social risks, and regulationsto protect social and environmental interests are adopted slowly.Upon announcing the urgent need for sustainability by Brundtlandand the United Nations Commission in 1987, and the formalintroduction of a paradigm for sustainability in the 1990s, manynations and institutions have been trying to define the concept ofthe “sustainability” and its relevance to their operations, values,and functionality. The concept of sustainability is still evolving aswe learnmore about its multifaceted, complex nature. Most studieshave focused on interdisciplinary theoretical issues and empiricalunderstanding of economic aspects, ecological conditions and so-cial values of sustainability (Economic-Ecology-Social Nexus)(Khalili, 2011a).

Sustainability, by definition, formulates a relationship betweendynamic human economic systems and slower changing ecologicalsystems, in which human life can continue indefinitely, humanindividuals can flourish, and human cultures can develop, whilediversity, complexity, and function of the ecological life supportsystem are protected (Norton, 1992). Sustainability is also an eco-nomic state where the demands placed upon the environment andnatural resources by people and commerce can be met withoutreducing the capacity of the environment to provide for futuregenerations (Gladwin et al., 1995).

A more elaborate analysis of the cleaner production and sus-tainability topics which this paper is concernedwith is presented inthe following sections.

1.1. Cleaner production

Cleaner production is defined as an “integrated preventativeenvironmental strategy” for improved resource efficiency, mini-mization of risks and environmental impact, and reduced wasteand costs in an organization’s operations (UNEP, 2013). It has beenpromoted since the 1980s as a strategy to enable businesses tominimize waste and improve their environmental performancewhile reaping financial benefits from those activities. In NorthAmerica and Europe, CP has enabled companies to reduce costs andimprove efficiency in their operations. It also opened the door formore formal environmental management systems and strategicinvestments across a variety of business functions, leading tohigher productivity, revenues and market share (Hart, 1995; Porterand van der Linde, 1995). It has become the most widely adopted of

Please cite this article in press as: Khalili, N.R., et al., From cleaner prodCleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.099

various environmental management practices, and there has beenmuch research and evidence for a positive correlation betweencleaner production and improved business performance (Hart andDowell, 2011). Hart and Dowell (2011) also note that broader sus-tainable development strategies, including addressing marketneeds at the base of the pyramid and developing clean technolo-gies, have not been as widely adopted by companies because theypresent a greater challenge and less certain returns. Thus, from abusiness perspective, there is a gap between the shorter term,microeconomic focused cleaner production strategies and thoseaimed at addressing macroeconomic sustainability.

For nearly two decades, United Nations-sponsored NationalCleaner Production Centers (NCPCs) have promoted CP promotionin many developing regions. While larger enterprises have had fairsuccess, smaller enterprises face significant hurdles to adopting CP.In general, micro, small and medium enterprises (MSMEs) espe-cially face significant hurdles to adopting CP as those are con-strained by limited professional management skills and systemsincluding: concentrated decision-making by owners, limited skilledhuman capital, non-involvement of workers, poor record keepingand lack of in-house monitoring and maintenance systems, andunstable finances and sources of funding (Ashton et al., 2002).Additionally, while the concept is often sold as a “winewin”, it isnot universally so. There are diverse activities under the CP um-brella, some of which require higher levels of investment andlonger payback periods, and may not have as clear a win (King andLenox, 2002; Sarkis and Dijkshoorn, 2007; Zeng et al., 2010). Thishelps to explain why the concept has not become as widelyaccepted and practiced as has been expected. Thus, it is importantto consider how these potential barriers limit adoption and may beovercome through improved education and awareness amongstboth technical professionals and the business community.

1.2. Sustainable development

The widespread rise of interest in and support for the concept ofsustainable development could signify an important shift in therelationship of humanity with nature and in inter-human relations.SD’s emphasis on mutual dependence stands in contrast to thedominant outlook of the last couple of hundred years (particularlyin developed nations), which was based on the separation of theenvironment from socio-economic issues. The concept of sustain-able development is partially a result of growing awareness of theglobal links between mounting environmental problems, socio-economic issues related to poverty and inequality, and concernsabout a healthy future for humanity (Hopwood et al., 2005a, b).

The Sustainable development (SD) paradigm, which was intro-duced in a formal fashion in the 1990s (Khalili, 2011b) targetsenvironmental, social, ecological and economic sustainabilitythrough a cohesive framework that treats them as interconnectedgoals. SD requires the consideration of a much more extensive andintegrated set of objectives while monitoring the outcome ofdevelopmental activities via a wide range of indicators. Conse-quently, outcomes have to bemeasured inmultiple dimensions andat the macroeconomic level. Alignment between enterprise ob-jectives and regional, national and global objectives can be ach-ieved through signals such as raw material prices, energy prices,and regulations and policy that mitigate risk. The alignment of themicro- and macroeconomic objectives is expected to improve asSustainable Development (SD) is gaining wider acceptance as aparadigm for macroeconomic policy.

As outlined in the Rio Declaration and Agenda 21, sustainabledevelopment has become the overarching goal of the internationalcommunity, and influences the development of national strategiesfor sustainable development. Despite all the efforts, however,


N.R. Khalili et al. / Journal of Cleaner Production xxx (2014) 1e14 3

concerns over global economic and environmental developmentsprevail in many countries. These concerns have been intensified byrecent prolonged global energy, food and financial crises, (UNDESA,2011).

Nevertheless, many experts remain optimistic that a sustainablefuture is a possibility: Most recently, the “Great Transition” sce-nario, requiring a suite of strategic and a value change was pro-posed as an effort for turning toward a civilization of enhancedhuman well-being and environmental resilience (Raskin et al.,2010).

The global movement toward a balanced and inclusive greeneconomy in support of SD calls for support of environmental pol-icies, greening economics and measuring sustainable developmentefforts and initiatives. Emphasizing the need to address globalproblems such as climate change, ozone depletion, tropical defor-estation, and resource losses in the developing world, the greeneconomies approach deals with current challenges and deliverseconomic development opportunities with multiple benefits for allnations (Rioþ20) (UNDESA, 2012, and UNEP, 2012).

