JOSCM - Journal of Operations and Supply Chain Management – Vol. 10, n. 1 - Jan/Jun 2017

1 JOSCM | Journal of Operations and Supply Chain Management | FGV EAESP
SPECIAL ISSUE
Invited article
DOI: http:///dx.doi/10.12660/joscmv10n1p01-02
ADVANCES IN SUPPLY CHAIN AND LOGISTICS
MANAGEMENT FOR A MORE SUSTAINABLE SO-
CIETY: AN INTRODUCTION
Ernesto DR Santibanez Gonzalez
santibanez.ernesto@gmail.com
Professor at Universidad de Talca, Facultad de Ingeniería – Talca, Chile
Charbel J. C. Jabbour
c.j.chiappettajabbour@stir.ac.uk
Professor at University of Stirling, Stirling Management School – Stirling – Scotland, UK
ISSN: 1984-3046© joscm | São Paulo | V. 10 | n. 1 | Jan-June 2017 | 01-02

2 AUTHORS | Ernesto DR Santibanez Gonzalez | Charbel J. C. Jabbour
As part of the concern for achieving a more sustain-
able society, to effectively adopt the triple bottom line
(TBL) approach has become one of the major chal-
lenges that organizations have been facing. Increas-
ing customer’s awareness and stronger regulations
have been pressing organizations to balance econom-
ics objectives, with social and environmental (TBL)
concerns in order to effectively contribute to a more
equitable and carbon neutral society. Researchers and
practitioners are looking for solutions that can sup-
port decision makers in the complex task of address-
ing sustainable issues. In the recent past, an increas-
ing number of papers had focused in the sustainability
domain, proposing assessment tools, analytical mod-
els and solution tools to support decision makers.
A real integration of the three TBL’s dimensions is a
necessity in the contemporary society, however there
is an evident lack of research on how products, pro-
cess and business models need to be re-shaped in this
challenging sustainability setting, as well as how de-
scriptive models and quantitative approaches have to
be re-build or enhanced to tackle the aforementioned
challenges. Supply chain and logistics management
are areas that have an inevitable huge potential to
contribute with cutting-edge solutions in order to
tackle the myriad of complex problems that organiza-
tions have been facing when pursuing sustainability
and low-carbon strategies.
Analytical models, empirical studies, case-based stud-
ies, and solution approaches that can effectively man-
age the balances, and synergies associated with the
integration of economics, environment and social
perspectives into traditional decision making pro-
cesses are the focus of this special issue.
The aim of this special issue was to publish cutting-
edge research capable of dealing with key topics in
supply chain and logistics management for sustain-
ability, by proposing tools so that managers and deci-
sion-makers will be able to build up a more equitable,
sustainable, and carbon zero society. The special is-
sue offers a unique opportunity to be in contact with
recent developments in sustainable operations. The
manuscripts that are part of the Special Issue are:
• Locating operations in high labor cost countries –
Eevidence from Spain, by Angel Diaz and Elcio
Mendoça-Tachizawa, which provides empirical
evidence of the location of manufacturing and
services in the context of a European country
(Spain), exploring the drivers, social implications
and organizational theories that can explain it.
Based on four Spanish companies, this paper
analyzes possible operational responses that can
incentive job creation and bringing back jobs lost
to offshoring.
• Comparing Madrid and Salvador GHG emission
inventories: Implications for future researches, by
José Celio Silveira Andrade, Andrea Dameno,
Javier Pérez, Juan Manuel de Andrés, and Julio
Lumbreras. The research aimed at comparing the
Greenhouse Gas (GHG) emission inventories of
Madrid and Salvador, with implications for mul-
tiple stakeholders.
• Scanning insights on sustainability and supply
chain management in Brazil, by Minelle E. Silva,
Morgane M. C. Fritz, and Breno Nunes, aims at
analysing how the publications in Brazil are con-
sidering the relationship between sustainability
and supply chain management.
• Sustainable operations management and bench-
marking in brewing: A factor weighting approach,
by Dan P. Bumblauskas, sheds light on sustain-
able brewery performance and establish com-
mon metrics for sustainability in the beer sup-
ply chain. Ten criteria are proposed to assess
environmental and sustainable practices in four
brewery companies. Criteria include donations
to environmental/social causes and community
involvement, transparency, employee sustain-
ability culture/benefits to employees for ‘green’
behaviour, greenhouse gas (GHG) emissions,
water conservation and reuse, energy consump-
tion, energy intensity, and waste diversion rates,
among others.

SPECIAL ISSUE
Submitted 20.07.2016. Approved 07.03.2017.
Evaluated by double blind review process.
Scientific Editors: Ernesto Santibanez Gonzalez and Charbel Jabbour
LOCATING OPERATIONS IN HIGH LABOR COST
COUNTRIES – EVIDENCE FROM SPAIN
ABSTRACT
The location of operations in high labor cost countries is increasingly discussed in
the media, in part for recent declarations and actions from the president of USA,
Donald Trump. While this particular instance can be labeled as populist or protec-
tionist, the factors underlying the debate are extremely important: advances in sys-
tematic increases in productivity, low population growth, and the transfer of jobs
to countries with lower labor costs are creating unemployment and underemploy-
ment in developed countries that could eventually result in protectionism and re-
strictions to free trade. This phenomenon has enormous social and economic impli-
cations, and has attracted considerable interest from researchers. In particular, this
study provides empirical evidence of the location of manufacturing and services in
the context of a European country (Spain), exploring the drivers, social implications
and organizational theories that can explain it.
