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Supply Chain Proficiency in Relation to Resilience, Robustness,

Social-Ecological Innovation and Enterprise Sustainability

Rick Edgeman, Professor of Performance & Enterprise Excellence

Interdisciplinary Center for Organizational Excellence & AU-Herning

Aarhus University

Aarhus, Denmark

Zhaohui Wu, Associate Professor of Supply Chain Management

College of Business

Oregon State University

Corvallis, Oregon, USA

Abstract

Purpose – To broadly explore the contributions of supply chain proficiency in relation to

Sustainable Enterprise Excellence, Resilience and Robustness (SEER2).

Design/methodology/approach – A pre-existing SEER2 model, referred to as the Springboard

to SEER2 is put under the microscope to determine specific interactions of supply chain

proficiency with six key areas of the Springboard: triple top line strategy and governance;

strategy execution via policies, processes, and partnerships; financial and marketplace

performance and impact; sustainability performance and impact; human ecology and capital

performance and impact; and social-ecological and general innovation and continuous

improvement performance and impact.

Findings – Supply chain proficiency is integral to attainment of Sustainable Enterprise

Excellence, Resilience and Robustness (SEER2). As such, supply chain proficiency must be

thoughtfully and strategically approached, with success critical to enterprise contribution to

mitigation or solution of wicked global challenges ranging from climate change, to food

insecurity to societal conflict.

Originality/value – This paper reveals in depth the centrality of supply chain proficiency to

Sustainable Enterprise Excellence, Resilience and Robustness, suggesting that such models as

those behind the Malcolm Baldrige National Quality Award and the European Quality Award

might be enhanced by more deeply considering the importance of the supply chain to business

and performance excellence.

Keywords – Assessment, big data analytics, governance, resilience, robustness, social-ecological

innovation, supply chain proficiency, sustainable enterprise excellence, triple bottom line, triple

top line.

Paper type – Research paper

Introduction

Sustainable enterprise excellence, resilience, and robustness (SEER2) are important, desirable,

and related, but not wholly consonant enterprise traits, with objectives that differ in subtle yet

important ways. Multiple enablers of SEER2 have been identified (Edgeman, 2013; Edgeman

and Eskildsen, 2014a; Edgeman and Williams, 2014), among which are governance, big data

intelligence and analytics, operational & supply chain proficiency, general- and social-ecological

innovation (Edgeman and Eskildsen, 2014b), and human ecology.

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SEER2 results from strategic and tactical integration of critical principles and practices from the

business excellence and sustainability movements, where:

Sustainable enterprise excellence, resilience and robustness balance the complementary

and competing interests of key stakeholder segments, including society and the natural

environment and increases the likelihood of superior and sustainable competitive

positioning and hence long-term enterprise success that is defined by continuously

relevant and responsible governance, strategy, actions and performance. This is

accomplished through ethical, efficient and effective (E3) enterprise governance

(Elkington, 2006) and strategy that emphasize superior organization design & function,

innovation, enterprise intelligence & analytics, operational, supply chain, customer-

related, human capital, financial, marketplace, societal, and environmental strategy and

performance. Sustainable enterprise excellence results from driving 3E triple top line

strategy (McDonough and Braungart, 2002a) throughout enterprise culture, processes,

and activities to produce superior triple bottom line 3P performance (Elkington, 1997)

that is simultaneously pragmatic, innovative and supportive of enterprise resilience and

robustness.

While numerous forms of innovation are important to SEER2, both general and – especially -

social-ecological innovation are emphasized in SEER2. Social-ecological innovation (SEI)

occurs at the interface of sustainable innovation and innovation for sustainability. Sustainable

innovation is central to organizational culture when innovation is regular, rigorous, systematic,

systemic, and a focal part of enterprise strategy. Innovation for sustainability explicitly targets

social or environmental outcomes that are tangibly and positively linked to both general and

enterprise financial performance so that SEI partially enables transformation of triple top line

strategy into triple bottom line performance.

SEI is critical to enterprise resilience and robustness where resilience is an enterprise’s capacity

to self-renew through innovation (Reinmoeller and Van Baardwijk, 2005) and adapt its responses

over time to negative shocks or extreme challenges (Contu, 2002). Robustness is resistance or

immunity to such impacts and challenges through formation and execution of an array of

enterprise strategies, policies, partnerships, and practices that maintain enterprise competitive

position or transform extreme challenges into opportunities, thus avoiding any necessity to

rebound. Realizing SEER2 requires tradeoffs between optimal performance, resilience and

robustness, a dilemma that arises since performance of a robust and resilient enterprise rarely

matches the efficiency of less robust and less resilient “optimum” one, but instead delivers

performance that does not deteriorate as precipitously or rapidly (Anderies et al., 2004).

SEER2 and SEI are central to continuously relevant and responsible organizations (Edgeman et

al., 2013) with focus herein directed to elaboration of supply chain proficiency contributions to

and interrelationships with SEER2 and SEI.

Sustainable enterprise excellence, resilience and robustness

Enterprise sustainability is its capacity to create and maintain economic, environmental and

social value for itself, its stakeholders and society at large, in the short term and for the long term

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–sustainability is the capacity to survive. Although survival is attractive in most cases, there are

complementary performance considerations that, when integrated with survival, enhance

enterprise performance including stakeholder perception (Wang and Qian, 2011) that translates

into financial and marketplace performance (Harrison et al., 2010).

What are these complementary considerations?

If sustainability connotes with survival, then excellence is the capacity of the enterprise to

prosper via delivery of superior performance across an array of defined domains. Performance

domains considered vital to enterprise excellence include big and small data analytics and

intelligence, corporate governance and leadership, operations and supply chain management,

innovation, and enterprise human ecology. By human ecology we intend the relationships

between the enterprise and its human capital with its supply chain and extended social, natural,

and built environments (Lozano, 2011), including competition, cooperation and collaboration

among individuals and entities within the enterprise and across boundaries.

Strongly related to sustainability and excellence are resilience and robustness, and though these

are sometimes used synonymously, they have both shared and unique qualities. Though

Reinmoeller and Van Baardwijk (2005) characterize resilience as enterprise capacity to self-

renew over time through innovation, more generally resilience may be thought of as the ability of

an enterprise to continually change, reinvent itself, and adapt its responses to negative shocks or

extreme challenges in a multi-faceted ecosystem that includes political, social, economic and

other aspects of its competitive domain (Contu, 2002). In contrast, robustness is immunity or

resistance to impacts from such shocks or challenges (Scholz et al., 2012) and is gained

principally via formulation and execution of an array of strategies, policies, partnerships, and

practices that maintain enterprise competitive position despite adverse conditions.