2. Cleaner production for sustainable development

Due to its philosophy, broad scope and long-term horizons,sustainable development necessitates capacity building viaadvancement of sustainable societal patterns and the creation of anew set of visions, paradigms, policies, methodological tools andapplicable procedures. The first and foremost step on this path isthe development of human capital required to make such atransition.

The role of CP in the sustainable development of modern soci-eties has been discussed over the last two decades. Examplesinclude a study conducted by Kjeheim in 2005 that suggested thatCP as a stand-alone option will not create a sustainable society, butexpanding the concept is believed to be an important step in theright direction, provided that sufficient funding is available over anextended period. Proposed modifications include encouragingadaptation of CP in the many very small enterprises, use of CP intotal quality control strategies, and inclusion of CP in the design ofenvironmental management systems (Kjaeheim, 2005).

As previously discussed, CP aims at protecting both economicgrowth and environmental values, specifically with regards to theindustrial sector; however, due to the magnitude and criticality ofthe changes required by CP, implementation is often challengingand can follow a steep learning curve. To address this issue, UNEPhas suggested that cleaner production centers and research/aca-demic institutes, along with industry associations and consul-tancies, should weigh in and help with CP design, but many of theseorganizations lack the resources to develop comprehensive trainingregimes and materials (UNEP, 2007).

Increased CP training in industry (supply chain), government,the private and public sectors, and academia is a priority on the SDagenda due to the key role these institutions play in addressingglobalized nature of environmental and social problems and chal-lenges. Sustainable supply chain management, in particular, isgaining momentum as sustainability issues do not stop at the gatesof single companies and have to be considered along the supplychain of the entities across, which related material and informationflows occur (Seuring et al., 2008).

The complexity of the process involved with making necessarychanges to CP strategy to support SD often prevents academia, andindustry and governmental leaders from proceeding beyond thestage of grappling with the magnitude of the challenges they face.The urgency of adopting the sustainability paradigm, however,makes it obvious that nations must work effectively on developing,testing and implementing multi-disciplinary strategies with the


promise to make progress toward a sustainable society (Bonillaet al., 2010). Such defined urgency motivated design of programssuch as one presented in this paper.

We believe that while cleaner production was designed toaddress environmental sustainability only, it has the potential toaffect related social, economic and prosperity indicators, measuredat the macroeconomic level, with expansion of the traditional CPmodel. CP design for sustainable development (CPeSD) requires anexpansion of the traditional CP model that incorporates a morecomprehensive understanding of sustainability as a multidimen-sional objective, which is in line with the view that environmental,social and economic sustainability are interrelated. The CPeSDstrategy must clearly demonstrate that the CP concept can beexpanded to more directly address the needs of developing coun-tries as well as the needs of developed nations in a green economy.

3. Education for Sustainable Development (ESD)

Colleges and universities in the United States and developednations particularly, are increasingly being viewed as engines ofcreating human capital needed to support development of localeconomies. This trend has been driven by the economic successstories of places such as Silicon Valley and the Route 128 corridoraround Boston, as well as the more general recognition of thetransition now underway towards a more knowledge-basedeconomy (Abel and Dietz, 2011).

The link between development of human capital and academiais an obvious one, and since the perspective of academia is the mostnatural to the authors of this paper, we proceed this section bydeveloping a better understanding of the role of academia in pro-moting sustainable development. We believe that design, devel-opment, and successful integration of cleaner production strategiesfor sustainable development, rest on the establishment of humancapital, namely professionals who possess adequate training andknowledge in CPeSD specific domains.

According to Wikipedia definition, human capital is the stock ofcompetencies, knowledge, social and personality attributes,including creativity, cognitive abilities, embodied in the ability toperform labor so as to produce economic values (Simkovic, 2013).Hershberg, 1996, defined human capital to be about educating,developing skill levels and problem-solving abilities that canenable an individual to be a productive worker in the globaleconomy of the twenty-first century. He questions if the need forhuman capital development should be addressed since it canimpact or shift direction of the global economic competition, or as itcan significantly impact achieving regional development goals bypreparing youth with the skills required by the jobs of the new lowcarbon global economy? (Hershberg, 1996).

Not surprisingly, the education community has been divided onhow to respond to the emergence of education for sustainability.Some appear quite comfortable with the term and seek to bothintroduce this line of education to the curriculum and use it toaddress issues under-represented by traditional environmental ed-ucation. Others have been expressing concerns about globalizationof education for sustainability. Education for sustainability has alsobeen used to accommodate global political agenda (Wals, andJickling, 2002). UNESCO, the lead agency for the UN decade of edu-cation for sustainable development has clearly stated that Educationfor Sustainable Development (ESD) requires far-reaching changes inthe way education is often practiced today. They also have empha-sized on the need for shifting the focus of education toward allowinghuman being to acquire the knowledge, skills, attitudes and valuesnecessary to shape a sustainable future (UNESCO, 2005e2014).

Although inclusion of sustainability specific training of theworkforce has been proposed since early 1990s (Boyle, 1999;



UNESCO, 2012a,b), a few academic programs have been addressingthose in an integrated fashion. In Australia, despite the apparentwidespread support for the concept of student education in sus-tainability, there has been limited indications of their imple-mentations, although Australian institutions of higher educationhave signed commitments to pursue sustainability education(Thomas, 2004). Fenner et al., 2005, examined the latest stage in aprocess of change aimed at introducing concepts of sustainabledevelopment into the activities of the Department of Engineering atCambridge University, UK. In this study, researchers aimed atdefining skills which future engineers require and vehicles forchange at both undergraduate and postgraduate levels. The focushas been to define the paradigms and pedagogy of teaching sus-tainable development issues to engineers, and define barriers suchefforts could encounter (Fenner et al., 2005). In 2006, Sterling andThomas, suggested a model of staged learning and change linkinginstitutional change with deepening student experience based oncurrent work at RMIT and the University of Plymouth. Between theundesirable extremes of curriculum prescription and emergence,the authors suggest some indicative schemas that might help ac-ademics design curricula for ESD (Sterling and Thomas, 2006).