KEYWORDS | Outsourcing, location decision, reshoring, offshoring, inshoring.
Angel Diaz
angel.diaz@ie.edu
Professor at IE Business School – Madrid, Spain
Elcio Mendonça Tachizawa
elcio.mendonca@uc3m.es
Professor at Universidad Carlos III de Madrid – Madrid, Spain

4 AUTHORS | Angel Diaz | Elcio Mendonça Tachizawa
INTRODUCTION
In this study, we provide empirical evidence drawn
from multiple industries in Spain on the factors that
affect the decision of locating operations in high labor
cost countries (HLCC, defined in this study as coun-
tries belonging to the OECD - Organisation for Eco-
nomic Co-operation and Development). Moreover,
we present some enablers of the decision of locating
operations in HLCC, i.e. factors that allow that such
location to have an impact on firm performance.
The literature on industrial location has tradition-
ally focused on reducing production costs, especially
those related to labor. However, recent localizations
in HLCC’s contradict such paradigm. For example,
labor costs in the auto sector in Spain are around
25 Euros per hour, 5 times higher than Romania
and almost 8 times higher than China (Expansión
2013). Nevertheless, the Almussafes industrial park
of Ford, in Spain, has become a role model for other
factories of Ford, soon to become its largest factory
in Europe and a global innovation hub of the firm (El
País, 2015). How can we explain that?
The economic recession, an increased emphasis on
sustainability, and higher customer expectations
for flexibility and cost performance drove firms to
reconsider their location decisions. Recently, a Bos-
ton Consulting Group study concluded that over one
third of large manufacturers are considering relocat-
ing their manufacturing activities in HLCC (Sirkin et
al., 2011). High oil prices, increased transportation
costs and the perception of global supply chain risk
have contributed to move production to HLCC (Tate,
2014). The trend encompasses not only big firms,
or cost-focused ones; it also is being perceived by
small firms and technological-focused ones (Gray et
al., 2013). Firms have moved activities to low-wage
countries based on easily measured costs, and have
returned to their home countries after experiencing
the risks associated e.g. delivery delays, communica-
tion problems, intellectual property issues, etc (Gray
et al, 2013). In a nutshell, the key premise behind
bringing operations to HLCC’s is that closeness to
product design, reduced order cycles and lower costs
of carrying inventory in the pipeline should offset
higher absolute production costs (Shih, 2014).
The location of operations in HLCC’s has been as-
suming increasing importance also for national gov-
ernments. For instance, the new Trump administra-
tion in US is focusing on mechanisms to stimulate
firms to locate their operations in the US rather
than low-cost countries. France has developed spe-
cific software (Colbert 2.0 -Direction Générale des
Enterprises, 2015), that allows companies to assess
whether they are better off producing in France.
However, while the literature on locations decisions
in specific countries or regions is large and diverse
(Ketokivi et al. 2017), empirical evidence is less
common in the academic literature. This may occur
because firms are reluctant to make their mistakes
public, and the fact that location decisions do not
constitute an item that has to be registered in of-
ficial data bases (Martinez-Mora & Merino, 2014).
Tate (2014) argues that research lacks empirical evi-
dence that allows analyzing the factors explaining
HLCC location. Actually, the trend is so recent that
there is little empirical evidence on the factors that
enable such decisions to effectively generate an in-
crease in firm performance (Martinez-Mora and Me-
rino, 2014). Furthermore, most of research on this
area has a US-centric perspective, lacking data from
other countries (Tate, 2014). One of the objectives
of this study is to help fill this gap in empirical re-
search, particularly because recent research suggests
that there may be changes in the importance of vari-
ous factors affecting the manufacturing location de-
cision (Ellram et al, 2013).
Thus, the main academic contribution of this study
is to provide empirical evidence of decisions on the
location of operations in the context of a European
country (Spain), exploring its drivers and enablers.
The theoretical framework used in the study is de-
picted in Figure 1.
Figure 1. Theoretical framework
DRIVERS HLCC LOCATION PERFORMANCE
ENABLERS
The paper is structured in the following way: First, we
provide a brief literature review on location decisions,
with special emphasis in HLCC’s. Then, we present
a case analysis of location decisions in four Spanish
and multinational firms, contrasting them under the
theoretical lens of organizational theories. Finally, in
the last part of the paper we discuss the social conse-

5ARTICLES |Locating Operations in High Labor Cost Countries – Evidence from Spain
quences of location decisions in the context of devel-
oped countries, and provide some policy implications.
RESEARCH BACKGROUND
There are many theories that have been used to ex-
plain manufacturing location decisions, such as
Transaction Cost Economics (Williamson, 2008) or
the Internalization theory in the make-or-buy deci-
sion (Coase, 1937). The classical theory of interna-
tional trade bases this decision on the differences of
production costs between countries, factor endow-
ment, or transportation costs. Other factors include
the “economies of agglomeration”, where firms clus-
ter together to enjoy advantages of skilled labor,
favorable climate, etc (Martinez-Mora and Merino,
2014). However, previous studies generally focused
on Western nations establishing subsidiaries in
low-wage countries (Gray et al, 2013), thus neglect-
ing the manufacturing location in HLCC’s. After a
diminishing interest in the manufacturing location
decision literature in the last decades, this area has
re-emerged with a new focus. Whereas previous re-
search focused on low labor cost, today it is focused
on value creation (Ellram et al, 2013).