Enterprise excellence, sustainability, resilience, and robustness – the components of SEER2 – are

related yet not wholly consonant constructs in the sense that the strategy, policies, and actions set

optimizing one of these is unlikely to optimize the others. Important questions thus include ones

of how significantly optimization of a singular component will lead to departure of each of the

remaining components of SEER2 from their optima, as well as which one of the SEER2

components is best to singularly optimize at the expense of the others. Edgeman and Williams

(2014) provide a conceptual calculus that captures the essence of this argument. They do so

through formulation of a coefficient of enterprise resilience and robustness (CER2) that is

derived by integrating and adapting Isaac Newton’s coefficient of restitution and Leonardo Da

Vinci’s coefficient of friction. Optimization of CER2 and hence enterprise resilience and

robustness include conceptual analogs to steepest ascent and descent methods (Box and Draper,

1987) and formulation of minimax regret strategy (Blackwell and Girshick, 1954).

Mathematically, a solution derived from a holistic approach that simultaneously explores and

harnesses synergies and reconciles dissonances among sustainability, excellence, resilience and

robustness will always dominate solutions derived from optimizing one of the SEER2

components in preference to the others. The extent of dominance depends on the degree to which

overall results are sensitive to the component of SEER2 selected for optimization with the

preference for a holistic approach – e.g. joint, constrained optimization – increasing as

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dissonance increases. It must be noted that mathematical concepts and language have been used

to describe the inherently qualitative constructs of sustainability, excellence, resilience and

robustness and that such holistic approaches generally derive from “making soft measures

harder” through use of carefully crafted, linguistically expressed maturity scales that are

sensitive to enterprise context and preferences.

From whence SEER2 comes and whither it goes?

The sustainability movement is closely associated with the triple bottom line that stresses a blend

of societal, ecological, and economic benefits (Elkington, 1997), yet the focus of many of its

advocates is inherently social-ecological, dedicating scant attention to the economic performance

dimension that is cornerstone to enterprise excellence. Similarly, enterprise excellence adherents

have historically devaluated the triple bottom line’s social and environmental dimensions.

Sustainable Enterprise Excellence (SEE) targets strategic integration of principles,

methodologies, and standards common to the enterprise excellence and sustainability movements

(Edgeman and Eskildsen, 2013) as a means of realizing Zadek’s (1999) vision of their

unification and subsequent joint, albeit constrained optimization of enterprise performance

across the triple bottom line people, planet, and profit (3P) domains, along with other related

domains.

Prior attempts at SEE have primarily focused on addition of sustainability modules or

perspectives to established excellence models, rather than on full integration of excellence and

sustainability. Although such efforts acknowledge sustainability, they have generally

marginalized its importance and have only poorly leveraged synergies, reconciled dissonances,

or prioritized sustainability performance. Among enterprise excellence models are the balanced

scorecard (Kaplan & Norton, 1992) and those supporting America’s Baldrige National Quality

Award the European Quality Award (Bou-Llusar et al., 2009). Familiar social-ecological

sustainability standards and principles include the 10 Principles of the United Nations Global

Compact (Kell, 2012), ISO 26000 Social Responsibility Standard (Helms et al., 2012), ISO

14000 Environmental Management Standard (Curkovic and Sroufe, 2011), United Nations

Millennium Development Goals (Sachs, 2012), and the Global Reporting Initiative or GRI

(Scherer and Palazzo, 2011).

Resilience, robustness, sustainable enterprise excellence, social-ecological innovation, and big

data intelligence & analytics are subsequently elaborated both separately and in relation to one

another while limiting consideration of other key SEER2 elements. Edgeman and Williams

(2014) introduce Springboard modeling focused on a strategic blend of simplicity and usability

to provide a SEER2 model and associated assessment regime. Their approach delivers insight

into recent organizational performance, including tactical and strategic successes and failures as

well as post-decision surprise areas where performance differed significantly from projections in

either form or magnitude (Smith and Winkler, 2006). Of perhaps greater in value is the ability of

the model and assessment regime to provide enterprise foresight that informs and shapes future

strategy and tactics that in turn lead to next best practices and sources of competitive advantage.

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Prominent SEER2 enablers in relation to supply chain proficiency

Enterprise governance (Duit et al., 2010), big and small data analytics and intelligence (Teece,

2007), general and social-ecological innovation (Boons et al., 2013; Teece, 2010), enterprise

human ecology (Sheth et al., 2011), superior operations (Edgeman et al., 2014), and supply chain

proficiency (Wu et al., 2014) have been identified as key enablers of SEER2. These are now

discussed in relation to one another, SEER2, and social-ecological innovation (SEI).

By supply chain we intend a system of enterprises, people, activities, information and resources

involved in the production and distribution of a product, service, or information from supplier to

customer. The importance of supply chain sustainability, resilience, and robustness have become

obvious in the wake of the terrorist strikes of September 11, 2001 (Christopher and Peck, 2004),

natural disasters such as the 2004 Indian Ocean tsunami, the 2011 Fukushima Daiichi nuclear

reactor meltdown in Japan, and Superstorm Sandy in 2012 and resulting severe supply chain

disruptions. Owing to sheer size, increasing geographic footprint, and more complex services

and products, firms around the globe are increasingly subject to disruptions that erode or impair

supply chain relationships, operations, and broader performance (Bode et al., 2011) with more

than 90% of companies involved in a survey by Price Waterhouse Coopers (2013) indicating that

such disruptions significantly impact their business and financial performance.

Superior operational and supply chain performance is a key enabler of SEER2 (Cao and Zhang,

2011) so that it must be important to and embedded in enterprise strategy, partnership

cultivation, policies and processes, and its performance relative to other key SEER2 enablers

must be managed, measured and honed. Superior supply chains are fast, cost-effective, agile,

adaptable, and able to ensure that all of the enterprises’ interests remain aligned (Lee, 2004),

robust, and resilient. Such characteristics provide obvious suggestions for assessment,

particularly when they can be directly connected to SEER2 or other of its key enablers in order

to leverage synergies.