Paul E. Murray and Sheran A. Murray in their 2007 paper sug-gested that open-ended enquiry-based learning techniques areuseful for promoting sustainability values within educational pro-grams. Their work fundamentally concerned with the design ofworkshops to provide learners on “career-based” programs withopportunities to reflect upon their values within the context ofsustainability (Murray and Murray, 2007).

The policy and practice framework for education for sustain-ability has developed considerably and in many countries. As aresult a range of government policies have been considered tosupport formal education in this area from schools to higher edu-cation. According to Wade, 2008, and as described by UNESCOreport in 2005, education is the prime lever for social change and isthe main driver for enabling people to foresee, face up to and solvethe problems that threaten life on our planet (Wade, 2008).

Under the direction of Agenda 21, the work of the UNESCOEducating for a Sustainable Future program in the 1990s, thedeclaration of a UN Decade of Education for Sustainable Develop-ment (2005e2014), and the movement to ‘‘green universities,’’ thefocus of environmental education has broadened to encompass thewider agenda of education for sustainable development. Thechallenge has been, among others, to define how much changewould be required in university curricula to accommodate educa-tion supporting sustainable development? (Thomas, 2009).

More or less, recent studies suggest that despite all efforts topromote sustainability education, we have not been as successful aswe wished for. To address this significant problem, Thomas et al.,2012, identified several key inhibitors; a lack of understandingand training for academics; contested nature of sustainability;already crowded curriculum; time and resources required for staffto developed knowledge and skills; lack of institutional drivers; anddisciplinary cultures and assumptions (Thomas et al., 2012). Mat-thias, 2013, has also addressed this issue by identifying threedistinctive patterns for introducing topics of sustainability in thecurriculum. With a unique set of influencing factors those includedstudent-led change from informal to formal learning; includingsustainability as a concern in campus operation; and brandinguniversity via sustainability as a unique selling-point (Barth, 2013).

With the challenge of sustainable development as considerableas ever, it has become evident that current technological advances,legislation and policy frameworks are not enough to meet sus-tainable development goals and objectives, unless those areaccompanied by changes inmind-sets, values and lifestyles, and thestrengthening of people’s capacities to bring about change.


The UNESCO 2012 report which followed the first report in 2009,highlighted trends in education and learning around the globe thatshow the potential and the challenges of ESD at all levels of edu-cation and in other less formal learning contexts (e.g. communitiesand businesses) (UNESCO, 2012a). Pedagogies associated with ESDmust be formulated to stimulate curiosities, ability to analyze, thinkcritically and make decisions. Such pedagogies move from teacher-centered to student-centered lessons and from rote memorizationto participatory learning. The four teaching techniques: simula-tions, class discussions, issue analysis, and storytelling. Each tech-nique stimulates different learning processes (UNESCO, 2012b).

Today, a major recognized institutional framework for change inall educational levels is the UNESCO led Decade of Education forSustainable Development (DESD). This Decade, which began in2005, has almost reached its mid-term point, and though thou-sands of DESD-related actions have occurred throughout the world,it has not yet influenced, in a significant manner, educational pro-grams worldwide (Ferrer-Balas et al., 2010).

This paper tests how academicians, across the globe, can assessthe requirements for the development and implementation ofcustomized, well-balanced and effective programs capable ofdeveloping human capital needed to support sustainable devel-opment from a set of standard indicators.

4. The goals and objectives

The primary goal of this study is to assist with the developmentof human capital needed to support SD. More specifically, this studyattempts to understand how academic programs infused withcleaner production concepts and theories can be advanced, underdifferent constraints, to support sustainable development at bothdeveloping and developed nations. The objective of the study is todefine methodologies for:

� Integrating the concept of CPeSD in the fabric of higher edu-cation, namely colleges, universities and institutions.

� Creating educational modules that can result in the develop-ment and implementation of CP strategies in line with national,regional and global sustainable development goals, objectives,and initiatives.

� Understanding the competing interests and constraints in thedesign and development of CPeSD academic programs that arespecific to local and regional development goals.

5. Methodological approach

Data collection and analysis method was designed according tothe project purpose to specify training programs needed at highereducation institutions to develop human capital that can drivesustainable development. Human capital, in this context, is definedas individuals who understand the concepts of sustainable devel-opment, are equipped with knowledge, skills, tools, and techniquesneeded to design and implement CPeSD initiatives that couldsupport micro-level initiatives, while advancing macro-level equi-table and sustainable societies.

The intention of themethodological approach, accordingly, was toinstigate a transition in academic programs from CP as a standalonetopic towards its integration into the SD paradigmwith the objectiveof creating a sustainable and dynamic societal framework. To achievethis, we developed a questionnaire by which we could modeleducational programs for sustainable development according to theexperience, knowledge, and expertise of academic leaders (experts)in a variety of disciplines (sciences, engineering, and management).Also accounted for in this study are considerations of the local, na-tional, regional, andglobal priorities.As indicated in the result section,


CP-Infudsed Academic Programs for SD(CPIAP-SD)

Resource Management (RM

RM1Eco-Region Protection

RM2Climate Change/ Carbon and Energy Management

RM3Water Management/

Conservation

RM4Earth-Land Management

RM5Use of Critical/ Non Renewable Material

Socio-Economic Development and Prosperity

(SEDP)

SEDP1Industrial Growth/ GDP per capita/ Net National

Income growth

SEDP2Household Earning and

Saving

SDEP3Energy Use and/or

Intensity

SEDP4Global Partnership

SDEP5Rate and Dispersity of

Job Creation

Human Capital Development

(HCD

HCD1Health Risk Analysis

(Assessment/Management

HCD2Employment

Development/Equality (gender-age-race)

HCD3Access to Education

HECD4Access to Labor Market

Human System and Governance

(HSG

HSG1Environmental/Financial

Regulations/Policies

HSG2Green Economic

Development Policies

HSG3Global

Cooperation/Partnership Initiatives

HSG4Financial Investment in

Green Economy

Fig. 1. Criteria and indicators used in development of the questionnaire (please see full questionnaire provided in the Appendix I).


participatingexpertswere identified in advance inorder tomake surethey could properly represent regional educational systems.