In this study, we use the eclectic theory of interna-
tional production (Dunning, 1988, 1998), because,
differently from previous theories, it is focused on
international location decisions. More specifically,
it investigates “whether a firm should internalize
its intermediate product markets within its home
country or in a foreign country, and the outcome
of this choice is primarily determined by the costs
and benefits of adding value to these products in
the two locations” (Dunning, 1988, p. 45). In his
theory, Dunning categorizes the location factors in
four types: resource seeking advantage (availabil-
ity of raw materials and infrastructure), marketing
seeking advantage (access to domestic markets),
efficiency seeking (production cost-related factors,
industry clusters and removal of trade barriers),
and strategic asset seeking advantage (knowledge-
related assets and synergies).
Why to locate operations in HLCC?
Contrary to the commonly studied location in low-
cost countries, several examples of location in HLCC
have attracted the interest of the media recently. For
example, the repatriation of textile and footwear in-
dustry in Spain, as well as the call centers of main
Telecom firms from Latin America (Martinez-Mora
and Merino, 2014); General Electric (Tate, 2014);
and some Macintosh lines of Apple (Gray et al, 2013).
Grayetal.(2013)identifiedtwomainresearchstreams
that deal with location decisions of operations: the In-
ternational Business literature (Dunning, 1980), and
the make-or-buy decision (Williamson, 1991). In both
cases, there is vast literature analyzing the multiple
factors that affect such decisions.
Location decisions are usually justified by labor costs
(Tondolo, Kaynak, de Souza, & Bitencourt, 2011).
However, increases in transportation costs, stagna-
tion of infrastructure, and labor cost differential
changes could hinder decisions of location purely
based on the low cost of labor. Moreover, most of the
literature focuses on a few elements of cost (e.g. trans-
portation and manufacturing costs in García & Díaz
(2012)), but actual costs of location decisions can be
much higher than imagined by managers. For exam-
ple, Platts & Song (2010) performed an extensive cost
analysis of sourcing from China that included set-up
costs, extended price, administrative, logistics, inven-
tory, quality and supplier management costs. These
trends are motivating firms to redesign their supply
chains in the developed world, in order to remain cost
competitive and in this way avoid offshoring.
In addition, proximity to local production networks
provides important operational advantages. For
example, it favors logistics responsiveness, reduc-
ing on-transit inventory and transportation costs
and improving lead times. Being close to suppliers
reduces the length of ordering cycles, enabling com-
panies to respond more quickly to market changes
(Shih, 2014). Furthermore, Jain, Girotra & Netess-
ine (2013) found that a 10% shift in sourcing from
domestic to global suppliers increases the inventory
investment by 8.8%. Having a supply chain close to
the final consumer also favors communication and
reduces complexities associated with global net-
works. For example, Lenovo, formerly a subcontrac-
tor of IBM, surprised the business world when it
acquired in 2005 the laptop unit of IBM (The Wall
Street Journal, 2012b). Facing a declining and quick-
ly changing market, the company has decided to fol-
low a contrary path to most electronic producers by
increasing vertical integration to 50% (from around
30%) to reduce lead times. In a striking similar com-
ment to those of the founder of Inditex, Amancio
Ortega (case analyzed below), CEO Yuanquin has
declared that “selling PCs is like selling fresh food”.
Location in HLCC’s also favors flexibility, because it

is associated with proximity to consumer markets
and lower lead times. The results reveal that this
phenomenon is a response to changes in the market,
which is demanding smaller batches in shorter time
frames (Martinez-Mora and Merino, 2014). Such
constraints limit production in low-wage countries,
because firms in these countries often require large
production lots, in order to obtain economies of
scale. Also, local operations facilitate access to local
markets, and the prompt identification of consumer
trends that would be hard to identify if production
was in other countries (Gray et al, 2013).
Other factors in HLCC location decisions include more
intangible factors. For example, supply chain risks.
Risk and vulnerability are implicit in all operations,
but are particularly critical when they extend beyond
the borders of the firm. According to Wagner & Bode
(2008), “modern supply chains seem more vulnerable
than ever”, citing recent crisis and catastrophes that
have impacted supply chains world-wide, both man-
made (e.g. terrorist attacks) and natural (e.g. hurricane
Katrina). Kumar et al. (2009) have analyzed supply
chain risks, proposing a classification of causes that
include country risks (e.g. political instability), repu-
tation (as in the Corporate Social Responsibility cases
mentioned below), strategic, operational, credit (recov-
ery of accounts receivable) and of compliance (laws and
regulations). Moreover, by locating in HLCC’s, firms
can decrease the risks related to losing control of intel-
lectual property, or positively affecting product quality
and brand image (Tate, 2014). We can add to these the
cultural risks. Cultural differences among countries
and groups have been considered by some authors as
an argument against placing operations away from
consumer markets, culture being here defined as “the
collective programming of the mind distinguishing the
members of one group or category of people from oth-
ers” (Hofstede, 2010). Likewise, Metters (2008) cites
studies reporting cultural differences as a major prob-
lem in manufacturing location.