Larger, more complex organizations often have larger and more complex ecosystems and supply

chains so that the importance of supply chains to enterprise resilience and robustness can be

profound. Strategies aimed at increasing operations and supply chain resilience and robustness

ordinarily focus on managing and minimizing operational and supply chain risk (known

unknowns) and reducing uncertainty (unknown unknowns) relative to the potential impact on

assets and related services that might result from inadequate or failed internal processes, systems,

technology, actions of people, or external events leading to supply chain or operations corruption

or disruption (Gulati et al., 2010). Operational and supply chain resilience and robustness

strategies thus seek to sustain high-value operations, services or supply sources or to limit

damage to or disruption of these due to risk or uncertainty realization; effectively and efficiently

address results and ramifications of risks and uncertainty in order to restore the organization to

its prior steady state; and fulfill these goals at lowest cost, least negative social consequence, and

least damaging environmental impact. The intent then is to design, create and implement more

resilient and robust operations and supply chains via strategies and approaches that include risk

segmentation; operations and supply chain flexibility and agility; information sharing and

security throughout the supply chain (Cachon & Fisher, 2000); operational and supply chain

maturity and risk management (PricewaterhouseCoopers, 2013); trust and collaborative

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relationships among supply chain partners (Faisal et al., 2006); corporate social responsibility

(Sydow & Frenkel, 2013), and alignment of incentives and revenue sharing policies across the

supply chain (Tsay, 1999). A sustainability-oriented constraint that may be governance enforced

is that such approaches should support closed loop cradle-to-cradle practice (McDonough &

Braungart, 2002b) wherein end-of-life products supply energy or material for subsequent

products or processes (Maxwell et al, 2006; Souza, 2013).

Government, governance, and supply chain proficiency

Sustainability cannot in the omnibus sense be separated from climate change and this typically

intersects supply chains so that in many cases a sustainable supply chain must of necessity

equate to an ethical and eco-efficient one. Baseline corporate and supply chain governance

expectations are that it should be both ethical and transparent and should embrace the Ten

Principles of the United Nations Global Compact (UNGC) that address human rights, labor,

ecological, and anti-corruption issues that are echoed and added to by the Global Reporting

Initiative or GRI (Rasche and Gilbert, 2012). These areas may be more fully and contextually

elaborated to embed more specific supply chain governance practices – for example business

sectors or activities in which an organization is engaged may dictate adherence to designated

codes of conduct. Similarly, governance in complex supply chains and multinational

corporations may be subject to differing national or regional expectations and hence alternative

governance expressions, a fact supporting the call for third-party supply chain governance

involvement (Bitran et al., 2007).

Two primary actors establish the legal and competitive boundaries inside of which an

organization and its supply chain compete: government and the marketplace. Although many

organizations function globally, governments influence their marketplace. Governments also

function with varying sovereignty levels that are enriched or limited by international alignments

such as the European Union or United Nations, agreements such as NAFTA, or – on some

occasions – by life-and-resource sapping conflicts. While some components of alignments and

agreements are voluntary, others are obligatory and anticipate cooperation, collaboration, or

compliance with failure to supply these resulting in censure or more dramatic disciplines such as

trade embargos. As such, alignments, agreements, and conflicts among nations may either

support or inhibit positive environmental policy and action. This implies societal need to

determine and deliver, and to review and revise the roles, responsibilities, and actions of

government needed to realize the future we desire. Given long term atmospheric persistence of

climate changing greenhouse gases such as carbon dioxide (CO2) and nitrous oxide (N2O), a

desirable environmental future may not be accessible, so that mitigation and limitation of

damage may instead define boundary conditions since we know with near certainty that our

current path is toward global scale environmental catastrophe (New et al., 2010). Positive

organizational and supply chain performance relative to climate change is implicit in SEER2 and

may be made contextually explicit via enterprise selection of performance measures and

subsequent maturity assessment.

At government, corporate, and by extension supply chain governance levels, any future as such

is shaped by the degree of success or failure experienced in aligning private incentives with

societal and environmental considerations that compose the public good. John Locke insinuated

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this idea in his Second Treatise of Government on property rights in 1689 (Nacol, 2011) in

stating that property owners - corporations in our context – were entitled to the fruits of their

labors, yet obliged to leave “enough and as good” for others. Similarly, created in 1787 and

ratified in 1788, the United States Constitution anticipated the governmental role in what is

referred to as the general welfare clause (Lyons, 1977), that is: “to form a more perfect union,

establish justice, insure domestic tranquility, provide for the common defense, promote the

general welfare, and secure the blessings of liberty to ourselves and our posterity.” If the tack is

taken that the “blessings of liberty to … our posterity” include a safe natural environment, then it

may be argued that the United States is constitutionally obliged – at least domestically – to fulfill

essentially all key elements of the United Nations Post-2015 Sustainable Development Goals

(United Nations, 2013) that generally represent further elaboration of the 1987 World Council on

Environment and Development definition of sustainable development as development that

“meets the needs of the current generation without compromising the ability of future

generations to meet their own needs” (Robinson, 2004).

Centrality of governance to the strategy, policies, and practices of enterprise excellence (Foote et

al., 2010), sustainability (Aras and Crowther, 2008; Martinelli and Midttun, 2010), robustness

and resilience (Carmelli and Markman, 2011) is well-established (Fowler and Hope, 2007) and

governance stimulating supply chain robustness is of value is since enterprises having robust

supply chains tend more generally to be robust. Governance is important to each of the triple

bottom line dimensions of sustainability: people (Jo and Harjoto, 2012), planet (Walls et al.,

2012), and profit (Surroca et al., 2010) and both operational and supply chain robustness are

positively correlated to governance that prioritizes eco-efficiency. As a bonus benefit, the value

differential between more eco-efficient and less eco-efficient enterprises increases over time

(Guenster et al., 2010) so that supply chain participants are wise to place a premium on eco-

efficiency.

Given the relationship of governance to each of the triple bottom line elements, it is natural that

SEER2 incorporates governance. This is perhaps especially necessary in high intensity socio-

technical enterprise environments marked by the need to integrate and govern complex human

ecology and technological interfaces (Smith et al., 2005). Enterprise excellence models do not

directly address governance, whereas SEER2 anticipates the clear causal roles of strategy and

governance in producing and defining the frontier of enterprise performance of all sorts,

including resilience, robustness, sustainability and financial performance and impact so that

SEER2 presumes that triple top line enterprise governance and strategy intersecting

governmental and societal requirements and expectations are deployed and transformed through

people, processes, partnerships, and policies that produce triple bottom line societal, ecological,

financial, and other performance and impact.

Data analytics, intelligence and supply chain proficiency

The broad data-driven decision-making domain of technologies, applications, and processes for

gathering, storing, assessing, analyzing and activating is often referred to as business intelligence

(Chauduri et al., 2011). Enterprise excellence models have long advocated business intelligence

and management as a means of advancing whole system optimization. The game changing

disruption however, is integration of business intelligence with so-called “big data”. Hallmarks

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of big data (McAfee and Brynjolfsson, 2012) include richer and more numerous data sources;

massive data volume and variety; and quantum leaps in analytic capability and graphic intricacy

that enable discovery, characterization, and management of complex patterns and interactions

that in turn produce strategic intelligence (Kuosa, 2013). The big data era is a result of dramatic

and persistent advances in data storage capacity and processing speed that has long followed

Moore’s law (Schaller, 1997).