5.1. Selection criteria and indicators for sustainable development

As described, the main components of the study were devel-opment of a questionnaire to solicit expert opinions on theimportance of including CPeSD training material (defined bycriteria and indicators) in different types of academic programs.The questionnaire composed of training criteria and associatedindicators (topics) that could reflect a broad scope of sustainabledevelopment paradigm. The types of the criteria and indicatorsselected were based on industry experience at both national andinternational scales and those identified by UN and clean produc-tion centers in Latin America and China.

More specifically, we included indicators that could be used tomeasure sustainable development in economy-wide key sectors(agriculture, energy, manufacturing, transportation, waste, andwater). Other indicators included were aggregate indicators ofprogress and wellbeing (poverty reduction), decoupling indicators(reduce interdependence), growth (water, energy, land use andfootprints), and indicators associated with sector investment ($),employment, and output ($) (UN Sustainable Development NASASustainable Development Indicators, 2013, and NASA, 2013). Fig. 1demonstrates how selected criteria and their indicators arerelated to each other, and are in transition.

5.2. Participants

Participants in this study were identified through authors’network and according to their interest, background, and different


levels of involvement in development or assessment of academicprograms. The academic background of the participants in thisstudy (the experts) varied from engineering, to business andmanagement science. Almost all participants have had exposureto the concepts of sustainable development and cleaner produc-tion (pollution prevention). Participants were supplied by twodocuments: Guideline on how to complete questionnaire, and“the questionnaire” itself which was provided as an Excelspreadsheet.

Factors influencing selection of the participating countries/ex-perts included, among others, accessibility to the experts, experts’willingness to participate, countries economic development needsand concerns, current approaches to managing the impact of theirindustrial growth on the socio-economic systems, and their will-ingness to develop human capital needed to support creation ofnew green economies.

5.3. The questionnaire

In addition to collecting demographic data on participating ex-perts (academicians who participated in the study) which includednationality, age, gender, disciplines within which they practice,their terminal degree, level of exposure and involvement withsustainability education and/or practices and work focus, thequestionnaire included twomain tables to be completed, consistingof five types of academic programs, their associated courses, andfour sustainable development criteria composed of 4 or 5 CPeSDindicators. Table 1 was designed to collect data on the importanceof including CPeSD criteria ” Resource Management (RM), Socio-Economic Development and Prosperity (SEDP), Human CapitalDevelopment (HCD), Human System and Governance (HSG)” and


Table 1An overview of participants, demographic data.

Country Total Gender Background/expertise Exposure to CPeSD disciplines

Male Female Engineering Business/policy Hybrida Low Mid High

USA 7 3 4 3 1 3 1 2 4LA 10 8 2 7 2 1 2 2 6China 8 5 3 2 4 2 3 3 2Total 25 16 9 12 7 6 7 6 12

a Engineering/management/business/economics.


their respective indicators in academic programs. Indicators foreach criterion were then selected to address the challenges ofpursuing sustainability. Those, among others, included parametersof resource management, of socio-economic development (i.e.creating well distributed job opportunities), eradicating poverty,protecting public health and improving financing models to sup-port development of green economies and sustainability initiatives,and use of earth critical material across regional dimensions.

The five different options for design of CPIAP-SD academicprograms were also listed in the questionnaire. These were notmeant to reflect what is currently taught at any one university, butinstead they were suggestive of courses that could include cleanerproduction topics with an objective of improving sustainabledevelopment:

� Type I: Provide Exposure to the Basic Knowledge of CP and SD� Type II: Include Fundamental of CP and SD Concepts in AllCourses

� Type III: Design of Cleaner Production and Sustainability Grad-uate Programs

� Type IV: Develop Concentration/Minor in CPeSD� Type V: Promote Research In the Areas of CP and SD

Participants were asked to score each indicator according to theirperception of its importance for each of the listed academic programsand courses. The scores were assigned on a scale of 0e3 with 0 indi-cating “not at all important” and 3 indicating “highest importance.”While Tables 1a and b in the questionnaire collected data about de-mographics of the reviewers and an overview of the academic pro-gram types, content, criteria groups and associated indicatorsrespectively, Table 2 asked participants to assess the constraintsassociated with the development and implementation of the aca-demic programs. For example, for Constraint 1 (Ease of Imple-mentation), participants were directed to assign a value of 0 if theybelieve that changing academic programs is easy and so can beimplemented, or “1” if they believe otherwise (Appendix I for details).

5.4. Data recording instructions

In order to assist with completing questionnaires which weresent to the participants electronically, we produced and emailed toall participants videos, one in English and one in Chinese describingproject goals, objectives, definitions of the criteria and their in-dicators as well as significance of the listed academic programs inthe questionnaire. Also provided were a 2 page guidelines inSpanish, English and Chinese, describing steps involved withcompleting the questionnaires, methods for assigning weights, andscoring constraints associated with program implementations.

6. Data analysis and results

The objective of the study, as stated before, has been to under-stand/convey the importance of including CPIAP-SD topics indiverse academic settings. Our integrated approach, however,


allowed us to perform this study globally, and in countries withvarying levels of economic development goals and objectives, whiletaking into account their capacity based constraints.

The questionnaire used in the study was designed to assist withcollecting data needed to understand/characterize factors andconstraints associated with the design and implementation of ac-ademic programs that could integrate cleaner production conceptswith the requirements of sustainable development. We havereceived a total of 25 completed questionnaires from the LatinAmerica, the United States, and China with a response rate of about60e80%, respectively.