Moreover, productivity and innovation can be im-
proved by locating operations in HLCC’s. A common
thread of research on the formation of networks (Brito
& Carvalho, 2014) is related to knowledge diffusion,
firstly proposed by Marshall over a century ago. The
effect can be both positive and negative. For example,
Fischer, Scherngell & Jansenberger (2009) reported a
disproportional co-location of patent citations, as evi-
dence of localized knowledge spillovers, and Christoph
(2005) analyzed labor poaching in the German high
tech industry. The effect of governmental policy and
proximity to higher education institutions on the cre-
ation of high-tech clusters is another example (Breto-
nès & Scheel 2011; Frenkel, Shefer & Roper, 2003;
Woodward, Figueiredo & Guimarães, 2006).
Finally, new trends such as sustainability are encour-
aging location in HLCC. One factor is related to the
increasing standardization of sustainability regu-
lation over global supply chains, which dissuades
firms from seeking less restrictive legal environ-
ments (Gray et al, 2013). More importantly, loca-
tion in countries with low labor costs can increase
reputation risks (and implicit customer backlash)
due to unethical practices at remote suppliers, as the
recent case of the tragic death of over 100 workers
at a supplier factory in Bangladesh of garments for
Walmart and others dramatically show (The Wall
Street Journal, 2012c). Also, it can increase the risks
of indirectly supporting slave or child labor in oth-
er supplier countries, together with environmental
degradation, or support of dictatorships, with sig-
nificant damages to corporate image. Thus, firms are
encouraged to avoid offshoring and engage in local
operations. After all, it is easier for buying firms to
control the sustainability of their supply chains in
their own country (Tachizawa & Wong, 2014).
When it makes sense to locate operations
in low-wage cost countries
Locating operations in mature economies is not natu-
rally without caveats, making offshoring a desirable op-
tionforgiventypesofindustries.Astrongdeterminant
of global network design is corporate taxation. While
corporate tax in the USA (federal plus local) is about
40%, it is only 26% in Canada, 30% in Mexico, 25% in
China (down from 30%), 30% in Spain, 18% in Switzer-
land,12.5%inIreland,andevenzeroinfiscalparadises,
or very small with taxation loops (KPMG, 2013). Thus,
setting part of the operations in a country that offers
better fiscal conditions make fiduciary sense for large
corporations. Companies such as Apple and Google
reportedly pay little in corporate taxes by using such
loops, but in at least one high profile case (Starbucks)
the company has agreed to increase their tax payments
due to public backlash (Bloomberg, 2013).
Low labor cost is still another important consider-
ation in offshoring decisions, especially in labor-
intensive industries (e.g. textiles and electronic as-
sembly). For instance, in the 2011 survey of primary
textile (Werner International, 2012) the hourly la-
bor cost in Switzerland is almost $50, compared to

$2.1 in China (and over $18 in Spain, where some
textile firms manage to stay highly competitive – see
case Inditex, further in the text).
There are as well operational reasons to offshore op-
erations. Wharton Professor Mauro Guillen (Knowl-
edge@Wharton, 2011) cites the example of the
Spanish maker of cigarette lighters Cricket, which
operates three factories - one in Spain, one in India
and a third in China. Although labor costs are high-
er in Spain, the per-unit production costs are lower
than in China as the plant is fully automated. Still,
the company keeps the plant in China to facilitate
filling orders for customized lighters, as it is cheaper
to retool in China where the lines are not automated.
Lastly,anotherfactorthatjustifieslocatinginlow-wage
countries occurs when the supply base is located in
other countries. For industries such as electronics, that
means a global shift of the supply base towards China.
In such industries, moving production to a country
such as the United States often means a manager will
face a weak supply base. For example, in the United
States, there are no domestic suppliers of touchscreen
displays or batteries, and most of the circuit boards and
components had to come from abroad as well. This im-
plies higher logistics costs than if the phone had simply
been assembled in Asia (Shih, 2014).
METHODOLOGY
In this study, we use a multiple case study method-
ology. Case research is being increasingly used to
study industrial location. Gray et al (2013) argue
that public secondary data is difficult if not impos-
sible to obtain, and standard surveys face difficulty
disentangling decision biases and actual costs. On
the other hand, in-depth case studies are necessary
to facilitate an understanding of the context and real
drivers of location decisions (Gray et al, 2013). Fur-
thermore, Ellram et al (2013) make a call for more
case research that indicates that more strategic fac-
tors such as value capture are becoming a more im-
portant issue than cost savings.
In order to add more empirical evidence to the re-
search field, we provide four examples from firms op-
erating in Spain, a HLCC and particularly interesting
country to focus on, for several reasons: The country
is suffering the aftereffects of a financial and banking
crisis, and a housing bubble explosion that has created
an unprecedented 26% unemployment rate (reduced
now to about 19%, but much higher for those under
25). Thus, trying to understand mechanisms for the
location of operations in HLCC (and the implicit cre-
ation of employment) is a critical priority for Spain.
In this study, we analyze four cases in different in-
dustries that have located or expanded operations in
Spain. The firms have different sizes and strategical
priorities, in order to have a more complete picture
of location of operations in a HLCC. Two of the cases
(NGA and CHEP) are service companies, and two
(Ford and Inditex) manufacturing companies, and
all have been able to create, attract, or keep opera-
tions to the country, creating employment in spite
of the crisis. All cases have been documented from
secondary data available in Internet and from per-
sonal communications with the companies by the
authors and extended semi-structured interviews in
the cases of NGA and CHEP.