In part the role of big data is to support strategic intelligence that enables organizations to

operate differently and more intelligently than their competitors, thus providing additional

avenues to resilience and robustness through delivery of highly efficient, effective, rapid and

customized translation of data into intelligence, intelligence into foresight, and foresight into

value (LaValle et al., 2011). This has motivated a transition away from traditional (small) data

driven decision making toward a blend of tradition with increasing leverage of vastly more

complex concept and computationally-intensive big data analytics that may yield mixed

quantitative, qualitative and visual forms. The power and widespread availability of big data

intelligence and analytics has intensified the importance of comprehensive data confidentiality

and security as means of rendering organizations more robust against cyber-attack and espionage

(Crane, 2005).

Big and small data analytics and intelligence along with other sense-making approaches may be

used for multiple purposes (Angus-Leppan et al., 2010), essentially all of which have the end

goal of deriving financial and other valuable impacts (Chen et al., 2012). Among these purposes

are scanning the competitive and legislative landscape, along with the cascading ones of real- or

near-real-time performance assessment, intervention in and control of associated processes,

strategy refinement and process improvement or innovation, and identification and

implementation of best and next best practices and sources of competitive advantage. Many of

these are elements of a cyclical process aimed at optimizing organization performance relative to

enterprise mission and vision. Mission and vision refers to that emphasized by a given model –

in this case sustainable enterprise excellence, resilience and robustness – and whatever means the

model employs to deliver these so that big and small data analytics and intelligence performance

drivers and results will include contextualized societal, environmental, and financial elements.

Analogous to climate change and related concerns driving sustainability, the big data megatrend

is indicative of fundamental transformation in the global economy wherein few business activity

spheres or application areas will remain untouched (McAfee and Brynjolfsson, 2012) and for

which there are already abundant supply chain management applications (Closs et al., 2011).

Application of big and small data intelligence and analytics to supply chain design and

optimization carries with it the potential to transform connected intelligence into integrated

collective intelligence. Connected intelligence is what might be referred to as “dissipative

additive” in the sense that while knowledge is summative across the chain, anything short of

perfect connectivity results in a certain amount of energy or knowledge loss. Integrated

collective intelligence is in contrast multiplicative. The former case can aid identification and

transformation of best practice into standard practice through knowledge sharing. The latter case

relies on knowledge multiplication through collection of best practice fragments collected across

the chain and recombined in ways that lead to next best practices and sources of competitive

advantage deployed more extensively across the chain to advance supply chain sustainability,

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resilience, robustness and excellence and hence also shared improvement in financial, societal

and ecological performance and impact. This illustrates one of many ways in which progress

toward SEER2 is enabled by sophisticated analytic transformation and translation of information

into actionable enterprise intelligence and foresight.

Enterprise and supply chain human ecology

Enterprise human ecology refers to the relationships between the organization and its human

capital with the social, natural, and built environments via whatever mediators are pertinent

(Lozano, 2011). In the context of SEER2 enterprise human ecology may be regarded as a natural

extension of enterprise human capital management, which has long been emphasized as a critical

enabler of enterprise excellence (Kim et al., 2010). Strategic management of this ecology to

create specific competencies based on selected cognitive abilities, behavioral traits, and

aggregate these competencies at the organizational level makes it possible for enterprises to

respond to severe shocks in a resilient manner by cultivating ambidextrous learning that enables

enterprises to exploit their existing knowledge domains while exploring new ones (Lengnick-

Hall et al., 2011). Similarly, enterprise human ecology contributes to robustness when this

ecology is configured via appropriate intellectual capital architectures emphasizing ambidextrous

learning (Kang and Snell, 2009), sustainability (Pfeffer, 2010), and enterprise excellence

(Chuang and Liao, 2010). Enterprise human ecology is vital to SEER2 primarily because it

interacts with or “pre-enables” other key enablers of SEER2. As examples, strategic human

ecology practices are central to innovation performance (Chen and Huang, 2009); supply chain

management (Ou et al., 2010); corporate governance (Sharma et al., 2011); and big and small

data analytics and intelligence where it has been noted that for all its power, and potential big

data does note erase the need for vision or human insight (McAfee and Brynjolfsson, 2012).

Innovation, social-ecological innovation, and supply chain proficiency

Sustainability has been identified as a megatrend (Lubin and Esty 2010), source of competitive

advantage (Laszlo and Zhexembayeva 2011), and documented driver of firm value (Al-Najjar

and Anfimiadou 2012). As such it is important to determine key drivers of sustainability, with

innovation documented as not only chief among sustainability enablers (Nidumolu, et al, 2009),

but also of enterprise excellence (Eccles and Serafeim, 2013), resilience and robustness

(Reinmoeller and Van Baardwijk, 2005), and hence of SEER2. We regard innovation in general

and social-ecological innovation (SEI) in particular as chief among enablers of SEER2 and as

part of that, critical to supply chain sustainability and proficiency (Oke et al., 2013).

SEI embeds innovation for sustainability (Rennings, 2000) in a culture of sustainable innovation

(Nill and Kemp, 2009). Such cultures exist when innovation is regular, rigorous, systematic,

systemic, is central to enterprise strategy, and tangibly impacts enterprise financial, societal, and

ecological performance (Edgeman, 2013). More generally, SEI weds social innovation and

institutional entrepreneurship research with research on socio-ecological systems and resilience

thinking and leverages this marriage to explicitly target social or environmental outcomes of

innovation partially enabling transformation of triple top line strategy into triple bottom line

performance. Effective implementation of innovation in enterprise excellence models positively

drives firm performance, including financial performance (Barua et al., 2001).

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We thus see that effective fusion of innovation with sustainability and enterprise excellence

provides a compounding or synergistic impact for enterprises seeking to become continuously

relevant and responsible. From a SEI perspective, innovation is relevant to the organization,

society, and the natural environment and the organization is relevant and responsible to society

and the natural environment. Positive correlation of SEI with enterprise value (Al-Najjar &

Anfimiadou 2012), affirms the profitability of strategic SEI. Proliferation of SEI throughout an

enterprise ecosystem contributes to socio-ecological resilience (Olsson & Galaz, 2011) with

large-scale SEI deployment possible through a modified form of quality function deployment

(Edgeman & Hensler, 2005).