The first step of data analysis involved characterization of therespondents’ demographic (see Table 1). As shown, male re-spondents contributed 80, 62, and 43 percent of the completedquestionnaires obtained in Latin America, China, and US, respec-tively. Cumulatively, 64 percent of respondents were male and 36percent female. While 50 percent of respondents had formal engi-neering training and work experience, 25 percent were frommanagement/business disciplines and 24 percent had backgroundeducation and practical experience in both fields. The level ofexposure and understanding of the issues associatedwith designingcleaner production programs, sustainability education or researchinitiatives ranged from 48 to 24 percent (according to respondentself-assessment). All participants had been introduced to theconcept of cleaner production and sustainable economic develop-ment, while 72 percent had sufficient knowledge in these areas.

6.1. Quantitative analysis of the results

6.1.1. Homogeneity test (Chi-square test)Data analysis was performed confirming that scores were

assigned on a scale of 0e3. Each one of the 18 indicators (seeTable 1b Appendix I) took any value integral in the interval of 0e3.These values were integers like the scores associated with the 4constraints which could take the value 0 or 1.

We have worked with the scores identified for each indicator(cell ij) to estimate the cumulative scores for each criterion using ahorizontal summing method and assigned weights for each col-umn. The total score for each program then was estimated bysumming up scores obtained for criteria 1e4. The program scoreswere then corrected (normalized) according to the number ofprogram sub-topics identified in the questionnaire prior to beingconsidered for further analysis.

The first step in quantitative data analysis was to test the hy-pothesis of homogeneity for the collected data (scores of eachprogram) both for total scores and for each participating country(USA, China and Latin America). More specifically, this test wasused to determine the level of consistency among responses(importance of scores) obtained for types of academic programsevaluated in this study.

c22 ¼�OijEij

�2

Eij(1)


Table 2Results of c2 tests performs to test hypothesis of homogeneity among reported scores (j: < 1 ¼ Not Important ¼ NI, 1 � x < 2 ¼ Important ¼ I, � 2 ¼ Very Important ¼ VI).

Programs Total scores Eij c2 Comment

N I VI Row total

I 1.00 7.00 13.00 21.00 1.50 10.00 9.50 4.71V 2.00 13.00 6.00 21.00 1.50 10.00 9.50Column total 3.00 20.00 19.00 42.00II 3.00 11.00 7.00 21.00 2.50 12.00 6.50 0.44V 2.00 13.00 6.00 21.00 2.50 12.00 6.50Column total 5.00 24.00 13.00 42.00III 7.00 8.00 6.00 21.00 4.50 10.50 6.00 3.97V 2.00 13.00 6.00 21.00 4.50 10.50 6.00Column total 9.00 21.00 12.00 42.00IV 5.00 10.00 6.00 21.00 3.50 11.50 6.00 1.68V 2.00 13.00 6.00 21.00 3.50 11.50 6.00Column total 7.00 23.00 12.00 42.00I 1.00 7.00 13.00 21.00 2.00 9.00 10.00 3.69II 3.00 11.00 7.00 21.00 2.00 9.00 10.00Column total 4.00 18.00 20.00 42.00III 7.00 8.00 6.00 21.00 5.00 9.50 6.50 2.15II 3.00 11.00 7.00 21.00 5.00 9.50 6.50Column total 10.00 19.00 13.00 42.00IV 5.00 10.00 6.00 21.00 4.00 10.50 6.50 0.62II 3.00 11.00 7.00 21.00 4.00 10.50 6.50Column total 8.00 21.00 13.00 42.00I 1.00 7.00 13.00 21.00 4.00 7.50 9.50 7.15 XIII 7.00 8.00 6.00 21.00 4.00 7.50 9.50Column total 8.00 15.00 19.00 42.00II 3.00 11.00 7.00 21.00 5.00 9.50 6.50 2.15III 7.00 8.00 6.00 21.00 5.00 9.50 6.50Column total 10.00 19.00 13.00 42.00IV 5.00 10.00 6.00 21.00 6.00 9.00 6.00 0.56III 7.00 8.00 6.00 21.00 6.00 9.00 6.00Column total 12.00 18.00 12.00 42.00I 1.00 7.00 13.00 21.00 3.00 8.50 9.50 5.78 XIV 5.00 10.00 6.00 21.00 3.00 8.50 9.50Column total 6.00 17.00 19.00 42.00II 3.00 11.00 7.00 21.00 4.00 10.50 6.50 0.62IV 5.00 10.00 6.00 21.00 4.00 10.50 6.50Column total 8.00 21.00 13.00 42.00

TotalPrograms Total scores

N I VI Row total Eij Chi-square for program Type I to III 1 7 13 21 2 9 10 3.6889II 3 11 7 21 2 9 10Column total 4 18 20 42

Eij Chi-square for program Type II to IIII 3 11 7 21 3 11 7 0II 3 11 7 21 3 11 7Column total 6 22 14 42

Eij Chi-square for program Type III to IIIII 7 8 6 21 5 9.5 6.5 2.1506II 3 11 7 21 5 9.5 6.5Column total 10 19 13 42

Eij Chi-square for program Type IV to IIIV 5 10 6 21 4 10.5 6.5 0.6245II 3 11 7 21 4 10.5 6.5Column total 8 21 13 42

All types to IIITotalPrograms Total scores

N I VI Row totalI 1 7 13 21 4 7.5 9.5 7.1456III 7 8 6 21 4 7.5 9.5Column total 8 15 19 42II 3 11 7 21 5 9.5 6.5 2.1506III 7 8 6 21 5 9.5 6.5Column total 10 19 13 42III 7 8 6 21 7 8 6 0III 7 8 6 21 7 8 6Column total 14 16 12 42

(continued on next page)


Please cite this article in press as: Khalili, N.R., et al., From cleaner production to sustainable development: the role of academia, Journal ofCleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.099