In our study, a driver is a factor that affects the de-
cision of locating operations in HLCC’s (e.g market
pressures). In addition, an enabler is a factor that
facilitates that such location have an impact on firm
performance (e.g. R&D investments). Accordingly,
Table 1 synthesizes the drivers for locating operations
in Spain identified in the cases. The drivers are classi-
fied according to the typology proposed by Dunning’s
(1998) eclectic theory of international production. Fi-
nally, Table 2 depicts the enablers that were identified
in the study. The enablers are divided according to the
stakeholders that are affected in each case.
Table 1. Drivers for HLCC location
Firm Type of driver (Dunning, 1998) Driver
NGA Human
Resources
Resource-seeking
• High availability of skilled workers, with low local
demand for such resources
• Low cost of living compared to big European cities
Market-seeking -
Efficiency-seeking Same time zone as Europe
Strategic asset-seeking Cultural affinity to European consumer market

CHEP
Resource-seeking
• Low employee rotation
• Availability of skilled workers, with low local demand
for such resource
Market-seeking -
Efficiency-seeking -
Strategic asset-seeking
• Madrid as a center of excellence
• Previous existence of planning and financial teams in
Madrid
Inditex
Resource-seeking -
Market-seeking
Proximity to consumer markets allows prompt detection
of demand patterns
Efficiency-seeking
• Need to reduce lead time
• Unstable, hard-to-forecast demand
• Low labor intensity
High capacity of response / flexibility due to proximity of
suppliers
Almussafes
industrial park,
Ford
Resource-seeking Proximity to suppliers
Market-seeking Geographical proximity to consumer markets
Efficiency-seeking Labor unions moderation and flexibility
• Cultural affinity to consumer markets
• Competitive auto parts industry
Table 2. HLCC location enablers
Firm Stakeholder Enabler
NGA Human
Resources
Employees
• High unemployment level decreases employee turnover
• High quality of life incentivizes labor force to stay in the region
Universities
• University with an active participation in Erasmus program
• High quality of courses in the Language area
CHEP
Employees
• High unemployment
• High quality of life
• High unemployment level lowers employee turnover
• Competitive salaries and soft benefits
Universities Erasmus Exchange program
Inditex
Suppliers Close relationship with local suppliers
Universities Close ties with local universities
Almussafes
industrial park,
Ford
Universities Heavy R&D investments
Government Local government support
NGA Human Resources
NGA Human Resources, a Human Resources service
company (part of group Northgate - http://www.
ngahr.com), originally centralized in Poland its tech-
nical back-office for Europe, Middle East and Africa.
But the location had its caveats: it took 3-4 years to
train the workers (initially through conventional
training, then on-the job training with mentoring)
only to see them leaving, resulting in high employee
turnover. The company then relocated their service
hub to Granada, Spain, where the advantages of
lower employee rotation and know-how more than
offset higher labor cost. NGA Human Resources has
expanded their Granada operations from 15 employ-
ees to more than 500, plus 100 more in a back-office

related organization. Talent availability for this type
of service center that requires skilled workers is criti-
cal, and Granada has a multicultural university that
provides technical training and graduates with good
language skills. Technical and language expertise
are partially due to the European exchange program
Erasmus (Granada is one of the most active univer-
sities in this program) and the high quality of its
courses in the language area (El Mundo, 2015). High
unemployment levels and a labor force who wants
to stay in the region due to the high quality of life
also help to minimize turnover. Although offshoring
activity in the sector is high, competition for global
resources that are not backed by strong brand name
(as NGA Human Resources feels was their case, vis-
à-vis the likes of Microsoft or Google) is fierce, and
there is currently little competition for these re-
sources in Granada. There are also many advantages
in the location for serving the European market:
cultural affinity, less change management and su-
pervision required, and same time zone. The advan-
tages of the larger Spanish cities (Madrid, Barcelona)
would be less significant in this particular case, due
to higher cost of living and more local competition
for resources.
CHEP
CHEP is the world leader in the pooling of pallets
(readily recognized by being painted blue on the
side) and containers. The company, owned by Bram-
bles Limited, an Australian company, employs 7700
persons, owns over 285 million pallets and contain-
ers, and has over 300,000 customers in more than
50 countries. With 440 service centers, it performs
over 2.5 million movements of pallets and contain-
ers every day.
García and Díaz (2012) described the transforma-
tion of the European unit of CHEP, from a country-
based organization, to a pan-European organization.
As a result of this reorganization, strategic, tactical
and operational activities, that were performed lo-
cally at each European country, were centralized in
Madrid, where 50% of the European staff is located
(the other half reports to Madrid but is decentral-
ized at the country base as this allow proximity to
markets and improvements in sales and operations
-S&OP). CHEP Europe has also recently centralized
the execution of transportation for all of Europe, the
last function that remained decentralized; relocated
some seventy additional specialized staff to Madrid.
Among the reasons argued for the centralization
of operations in Spain are the previous existence
of planning and financial teams in Madrid, which
operated as a center of excellence, assuring control
and supervision for the next processes to be central-
ized, especially activities critical for their impact on
customer service. The availability of skilled labor in
Madrid is cited as another location factor, as young
workers with higher education and languages exper-
tise, in a country with high unemployment, find mo-
tivating the opportunity to work in an international
company that offers progression opportunities.
The Department of Transport Execution required
that a significant percentage of the new employees
were natives of the country they were to serve, and
the student exchange program Erasmus facilitated
the recruiting of international workers, as many
participants in this program welcomed the oppor-
tunity to stay in Spain after finishing their studies.