Serious assessment of SEI performance requires understanding of what SEI is, how and in what

forms it manifests, how developed or mature it is, and how to improve future SEI strategy and

results. Edgeman and Eskildsen (2014) elaborate SEI and maturity scale based assessment

thereof via a combined graphic and narrative format referred to as a SEI News Report. Such

reports provide feedback concerning present SEI performance, while also delivering significant

foresight capable of informing future SEI strategy, priorities, processes, and activities and hence

future SEI performance. Though the SEI approach of Edgeman and Eskildsen provides 20

generic basic and advanced strategies and activities used to advance enterprise SEI performance,

the intent of their overall approach is that it should be contextualized.

Supply chain proficiency in the Springboard to SEER2 model and its assessment

Assessment of supply chain contribution to enterprise financial performance is common practice.

Supply chain relationships with governance, big data analytics and intelligence, innovation and

other SEER2 drivers are equally well established. Of more recent origin is assessment of supply

chain contribution to and impact on environmental performance (Shaw et al., 2010), society

(Hoejmose et al., 2013) and hence sustainability. In combination then, it is clear that supply

chain proficiency plays a sufficiently important role in SEER2 to merit inclusion in the

Springboard to SEER2 model and its associated assessment regimen.

Edgeman and Williams (2014) provide a Springboard to SEER2 model a model that is structured

in a manner recognizable to users of either America’s Malcolm Baldrige National Quality Award

(MBNQA) or the EFQM Model that supports the European Quality Award (EQA). While the

overall structures of these models are similar, the Springboard to SEER2 differs in terms of

specific objectives that explicitly address enterprise sustainability, resilience and robustness in

concert with enterprise excellence. Enterprise excellence is used here as a synonym for the

MBNQA term performance excellence and the EQA term business excellence. Integration of

sustainability, resilience, and robustness as enterprise objectives quite naturally leads to use of

selected enablers not used by the MBNQA or EQA models and to differences in the way that like

enablers are construed, albeit sometimes only minor or subtle distinctions.

Figure 1 provides a high-level summary of the Springboard to SEER2 model. This model

insinuates that the leadership and governance of an enterprise informs its triple top line oriented

strategy; strategy is principally executed via policies, partnerships, and processes; these in turn

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deliver triple bottom line related sustainability, resilience and robustness performance and

impact, along with more familiar enterprise excellence performance and impact.

Figure 1. Modified Springboard to SEER2 Model. Adapted from Edgeman and Williams (2014)

This model and been elaborated in greater detail (Edgeman and Williams, 2014) as have its

criteria and their assessment, presentation of assessment results, and their ability to provide the

enterprise with both feedback and foresight. Feedback provides the enterprise with a review of

its performance during the most recent appraisal cycle. In contrast, foresight supplies the

enterprise with intelligence used to inform its future strategies and actions through identification

and implementation of relevant best and next best practices and sources of competitive

advantage.

The assessment regiment for the Springboard to SEER2 consists of 24 specific criteria,

distributed as four to each of six major assessment regions. Relative to the model of Figure 1, the

first major assessment region is triple top line strategy; the second is strategy execution via

policy, processes and partnerships; and the remaining four are specific triple bottom line

performance and impact areas: financial and marketplace, sustainability, human ecology and

capital, and SEI and general innovation and continuous improvement. The four criteria assessed

for each region are symbolized by N, E, W and S, with each of these assessed relative to highly

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descriptive 0-to-10 point maturity scales. Although Edgeman and Williams (2014) chose not to

differentially weight these criteria, instead leaving weighting to enterprise competitive context,

we here note that models such as the MBNQA and EQA typically ascribe approximately 50% of

the weight to performance / impact, about 35% to process implementation and execution, and

15% to strategy, governance and leadership.

Given the common association of N, E, W and S with the primary directional points of a

compass, their use to form the word “news”, and the intent of assessment to provide both news

(feedback) and direction (foresight), Edgeman and Williams (2014) organized the assessment

results for each region into an associated graphical NEWS Compass, each augmented by a SWOT

Plot Narrative. The assembly of these across all assessed areas provides an overall assessment,

referred to as a Springboard to SEER2 NEWS Report.

The full set of 24 criteria were derived from a combined literature review and comprehensive

examination of the models, criteria, principles and approaches of the GRI, UNGC, America’s

Baldrige National Quality Award, the European Quality Award, ISO 14000, ISO 26000, and

balanced scorecard and can be found in Edgeman and Williams (2014). Of importance in the

present context is that various contributions of supply chain proficiency to SEER2 are

represented in each of the six “N” criteria, with the N criteria reported in Table 1. As such, the

perspective emerges that supply chain proficiency is integral to SEER2, and not merely

component. We see than, that supply chain proficiency is focal to triple top line strategy, is

deployed via policies, partnerships and processes, and is reflected in financial and marketplace

performance, sustainability performance, human ecology performance, and in innovation and

continuous improvement performance.

Table 1. Springboard to SEER2 Assessment Regions and Associated N Compass Points

REGION: Triple Top Line Strategy

Financial & Marketplace Strategy for SEER2 & Supply Chain Strategy

REGION: Strategy Execution Via Policy, Processes and Partnerships

Financial, Operations & Supply Chain Processes for SEER2

REGION: Financial & Marketplace Performance and Impact

Financial & Marketplace Results Traceable to Supply Chain Performance

REGION: Sustainability (SEER2) Performance and Impact with Embedded

Economic, Innovation and Analytic Impact

Sustainability Results Traceable to Supply Chain Performance & Analytics

REGION: Human Ecology & Capital Performance and Impact

Impact of Human Ecology & Capital on the Supply Chain

REGION: Social-Ecological & General Innovation, Design and Continuous

Improvement Performance and Impact

Impact of Innovation, Design & CI Across and In the Supply Chain on SEER2

13

Summary and conclusions

A classic contribution by Churchman (1967) defines a wicked problem as “that class of social

system problems that are ill-formulated, where the information is confusing, where there are

many clients and decision makers with conflicting values, and where the ramifications in the

whole system are thoroughly confusing.” Other common though not universal characteristics of

wicked challenges include association with highly charged and conflicting political, religious, or

social perspectives and the need for urgent, high stakes resolution. Similarly, Russell Ackoff

(1974) noted the inherent nature of such problems in systems populated by interacting and

inextricably knotted elements or issues. Citing numerous elements that range from climate

change and other components of ecological change to chaotic financial markets to widespread

corruption, Waddock (2013) establishes corporate leadership and governance, along with

collaboration that can include supply chain efficiency and effectiveness as critical to progress in

solving wicked (global) sustainability challenges.