Table 2 (continued )

IV 5 10 6 21 6 9 6 0.5556III 7 8 6 21 6 9 6Column total 12 18 12 42

All types to IVPrograms Total scoresCompare program 1 to V N I VI Row total Eij Chi-square for program Type II 1 7 13 21 3 8.5 9.5 5.775IV 5 10 6 21 3 8.5 9.5Column total 6 17 19 42Compare program II to V Eij Chi-square for program Type IIII 3 11 7 21 4 10.5 6.5 0.6245IV 5 10 6 21 4 10.5 6.5Column total 8 21 13 42Compare program III to 5 Eij Chi-square for program Type IIIIII 7 8 6 21 6 9 6 0.5556IV 5 10 6 21 6 9 6Column total 12 18 12 42Compare program IV to V Eij Chi-square for program Type IVIV 5 10 6 21 5 10 6 0IV 5 10 6 21 5 10 6Column total 10 20 12 42


Formula 1 was used to estimate the c2 test statistics among allfive program types. The test, accordingly, required organization ofthe scores obtained from completed questionnaires (observedvalues (Oij)) for each academic program type tested (i), and theirimportance for scoring intervals j (j: < 1 ¼ Not Important ¼ NI,1� x< 2¼ Important¼ I,� 2¼ Very Important¼ VI). The expectedscores were estimated under assumption of homogeneity (Eij). Thehigher value of the test statistic indicated greater inconsistencyamong scores reported for the programs tested in this study. Asshown in Table 2, since estimated c2 were less than tests statisticsat both 5 and 10 percent levels (df ¼ (5 � 1) (3 � 1) ¼ 8, and 5, and10 level of significance with Chi Squares of 15.5 and 13.36), weconcluded that there is no statistically significant difference amongsores reported for different tested academic programs and, there-fore, it is safe to conclude that the hypothesis of homogeneity fordata collected in this study can be assumed. Table 2 presents the c2test results for the total observations in this study. According to theresults, almost all program types have been evaluated to be equallyimportant, suggesting that we could accept the hypothesis of ho-mogeneity among data at both 5 and 10% significance. On the otherhand, the high values of c2 test statistic suggested different resultsfor program Types I, III, and IV. For example, programs I and III hadsignificant discordance (with c2 of 7.4) at both 5 and 10 percentlevels (the critical values of c2 at 5 and 10 percent significance with2 degree of freedom are 5.991 and 4.605 respectively). Similarlyhomogeneity was rejected among programs type I and IV at 10percent significant level (c2 of 5.78 > 4.605). These results sug-gested that programs type I and III were most differently valued.

6.1.2. Cluster analysisWe performed cluster analysis for our data set to evaluate

whether there are disjoint subsets or “clusters” among our data.Cluster analysis is an “unsupervised” data-mining tool. Unlike su-pervised data mining tools that are driven by user direction, clusteranalysis has no “a priori “assumptions concerning the number ofclusters or cluster structure. The basic objective in clustering is,therefore, to discover natural groupings of the cases or variablesbased on some similarity or distance (dissimilarity) measures. Weconducted average linkage cluster analysis for our entire data setutilizing all variables as analysis variables, and then separately us-ing only Resource Management (RM), Socio-Economic Develop-ment and Prosperity (SEDP), Human Capital Development (HCD),and Human System and Governance (HSG) variables, respectively,to examinewhether therewere discernible clusters of observations.


The analysis yielded several interesting observations. Bothwhenconsidering all variables, and when considering the subsets of thevariables. One cluster includes all American (North and CentralAmerican) participants, while the other cluster includes all Chineseparticipants. It was also observed that when evaluating ResourceManagement variables only, some members of the Americancluster were only marginally more similar to one another than tomembers of the more defined Chinese cluster. In the analysis ofSocio-Economic Development and Prosperity variables, twoAmerican clusters and one Chinese cluster emerged. The analysis ofHuman Capital Development (HCD) variables did not result inclusters. Human System and Governance (HSG) variables yieldedonly one cluster for Americans, and one for Chinese.

6.2. Qualitative analysis of data

The questionnaire was designed to also examine applicability offive different academic approaches to sustainability education ac-cording to their cumulative scores. Approaches ranged fromexposure to basic knowledge (Type I), tools and techniques (i.e. lifecycle analysis models, Types II and III), design of full programfocusing on practical and implementation strategies (Type IV), toinvesting into basic research that is specific to developing sus-tainability theories/models, and technological innovation that isresponsive to cultural and regional diversities and prerequisites(Type V).

The total normalized scores for programs, however, indicatedthat all types of criteria have been scored to be roughly equallyimportant (Fig. 2). The highest criteria-based scores were obtainedfor RM (resource management) with its indicators. Criterion sub-indicators (RM1 ¼ ecoregion protection, RM2 ¼ climate change-carbon management, RM3 ¼ water management, RM4 ¼ earth-land management, and RM5 ¼ proper use of critical and nonre-newable material) were considered roughly equally important toone another. For the other indicators, some sub-indicators wereranked higher than others: HCD1 (human health risk manage-ment), SEDP3 (energy use and intensity management), and HSG2(green economic development and policies) outranked other sub-indicators in their respective criteria.

The questionnaire was also used to evaluate how expertsparticipating in this study would rank the importance of includingCPeSD criteria in development of different types of academicprograms. Analysis of the data indicated no statistically significantdifferences among the raw and weighted scores estimated for the


Fig. 4. Criteria Ranking according to their normalized weighted scores for all regions.0% 20% 40% 60% 80% 100%

TYPE I

TYPE II

TYPE III

TYPE IV

TYPE V

Normalized Scores

Prog

ram

RM SEDP HCD HSG

Fig. 2. Observed normalized total scores for each criteria and academic program types.


program types. Regional based analysis of data presented in thegrouped Fig. 3 below suggested that US participants have scoredthe importance of developing CP-specific academic programs thatcan promote sustainable development higher for all types of theproposed programswhen compared to participants from China andLatin America. China clearly scored the importance of the researchhigher than Latin America, but lower than the US.