The country and the city quality of life are frequently
mentioned as differential elements in international
recruitment.
The company recognizes that the economic situation
in Spain makes employee rotation to be very low,
and that this circumstance can change in the future.
However, the company expects that offering com-
petitive salaries and other soft benefits will make
these workers stay:
“a good working environment, opportunities
to grow here or in the 50 countries where we
operate, sustainability message, Corporate
Social Responsibility policies…”.
The company did analyze alternative location for the
centralized functions (particularly in Eastern Eu-
rope), but were dismissed due to issues with recruit-
ment. The company cites data from the Economist in
which over 40% of Polish or Hungarians companies
have difficulties in filling jobs, while the same figure
for Spain is less than 15% (The Economist, 2015).
Inditex/Zara
In a sector (garments) traditionally characterized by
offshore production, Inditex has adopted a different
approach. Zara, the flagship company of the Inditex
group, consists of a network of producers in a con-
centrated area (Northern Spain) that allows the com-
pany to respond more quickly and with more flex-
ibility than its competitors. This Spanish integrated

manufacturer-retailer of apparel has been defined as
‘Armani for the masses’ (Díaz & Solís 2002). Sales
and profits make Inditex/Zara one of the largest and
most successful fashion companies in the world. Net
profits of Inditex were 2.36 billion Euros in 2012,
out of sales of 15.9 billion Euros, both registering
growths of 16% with respect to 2011.
Flexibility is key in Zara’s business model. It launch-
es over 100 collections per year (11,000 new gar-
ments) and has a total design-to-store cycle time
of less than 4 weeks. Interestingly, driven by “fast-
fashion" retailers like Zara, some apparel manufac-
turers are relocating production back to the United
States, aiming at shortening lead times and increas-
ing responsiveness (Sheng 2015). Every garment in
Zara will be on sale for a maximum of 5 weeks, after
which it is removed and sent to discount stores or
destroyed. Zara invests close to zero percent of its
sales in advertisement (5% of sales for Gap), relying
instead on keeping customers perpetually interested
in finding new surprises (Zara´s customers visit the
conveniently located stores an average 17 times a
year). While Gap brands, Zara intrigues.
Two distinct flows can be appreciated at Inditex.
One consists of long-term cycles, i.e., purchasing of
raw materials and the other a short-term cycle, i.e.,
design, fabrication and distribution. The long cycle
starts three to six months before each fashion sea-
son and consists in the acquisition of two thirds of
the raw materials required, mainly cloth (sourced
mainly from India, China, Morocco –a main sourcing
central is located in Tanger-, Mauricio, Korea, Italy,
Germany and Turkey), and about one half of all gar-
ments. These are those items that are thought to be
stable, i.e., basic products for which demand is fairly
predictable, or have a high labor component (e.g.,
embroidered garments). The rest of the garments
(those thought to have a higher risk) are produced
in-house in the short cycle described below.
The short cycle starts with design, an in-house affair
with over 200 designers. A key aspect of the process
is related to the area managers, who decide based on
local knowledge (e.g. the Caribbean or Eastern Eu-
rope) how much of a particular product they estimate
will be required for four to five weeks of demand in
their area of expertise. Patterns are scanned and
sent electronically to the manufacturing plants, all
located in the same area for in-house production (Ar-
teixo, in Northern Spain where headquarters are lo-
cated). Here capital-intensive activities such as dying
and cutting are performed, while sewing is manually
done mostly by outsourced local micro-companies.
Production is then pushed into the stores, where the
manager sends feedback in close to real time about
what moves and what doesn’t (colors, sizes, mod-
els), allowing for fast adjustments of the produc-
tion plan. Replenishment of stores is done twice or
three times a week, with a lead-time for existing (or
subject to slight design modifications) items of two
weeks, and of five weeks for new products. This ver-
tically integrated, centralized approach to fashion is
strikingly different than the more usual offshoring
used by Gap and others, and requires a higher level
of asset utilization. Nevertheless, it allows for a fast
response system that minimizes error in forecasting
and thus waste. In sectors like clothing, furniture
or household appliances, where product launches
are frequent, reducing the time gap between design,
production and distribution is critical. In such con-
text, keeping manufacturing close to customers and
suppliers is an effective strategy to assure control
over these stages in production and assure a highly
responsive system. Strong ties with local universi-
ties are also important to assure a constant inflow
of specialized workers and specific knowledge. For
example, the Inditex Chair of Corporate Social Re-
sponsibility at the University of Coruña.
Almussafes industrial park, Ford
Spain is the second largest producer of autos (and
first of industrial vehicles) in Europe, and the 12th
worldwide. Ninety percent of the production is ex-
ported to over 130 countries, generating the largest
contribution of all sectors to exports, over 17% of
total (ICEX, 2013). The activity of the automakers is
accompanied by an important auxiliary sector (6th
in the world), led by companies Gestamp and An-
tolín. The sector represents a contribution to Span-
ish Gross Domestic Product (GDP) and employment
as large as that of tourism (around 10% of total). In
spite of an important contraction in the European
auto market, the industry has experimented a nota-
ble comeback, with Ford Spain absorbing part of the
production of Belgium, PSA (Peugeot Citroën) Spain
part of the production of France, Renault absorbing
production from France and Turkey, and Nissan in-
vesting $170m.