It is in this vein of progress toward enterprise contributions to solution of the wicked global

sustainability challenges that Sustainable Enterprise Excellence, Resilience and Robustness

(SEER2) is evolving. While innovation is foremost regarded as critical to SEER2, attention has

been directed herein to the enabling role of supply chain proficiency in SEER2 and its

relationships to and interactions with innovation and other key enablers of SEER2. Beyond

previously cited roles and relationships, collaborative and co-creatively innovative supply chain

partnerships (Hernández-Espallardo et al., 2010) are able to advance sustainability through

greater resource efficiency (Schliephake et al., 2009) – an issue that in itself is aided by trust-

based governance (Ghosh and Fedorowicz, 2008) and enabled by big data analytics and

intelligence (Trkman et al., 2010).

These elements are embedded in the SEER2 modeling and combined narrative and analytical

assessment approaches presented herein enable not only enterprise progress toward SEER2, but

also supply chain performance as viewed through a SEER2 lens.

References

Ackoff, R. (1974), “The systems revolution”, Long Range Planning, Vol. 7, No. 6, pp. 2-20.

Al-Najjar, B. and Anfimiadou, A. (2012), “Environmental policies and firm value”, Business

Strategy and the Environment, Vol. 21, No. 2, pp 49-59.

Anderies, J., Janssen, M and Ostrom, E. (2012), “A framework to analyze the robustness of

socio-ecological systems from an institutional perspective”, Ecology and Society, Vol. 9, No. 1,

p. 18.

Angus-Leppan, T., Benn, S. and Young, L. (2010), “A sensemaking approach to trade-offs and

synergies between human and ecological elements of corporate sustainability”, Business Strategy

and the Environment, Vol. 19, No. 4, pp. 230-244.

14

Aras, G. and Crowther, D. (2008), “Governance and sustainability: an investigation into the

relationship between corporate governance and corporate sustainability”, Management Decision,

Vol. 46, No. 3, pp. 433-448.

Barua, A., Konana, P., Whinston, A. and Yin, F. (2001), “Managing e-business transformation:

opportunities and value assessment”, MIT Sloan Management Review, Vol. 43, No. 1, pp. 36-44.

Bitran, G., Gurumurthi, S. and Sam, S. (2007), “The need for third-party coordination in supply

chain governance”, MIT Sloan Management Review, Vol. 43, No. 1, pp. 36-44.

Blackwell, D. and Girshick, M. (1954), Theory of Games and Statistical Decisions, John Wiley

& Sons: New York, NY.

Bode, C., Wagner, S.M., Petersen, K.J. and Ellram, L.M. (2011), “Understanding responses to

supply chain disruptions: insights from information processing and resource dependence

perspectives”, Academy of Management Journal, Vol. 54, No. 4, pp. 833-856.

Boons, F., Montalva, C., Quist, J. and Wagner, M. (2013), “Sustainable innovation, business

models and economics performance: an overview”, Journal of Cleaner Production, Vol. 45, No.

1, pp. 1-8

Bou-Llusar, J.C., Escrig-Tena, A.B., Roca-Puig, V. & Beltran-Martin, I. (2009), “An empirical

assessment of the EFQM excellence model: evaluation as a TQM framework relative to the

MBNQA model”, Journal of Operations Management, Vol. 27, No. 1, pp. 1-22.

Box, G.E.P. and Draper, N.R. (1987), Empirical Model-Building and Response Surfaces, John

Wiley & Sons, New York.

Cachon, G. and Fisher, M. (2000), “Supply chain inventory management and the value of shared

information”, Management Science, Vol. 46, No. 8, pp. 1032-1048.

Cao, M. and Zhang, Q. (2011), “Supply chain collaboration: impact on collaborative advantage

and firm performance”, Journal of Operations Management, Vol. 29, No. 3, pp. 163-180.

Carmeli, A. and Markman, G.D. (2011), “Capture, governance, and resilience: strategy

implications from the history of Rome”, Strategic Management Journal, Vol. 32, No. 3, pp. 322-

341.

Chaudhuri, S., Dayal, U. and Narasayya, V. (2011), “An overview of business intelligence

technology”, Communications of the ACM, Vol. 54, No. 8, pp. 88-98.

Chen, H., Chiang, R.H.L. and Storey, V.C. (2012), “Business intelligence and analytics: from big

data to big impact”, MIS Quarterly, Vol. 36, No. 4, pp. 1165-1188.

15

Chen, C.J. and Huang, J.W. (2009), “Strategic human resource practices and innovation

performance: the mediating role of knowledge management capacity”, Journal of Business

Research, Vol. 62, No 1, pp. 104-114.

Christopher, M. and Peck, H. (2004), “Building the resilient supply chain”, International Journal

of Logistics Management, Vol. 15, No. 2, pp. 1-14.

Chuang, H.H. and Liao, H.U.I. (2010), “Strategic human resource management in service

context: taking care of business by taking care of employees and customers”, Personnel

Psychology, Vol. 63, No. 1, pp. 153-196.

Churchman, C.W. (1967), “Wicked problems”, Management Science, Vol. 15, No. 4, B141-

B142.

Closs, D.J., Speier, C. and Meacham, N. (2011), “Sustainability to support end-to-end value

chains: the role of supply chain management”, Journal of the Academy of Marketing Science,

Vol. 39, No. 1, pp. 101-116.

Contu, D.L. (2002), “How resilience works”, Harvard Business Review, Vol. 80 No. 3, pp. 46-

52.

Curkovic, S. and Sroufe, R. (2011), “Using ISO 14001 to promote a sustainable supply chain

strategy”, Business Strategy and the Environment, Vol. 20, No. 2, pp. 71-93.

Duit, A., Galaz, V., Eckerberg, K. and Ebbesson, J. (2010), “Governance, complexity, and

resilience”, Global Environmental Change, Vol. 20, No. 3, pp. 363-368.

Duit, A. and Galaz, V. (2008), “Governance and complexity: emerging issues for governance

theory”, Governance, Vol. 21, No. 3, pp. 311-335.

Eccles, R. and Serafeim, G. (2013) “The performance frontier: innovating for sustainable

strategy”, Harvard Business Review, Vol. 90, No. 5, pp. 4-10.

Edgeman, R. (2013), “Sustainable enterprise excellence: towards a framework for holistic data-

analytics”, Corporate Governance, Vol. 13, No. 5, pp. 527-540.

Edgeman, R., Bøllingtoft, A., Eskildsen, J., Kallehave, P. and Kjærgaard, T. (2013), ”Sustainable

enterprise excellence and the continuously relevant & responsible organization”, International

Journal of Social Ecology & Sustainable Development, Vol. 4, No. 4, 65-76.

Edgeman, R. and Eskildsen, J. (2014a), “Modeling and assessing sustainable enterprise

excellence”, Business Strategy and the Environment, Vol. 23, No. 3, pp. 173-187.