As expected, experts’ academic background, practicing disci-plines, as well as understanding of the specific needs for each re-gion affected scores identified for program types and theirimportance (as shown in Fig. 3). These results, expectedly, indicatedthat the discipline and teaching pedagogies could impact academicperspectives and defined level of needs for inclusion of sustain-ability and clean production perspectives in university curriculums.

Total weighted and normalized scores obtained for each sus-tainable development criterion (from their indicators tested in this

Fig. 3. Region-discipline-specific rank


study) indicated that inclusion of resource management (RM)topics in academic programs is the most preferred approach in allregions followed by developing programs in the areas of humancapital development (HCD), human system development (HSD),and sustainable economic development and prosperity (SEDP) at32, 27, 23, and 18 percent respectively (Fig. 4).

Analysis of the constraints (estimated according to scores ob-tained for ease of implementation, availability of the human capital,availabilityoffinancial resources, andother region specific policies orneeds) is presented in Fig. 5. As indicated, all regions indicated thatimplementing program type V (conducting fundamental research inspecified areas of sustainability) was least constrained. The highestlevels of constraints were reported for program types II in China andLatin America, and type IV for United States, respectively.

Data obtained from qualitative analysis of the questionnaires,more specifically, suggested that:

� Cumulatively, most experts favored the inclusion of resourcemanagement topics in academic programs over socio-economictopics.

ing of academic program types.


Fig. 5. An analysis of the Program-Region specific constraints.


� Indicators (topics) which were ranked the highest for differentcriteria were:� HCD1 (human health risk management),� SEDP3 (energy use and intensity management), and� HSG2 (green economic development and policies).

� Across the board the highest scores were assigned to programsType I followed by Type II, Type V, Type IV and Type III,respectively. Type IVwas evaluatedmuch less favorably than theother four program types across the board

� The potential impact of the experts’ background and countriesof originwere also evaluated. As shown in Fig. 3, US respondentsassigned the highest scores for inclusion of CPeSD topics in allacademic programs. China scored program types IV and V as themost important, while Latin America favored program types IIand V. This discrepancy was expected due to the existing vari-abilities in the participating universities educational model andfocus.

7. Conclusion

The primary purpose of this study was to understand how ac-ademic programs infused by cleaner production concepts andtheories can be advanced, under different constraints, to supportsustainable development. The main goal, however, has beendevelopment of human capital that can understand the urgencyand the need for pursuing SD and greening all emerging economies.Human capital, in this context, is defined here as individuals whounderstand and are capable of driving the design of CP strategiesfor sustainable development while taking into account regional,national and global priorities, cultural diversity and financialconstraints.

The paper suggests the application of a methodology by whichleaders in higher education could assess the need and define

Table 1aGeneral information.

1-Discipline (business, engineering, science, economics,.etc.):2-Age3-Nationality4-Gender5-Academic degree6-Are you directly involved with sustainability education/practice?

(Circle yes or no)7-What best describes you? (circle best answer)8-Were you involved with sustainability education/practice in your previous

professional activity? (Circle yes or no)9-Do you have any experience in developing curricula for academic education?

(circle yes or no)10-Membership/affiliation with any organizations dealing with sustainability issues?


patterns, types, and characteristics of training programs needed todevelop such human capacity in support of SD. At its core, theproposed methodology was formulated to utilize expert judgmentto assess the importance of a matrix of CPeSD indicators needed fordesign of common core CP infused academic programs. The criteriaand indicators were selected to (a) provide crucial guidance fordecision-making in a variety of ways as identified by specificationsof the listed academic programs in the questionnaire, and (b)translate the science of CP and sustainability knowledge intomanageable units of information that can facilitate the adminis-trative process when approaching the design and implementationof CPeSD programs.

Results of this study supported, among others, the two keytopics that are worthy of consideration in sustainable develop-ment initiatives (Bonilla et al., 2010): namely, efficient use of re-sources (RM in this study), and integration of sustainabledevelopment topics in the research. Results were also comparableto those reported for Australia, and Europe (UK, and Germany forexample), suggesting urgency for developing human capital atcapacities that can support SD. More specifically, this study pro-vides insight into how academic programs infused with cleanerproduction concepts and theories can be designed, under differentconstraints, to support sustainable economic development atglobal scales.

Although the methodology presented in this paper was provento be efficient, practical, and educational in nature, we suggest andemphasize on the need for conducting more studies with largerdata sets prior to confirming these results to be universal in nature.The proposed methodology, accordingly, was designed to be flex-ible, and as such, could bemodified to include and/or expand on theformat or diversity of the indicators, program types, expertise, andprofessional skills needed for the assessment phase.

Acknowledgment

The authors wish to thank participants in the survey, and thepartners in the Pathways to Cleaner Production in the Americasproject funded by Higher Education for Development, for theircontributions towards and participation in discussions regardingthe topics in the article.

We also would like to acknowledge the great work done by Mr.Xike Cheng andMr.Weiquan Cheng during data collection in China.