Labor costs in the auto sector in Spain are around
25 Euros per hour, almost half of that in Germany,
but 5 times higher than Romania and almost 8
times higher than China (Expansión 2013). How

to explain then the success of the sector? One
explanation can be found in the case of the evo-
lution of the Almussafes industrial park of Ford,
in the proximity of Valencia. Over the years, the
plant has evolved into a large industrial park, with
over 90 suppliers connected to the assembly line
via conveyors allowing for just-in-sequence pro-
duction, an initiative that has been successfully
adopted in other factories of Ford (e.g. Saarlouis,
Germany and Genk, Belgium). Labor and Union
moderation and negotiation flexibility, know-
how, and the proximity to suppliers (due in part
to incentives from the local government) will soon
make Almussafes the largest factory of Ford in Eu-
rope, as it absorbs the production of other Europe-
an plants (Cinco Días, 2013). Other explanations
come from the heavy investments in Research &
Development (89 robots for each 10,000 workers).
The President of Ford has recently declared that
the company plans to make the Spanish plant a
“global innovation center” of the firm, focusing on
models of higher size and sophistication for the
export market (El País, 2015). Moreover, other
factors that explain this decision are a competi-
tive auto parts industry (which obtains 60% of its
revenue from exports), and the geographical and
cultural proximity to consumer markets (Spain is
a privileged export platform for European, North
Africa and Latin American markets).
In order to facilitate the cross-case analysis, we catego-
rize the main drivers for locating operations in Spain of
each case. The cases are analyzed according the eclectic
theory. A summary table can be seen in Table 3.
These cases are analyzed under the theoretical lenses
of the eclectic theory of international production
(Dunning, 1980, 1988, 1990). In this theory, three
determinants of international production are pro-
posed: ownership advantages, location advantages,
and internalization advantages. In this study, we are
particularly interested in the location advantages
suggested in the eclectic theory. Our aim is to use
this theoretical lens to analyze the location decisions
of the companies mentioned in the study.
DISCUSSION
Empirical evidence of the location of operations in
HLCC is scarce in the academic literature (Ellram et
al, 2013; Gray et al, 2013; Tate, 2014). While location
decisions are usually justified by labor costs (Baker
& Roberts, 2006; Martinez-Mora & Merino, 2014;
Tondolo et al, 2011), the results of the study sug-
gest that location decisions include a much broader
set of drivers than just cost. Furthermore, results of
this study are in line with previous studies concern-
ing the cross-sectorial nature of location decisions in
high-cost countries, i.e. the fact that it encompasses
multiple a diversified array of industrial and service
sectors (Gray et al, 2013).
While location in low-wage countries remains a nat-
ural option for specific types of industries (e.g., labor
intensive, or located in countries that offer impor-
tant tax advantages) or when it is important to guar-
antee trade compliance (e.g. some countries prevent
importing from certain others), business cases are
often oversimplified by considering only labor costs
or taxation considerations. Locating operations in
HLCC may offer many cost, risk and agility advan-
tages, plus a positive effect in job creation that could
produce a hedge against protectionism. In particu-
lar, although local operations risks are often lower
than offshoring since firms have more knowledge
and are closer to local markets, they tend to be more
concentrated (i.e. the array of potential location al-
ternatives in the case of problems is more limited.)
A key driver of the cases is the reduction of employee
turnover. This is in line with recent research: stabiliz-
ing the workforce has been detected as one of the
main motivations for bringing back production to
HLCC’s. Indeed, high worker turnover is a problem
Table 3. Drivers for HLCC location
Type of driver NGA CHEP Inditex Ford
Resource-seeking X X X
Market-seeking X X
Efficiency-seeking X X X
Strategic asset-seeking X X X X

on the shop floor because it injects variability and
unpredictability into production schedules (Shih,
2014). Another important driver detected in the
study is skill availability. Many authors are consider-
ing the scarcity of non-strategic resources in areas
with high economic growth, especially trained and
motivated workforce (Tate, 2014). In our study, the
broad availability of linguistic skills in Granada fa-
vors the location of operations in the city, in the case
of NGA. However, even more critical is the gap of
skills in the manufacturing sector. This is important
as the resources used by firms in their traditional
manufacturing operations (e.g. suppliers, workforce,
and even the company’s own internal product design
capabilities) can atrophy, creating a generational
skills deficiency in most developed countries. Ac-
cordingly, the position of Spain in the World Rank-
ing of Economic Complexity has been decreasing
steadily in the last decades (from the 18th position
in 1995 to the 27th position in 2013). The Economic
Complexity Index (ECI) is calculated yearly by the
Center of International Development of Harvard
University, and measures how diversified and com-
plex a country’s export basket is (for more informa-
tion, see http://atlas.cid.harvard.edu/rankings/).
In order to solve this problem, increasingly com-
mon in the developed world, many companies in the
United States are hiring more experienced manufac-
turing engineers or working with local community
colleges to incorporate industry credential systems
and/or training into the schools’ programs to attract
students (Shih, 2014).
An interesting result of this study is related to labor
intensity. While most studies assume that labor-
intensive activities are prone to production in low-
wage countries, our findings show that this may not
be true, since even highly labor-intensive (e.g. call
centers) activities can be moved to HLCC. Thus, an
implicit assumption that only automatized activities
should be kept in the developed world (because of
the high labor cost) is questioned.