Edgeman, R. and Eskildsen, J. (2014b), “Social-ecological innovation”, in Wang, J. (Ed.),

Encyclopedia of Business Analytics and Optimization, IGI Global, Hersey, Pennsylvania, pp.

pending.

16

Edgeman, R. and Hensler, D.A. (2005), “QFD and the BEST paradigm: deploying sustainable

solutions”, World Review of Science, Technology and Sustainable Development, Vol. 2, No. 1,

pp. 49-59.

Edgeman, R. and Williams, J. (2014), “Sustainable, resilient & robust enterprise self-assessment

analytics”, The TQM Journal, Vol. 26, No. 4, pp. 368-381.

Edgeman, R., Wu., Z., Laasch, O., 2014. Operations: responsible enterprise excellence, in:

Laasch, O., Conaway, R. (Eds.), Principles of Responsible Management: Glocal Sustainability,

Responsibility, and Ethics. Cengage Publishing, Stamford, CT, USA, pp. 220-259.

Elkington, J. (1997), Cannibals with Forks: The Triple Bottom Line of 21st Century Business,

Capstone Publishing, Oxford, UK.

Elkington, J. (2006), “Governance for sustainability”, Corporate Governance, Vol. 14, No. 6, pp.

522-529.

Faisal, M.N., Banwet, D.K. and Shankar, R. (2006), “Supply chain risk mitigation: modeling the

enabler”, Business Process Management, Vol. 12, No. 4, pp. 535-552.

Foote, J., Gaffney, N. and Evans, J.R. (2010), “Corporate social responsibility: implications for

performance excellence”, Total Quality Management, Vol. 21, No. 8, pp. 799-812.

Fowler, S.J. and Hope, C. (2007), “Incorporating sustainable business practices into company

strategy”, Business Strategy and the Environment, Vol. 16, No. 1, pp. 26-38.

Ghosh, A. and Fedorowicz, J. (2008), “The role of trust in supply chain governance”, Business

Process Management Journal, Vol. 14, No. 4, pp. 453-470.

Guenster, N., Bauer, R., Derwall, J. and Koedijk, K. (2010), ”The economic value of corporate

eco-efficiency”, European Financial Management, Vol. 17, No. 4, pp. 679-704.

Gulati, R., Nohria, N. and Wohlgezogen, F. (2010), “Roaring out of recession”, Harvard

Business Review, Vol. 88, No. 3, pp 62-69.

Harrison, J.S., Bosse, D.A. and Phillips, R.A. (2010), “Managing for stakeholders, stakeholder

utility functions, and competitive advantage”, Strategic Management Journal. Vol. 31, No 1, pp.

58-74.

Helms, W. Oliver, C. and Webb, K. (2012), “Antecedents of settlement on a new institutional

practice: negotiation of the ISO 26000 standard on social responsibility”, Academy of

Management Journal, Vol. 55, No. 5, pp. 1120-1145.

17

Hernández-Espallardo, M., Rodríguez-Orejuela, A. and Sánchez-Pérez, M. (2010), “Inter-

organizational governance, learning and performance in supply chains”, Supply Chain

Management: An International Journal, Vol. 15, No. 2, pp. 101-114.

Hoejmose, S., Brammer, S. and Millington, A. (2013), “An empirical examination of the

relationship between business strategy and socially responsible supply chain management”,

International Journal of Operations & Production Management, Vol. 33, No. 5, pp. 589-621.

Jo, H. and Harjota, M.A. (2012), “The causal effect of corporate governance on corporate social

responsibility”, Journal of Business Ethics, Vol. 106, No. 1, pp. 53-72.

Kang, S.C. and Snell, S.A. (2009), “Intellectual capital architectures and ambidextrous learning:

a framework for human resource management”, Journal of Management Studies, Vol. 46, No. 1,

pp. 65-92.

Kaplan, R.S. and Norton, D.P. (1992), “The balanced scorecard: measures that drive

performance”, Harvard Business Review, Vol. 70, No. 1, pp 71-79.

Kell, G. (2012), “12 years later: reflections on the growth of the UN Global Compact”, Business

& Society, Vol. 51, No. 1, pp. 31-52.

Kim, D.Y., Kumar, V. and Murphy, S.A. (2010), “European foundation for quality management

business excellence model: an integrative review and research agenda”, International Journal for

Quality & Reliability Management, Vol. 27, No. 6, pp. 684-701.

Kuosa, T. (2011), “Different approaches of pattern management and strategic intelligence”,

Technological Forecasting and Social Change, Vol. 78, No. 3, pp. 458-467.

Lee, H.L. (2004), “The triple-A supply chain”, Harvard Business Review, Vol. 82, No. 10, pp.

102-113.

Lengnick-Hall, C., Beck, T. and Lengnick-Hall, M. (2011), “Developing a capacity for

organizational resilience through strategic human resources management”, Human Resource

Management Review, Vol. 21, No. 3, pp. 243-255.

Lopez-Cabrales, A., Pérez-Luño, A. and Cabrera, R.V. (2009), “Knowledge as a mediatory

between HRM practices and innovative activity”, Human Resource Management, Vol. 48, No. 4,

pp. 485-503.

Lozano, J. (2011), “What emerges when a market emerges?” Corporate Governance, Vol. 11,

No. 4, pp. 315-326.

Lyons, D. (1977), “Human rights and the general wealfare”, Philosophy & Public Affairs, Vol. 6,

No. 2, pp. 113-129.

18

Martinelli, A. and Midttun, A. (2010), “Globalization and governance for sustainability”,

Corporate Governance, Vol. 10, No. 1, pp. 6-17.

Maxwell, D., Sheate, W. and van der Vorst, R. (2006), “Functional and systems aspects of the

sustainable product and service development approach for industry”, Journal of Cleaner

Production, Vol. 14, No. 7, pp. 1466-1479.

McAfee, A. and Brynjolfsson, E. (2012), “Big data: the management revolution”, Harvard

Business Review, Vol. 90, No. 10, pp. 60-66.

McDonough, W. and Braungart M. (2002a), “Design for the triple top line: new tools for

sustainable commerce”, Corporate Environmental Strategy, Vol. 9 No. 6, pp. 251-258.

McDonough, W. and Braungart, M. (2002b), Cradle to Cradle: Remaking the Way We Make

Things, North Point Press, New York.

Nacol, E.C. (2011), “The risks of political authority: trust, knowledge and political agency in

Locke’s Second Treatise”, Political Studies, Vol. 59, No. 3, pp. 580-595.