Appendix 1. The CPIAP-SD goal and objectives

“Design of Academic Programs for a Prosperous, Innovative,Knowledge-rich, Competitive and Eco-efficient Sustainable andHigh Living Standards”

Please provide background information below

Yes No If Yes, please describe:

Faculty Researcher Consultant Other* *If Other, please describe:Yes No If Yes, please describe:




Table 1b

Educational criteria (subject matter) and associated indicator for CP infused Academic program for sustainable development (CPIAP-SD)

Academic discipline: Resource Management (RM) Socio-Economic Development and Prosperity (SEDP) Human Capital Development (HCD) Human System and Governance (HSG)

RM1 RM2 RM3 RM4 RM5 SEDP1 SEDP2 SEDP3 SEDP4 SEDP5 HCD1 HCD2 HCD3 HCD4 HSG1 HSG2 HSG3 HSG4

Academic program/(examplescoring* values from 0e3)

3 1 2 2 3 3 2 1 0 2 1 2 1 2 1 2 3 0

Type I: practicum (1e2 coursecovering application of CP)

Senior design courses (2 semesters)Capstone coursesCreating internships/project specific

courses with industryOthers 1 (please propose)Type II: including fundamental

of CP and SD in all coursesScience of sustainable developmentDesign of CP strategiesFundamental of industrial ecologyProcess diagnostics and logisticsCP financing optionsEnvironmental economicsOthers 1 (please propose)TYPE III: cleaner production and

sustainability programsCore coursesElectivesThesisInternshipOthers 1 (please propose)Type IV: developing concentration/

minor in CPeSDFundamentals of cleaner productionIndustrial ecologyEnvironmental economicsScience of sustainabilitySustainable innovationCorporate social responsibilityOthers 1 (please propose)Type V: promoting research in

the areas of CP and SDDemand managementSustainable transportationAgriculture, food securityClimate change issues and carbon

managementEnergy systems, intensity, demandWater managementWaste managementFinancial models for sustainable

developmentManagement of resources and

critical materialInternational trade/global issuesOthers 1 (please propose)Example weights (any value

between 0 and 1)1 0.5 0.5 1 1 1 1 0 1 0.7 0 0.5 0.3 0.8 0.4 1 0 0.5

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Scores

Scores: 0 ¼ not important, 1 ¼ slightly important, 2 ¼ important,3 ¼ very important.

Weights

WEIGHT needs to be a value between 0 and 1 (i.e. 0.2, 0.4, 0.55,.1)and assigned to each indicator defined for each category (Defaultvalue ¼ 1). Weight indicates relative importance of the indicators ineach criterion/country-region.

List and definition of the criteria and group indicators

Fundamentals of resource management (ecological risk analysis:theories, tools, applications)

RM1 ¼ Eco-region protection (e.g. deserts, forests, grasslands,aquatic, and tundra)RM2 ¼ Climate change/carbon and energy managementRM3 ¼ Water management/conservation programsRM4 ¼ Earth-land-managementRM5 ¼ Use of critical/non renewable material

Socio-economic development/prosperity (economic risk analysis:theories, tools, implementation/applications)

SEDP1 ¼ Industrial growth/GDP per capita/Net national incomegrowthSEDP2 ¼ Household earning and savingSEDP3 ¼ Energy use and/or intensitySEDP4 ¼ Global partnershipSEDP5 ¼ Rate and dispersity of job creation

Human capital development (social risk analysis: theories, tools,implementation/applications)

HCD1 ¼ Health risk analysis (assessment/management)HCD2 ¼ Employment development/equality (gender-age-race)

Please cite this article in press as: Khalili, N.R., et al., From cleaner productCleaner Production (2014), http://dx.doi.org/10.1016/j.jclepro.2014.01.099

HCD3 ¼ Access to educationHDC4 ¼ Access to labor market

Human System Development and Governance (theories, tools,implementation/applications)

HSG1 ¼ Environmental/financial regulations/policies (taxes,subsidies, etc.)HSG2 ¼ Green economic development policiesHSG3 ¼ Global cooperation/partnership initiativesHSG4 ¼ Financial investment in green economy

Scoring

Expert scorer: direction estimates are absoluteExpert scorer: magnitude estimates are relative0 [ Not Important1 [ Slightly Important2 [ Important3 [ Very Important

Each Academic Program should provide a comprehensiveunderstanding of the Importance of

1eResource management: issues, tools, and challenges (RMcriteria)2eSustainable socio-economic development (SEDP criteria)3eDeveloping human capital to support CP and sustainabledevelopment (HCD Criteria)4eDeveloping human systems, governance, institutions, andpolicies to promote CP and sustainable development (HSD)5eImportance of CSR

Appendix 2. The CPIAP-SD Goal and Objectives

“Design of academic programs for a prosperous, innovative,knowledge-rich, competitive and eco-efficient sustainable and highliving standards”

ion to sustainable development: the role of academia, Journal of

Table A2The CPIAP-SD Goal and Objectives “Design of Academic Programs for a prosperous, innovative, knowledge-rich, competitive and eco-efficient sustainable and high living standards”.

Academic discipline: Constraint 1 Constraint 2 Constraint 3 Constraint 4 Constraint 5

Ease of implementation Need for humancapital resources

Need for financialresources

Country-specific focus Others

EI (score 0 or 1) HCR (i.e. faculty/CP centers)(score 0 or 1)

FR (scholarships,research assistantship)(score 0 or 1)

CSN (water/energy/tech transfer)(score 0 or 1)

Please specify(score 0 or 1)

Academic programs 0 (Not a constraint)or 1 (is a constraint)

0 (Not a constraint)or 1 (is a constraint)




Type I: Practicum (1e2 course coveringapplication of CP)

Senior design courses (2 semester)Capstone coursesCreating internships/project specific courses

with industryOthers 1 (please propose)Others 2 (please propose)Type II: including fundamental of CP and

SD in all coursesScience of sustainable developmentDesign of CP strategiesFundamental of industrial ecologyProcess diagnostics and logisticsCP financing optionsEnvironmental economicsOthers 1 (please propose)Others 2 (please propose)TYPE III: design of CPeSD graduate programsCore coursesElectivesThesisInternshipOthers (please propose)Type IV: developing concentration/minor

in CPeSDFundamental of cleaner productionIndustrial ecologyEnvironmental economicsScience of sustainabilitySustainable innovationCorporate social responsibilityOthers 1 (please propose)Type V: promoting research in the areas

of CP and SDDemand managementSustainable transportationAgriculture, food securityClimate change issue and carbon managementEnergy systems, intensity, demandWater managementWaste managementFinancial models for sustainable developmentManagement of resources and critical materialInternational trade/global issuesOTHER1 (please propose)

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From cleaner production to sustainable development: the role of academia