New, M., Liverman, D., Schroder, H. and Anderson, K. (2010), “Four degrees and beyond: the

potential for a global temperature increase of four degrees and its implications”, Philosophical

Transactions of the Royal Society A, Vol. 369, No. 1934, pp. 6-19.

Nill, J. and Kemp, R. (2009), “Evolutionary approaches for sustainable innovation policies: from

niche to paradigm?” Research Policy, Vol. 38, No. 4, pp. 668-680.

Oke, A., Prajogo, D.I. and Jayaram, J. (2013), “Strengthening the innovation chain: the role of

internal innovation climate and strategic relationships with supply chain partners”, Journal of

Supply Chain Management, Vol. 49, No. 4, pp. 43-58.

Olsson, P. and Galaz, V. (2011), “Social-ecological innovation and transformation”, in: Nichols,

A., Murdoch, A. (Eds.), Social Innovation: Blurring Boundaries to Reconfigure Markets.

Palgrave MacMillan, London, pp. 223-247.

Ou, C.S., Liu, F.C., Hung, Y.C. and Yen, D.C. (2010), “A structural model of supply chain

management on firm performance”, International Journal of Operations & Production

Management, Vol. 30, No. 5, pp. 526-545.

Pfeffer, J. (2010), “Building sustainable organizations: the human factor”, The Academy of

Management Perspectives, Vol. 24, No. 1, pp. 34-45.

PricewaterhouseCoopers (2013), Making the Right Risk Decisions to Strengthen Operations

Performance, PwC/MIT Forum for Supply Chain Innovation Research Study, Boston, MA.

Rasche, A. and Gilbert, D.U. (2012), “Institutionalizing global governance: the role of the United

Nations Global Compact”, Business Ethics: A European Review, Vol. 21, No 1, pp. 100-114.

19

Reinmoeller, P. and Van Baardwijk, N. (2005), “The link between diversity and resilience”, MIT

Sloan Management Review, Vol. 46, No. 4, pp. 61-65.

Robinson, J. (2004), “Squaring the circle: some thoughts on the idea of sustainable

development”, Ecological Economics, Vol. 48, No. 4, pp. 369-384.

Sachs, J. (2012), “From Millennium Development Goals to Sustainable Development Goals”,

Lancet, Vol. 379, pp. 2206-2211.

Samson, D. and Terziovski, M. (1999), “The relationship between total quality management

practices and operational performance”, Journal of Operations Management, Vol. 17, No. 4, pp.

393-409.

Schaller, R.R. (1997), “Moore’s law: past, present and future”, IEEE Spectrum, Vol. 34, No. 6,

pp. 52-59.

Scherer, A. and Palazzo, G. (2011), “The new political role of business in a globalized world: A

review of a new perspective on CSR and its implications for the firm, governance, and

democracy”, Journal of Management Studies, Vol. 48, No. 4, pp. 899-931.

Schliephake, K., Stevens, G. and Clay, S. (2009), “Making resources work more efficiently: the

importance of supply chain partnerships”, Journal of Cleaner Production, Vol. 17, No. 14, pp.

1257-1263.

Scholz, R., Blumer, Y. and Brand, F. (2012), “Risk, vulnerability, robustness, and resilience

from a decision-theoretic perspective”, Journal of Risk Research, Vol. 15, No. 3, pp. 313-330.

Sharma, S., Sharma, J. and Devi, A. (2011), “Corporate social responsibility: the key role of

human resources management”, Human Resource Management: Issues, Challenges and

Opportunities, 9.

Shaw, S., Grant, D.B. and Mangan, J. (2010), “Developing environmental supply chain

performance measures”, Benchmarking: An International Journal, Vol. 17, No. 3, pp. 320-339.

Sheth, J.M., Sethia, N.K. and Srinivas, S. (2011), “Mindful consumption: a customer-centric

approach to sustainability”, Journal of the Academy of Marketing Science, Vol. 39, No. 1, pp.

21-39.

Smith, A., Stirling, A. and Berkhout, F. (2005), “The governance of sustainable socio-technical

transitions”, Research Policy, Vol. 34, No. 10, pp. 1491-1510.

Smith, J.E., and Winkler, R.L. (2006), “The optimizer’s curse: skepticism and postdecision

surprise in decision analysis”, Management Science, Vol. 52, No. 3, pp. 311-322.

20

Souza, G. (2013), “Closed-loop supply chains: a critical review and further research”, Decision

Sciences, Vol. 44, No. 1, pp. 7-38.

Surroca, J., Tribó, J.A. and Waddock, S. (2010), “Corporate responsibility and financial

performance: the role of intangible resources”, Strategic Management Journal, Vol. 31, No. 5,

pp. 463-490.

Sydow, J. and Frenkel, S.J. (2013), “Labor, risk, and uncertainty in global supply networks:

exploratory insights”, Journal of Business Logistics, Vol. 34, No. 3, pp. 236-247.

Teece, D.J. (2007), “Explicating dynamic capabilities: The nature and microfoundations of

(sustainable) enterprise performance”, Strategic Management Journal, Vol. 28, No. 13, pp.

1319-1350.

Teece, D.J. (2010), “Business models, business strategy and innovation”, Long Range Planning,

Vol. 43, No. 2, pp. 172-194.

Trkman, P., McCormack, K., De Oliveira, M.P.V. and Ladeira, M.B. (2010), “The impact of

business analytics on supply chain performance”, Decision Support Systems, Vol. 49, No. 3, pp.

318-327.

Tsay, A. (1999), “The quantity flexibility contract and supplier-customer incentives”,

Management Science, Vol. 45, No. 10, pp. 1339-1359.

United Nations (2013), A New Global Partnership: Eradicate Poverty and Transform Economies

Through Sustainable Development, United Nations Publications, New York.

Waddock, S. (2013), “The wicked problems of global sustainability need wicked (good) leaders

and wicked (good) collaborative solutions”, Journal of Management for Global Sustainability,

Vol. 1, No. 1, pp. 91-111.

Walls, J.L., Berrone, P. and Phan, P.H. (2012), “Corporate governance and environmental

performance: is there really a link?” Strategic Management Journal, Vol. 33, No. 8, pp. 885-913.

Wang, H., Qian, C., 2011. Corporate philanthropy and corporate financial performance: The

roles of stakeholder response and political access. Academy of Management Journal. 54, 6,

1159-1181.

Wu, Z., Edgeman, R., Laasch, O., 2014. Supply chain: responsible supply and demand, in:

Laasch, O., Conaway, R. (Eds.), Principles of Responsible Management: Glocal Sustainability,

Responsibility, and Ethics. Cengage Publishing, Stamford, CT, USA, pp. 260-299.

Zadek, S. (1999), “Stalking sustainability”, Greener Management International, pp. 21-31.