Although much of previous research suggests that
cost-related factors play the most important role in
location decisions, our study suggests that other fac-
tors (e.g. employee turnover, links with supply base)
may be equally important. Actually, the risk of sup-
ply interruption, together with the movement of
manufacturing to various regions suggests that sup-
ply base is becoming an important location factor
(Ellram et al, 2013).
As the Inditex case shows, positioning manufactur-
ing close to the market minimizes the inventory of
goods in the pipeline and reduces delivery times.
More importantly, the closeness reduces the length
of ordering cycles, enabling companies to respond
more quickly to market changes (Shih, 2014).
With respect to the enablers, an analysis of the im-
pact on stakeholders provided interesting results.
The most relevant stakeholders in the analyzed
firms were the employees and local universities. On
the other hand, other stakeholder categories such as
consumers or media were not mentioned. A possible
explanation is that the main drivers of the firms in
the study were in Dunning’s resource-seeking cate-
gory thus stakeholders who could potentially provide
such resources would acquire greater importance.
The reasons for that should be further investigated.
Finally, an important gap in the literature refers to
the potential differences between services and goods
location decisions. Are there different drivers for ser-
vice and manufacturing firms? Our study does not in-
dicate a significant difference between the drivers of
service and manufacturing location decisions. How-
ever, it would be interesting to have more research
specifically designed to investigate this issue.
Social and political impact of location
decisions
The HLCC location enablers depend heavily on the so-
cial and political contexts. It can be argued that devel-
oped countries are suffering a structural destruction
of employment (Díaz 2012), resulting from system-
atic increases in productivity that have displaced labor
from the primary sector of the economy (agriculture,
mining) to the secondary sector (manufacturing), and
then again to the tertiary sector (services).
While the four cases discussed above show the po-
tential for job creation in Spain, much remains to be
done to achieve unemployment values closer to oth-
er countries in the OECD. Some enablers, induced
from the gathered evidence, are sketched below:
Rebuild companies’ supplier ecosystem and some ba-
sic core competencies (in line with Shih, 2014). For
instance the creation of local clusters, following the
examples of Ford Almussafes and of the technologi-
cal cluster of Granada, discussed above.
Incentivize technical education and stimulate young
talents in this area. In the same vein, reduce the mis-

match between the unemployed skills and what em-
ployers need, through educational reform: according
to the OECD, over 45% of all College graduates in
Spain are working at jobs of low skills requirements,
twice the OECD average (Economist 2010). In multi-
lingual Europe to speak at least a second language is
also critical. In a study of US-based firms who brought
back their operations to the country, few of the new
hires were prepared for the expectations placed on
them or the environment in which they would be
working (Shih, 2014). While Chinese firms have been
developing vast pool of technical resources in manu-
facturing, HLCC have lagged behind (Shih, 2014).
Reduce corporate taxes. Corporate taxes in Spain are
between 20 and 25% for small companies and 30%
for companies with more than 25 employees and
profits over 300,000 Euros. A flat rate, closer to 20%
will stimulate re-shoring, employment and state in-
come (as most tax revenue all over the world come
from personal taxation).
Simplify regulation. Spain occupies the position 74
in the Ease of Doing Business ranking of the World
Bank, and despite recent advances, but much re-
mains to be done to facilitate hiring and firing,
improve productivity, reduce public holidays and
assorted worker benefits, and simplify procedures
for the creation of companies. Related to this is im-
proved access to credit, especially for SME.
But eventually job creation and competitiveness
have to come from the Spanish workers themselves.
As one director of an automobile assembly plant told
one of the authors:
“We are aware that this factory was located
in Spain because of the advantages of a weak
currency and cheap labor. These advantages
are now lost, and we have to substitute for
productivity, efficiency and innovation to
keep our jobs”.
CONCLUSION
Free trade promotes innovation and competition,
grants access to much larger markets, and to the ex-
change of ideas. Tragically, faced with a combination
of global economic slowdown, increased unemploy-
ment/underemployment, and migration pressures
many countries are being tempted by populist and
protectionist short-term political solutions that could
result in the erection of barriers to global trade. This is
a complex issue and in this paper we focus at providing
more empirical evidence on the location of operations
in HLCC, grounded on previous literature and organi-
zational theories. This issue is increasingly relevant,
being object of intense discussion at practitioner, aca-
demic and policy levels. As a matter of fact, the location
of operations in HLCC’s does not only present relevant
repercussions at supply chain decisions, but it also is
characterized by important social implications. We be-
lieve that an integrated discussion of both dimensions,
usually neglected in the literature, can raise a more
fruitful debate of how such decisions affect stakeholder
management, and can lead to industrial policies that
counter populist and protectionist political behaviors,
assuring the sustainability of global supply chains.
Although this paper constitutes a contribution in
this direction, we acknowledge the limitations of
being based on a small sample of companies located
in Spain, and of the secondary nature of the data.
Obviously, firms don’t like to broadcast previous
bad decisions. Thus, collecting more quantitative
data on location decisions is recognized by academ-
ics as a complex task (Martinez-Mora & Merino,
2014). However, more cross-sector and geographi-
cally diversified studies on this area are important
to support more grounded conclusions. Moreover,
tt would be interesting to study the supplier loca-
tion decision as well. To what extent are the loca-
tion drivers for manufacturers the same as those
for their suppliers? Overall, a better understand-
ing of total factors involved in location decisions is
needed to support business and political decisions.
In particular, the application of different organi-
zational theories can provide some useful insights
about locating operations in high labor cost coun-
tries and policy implications. We hope to have con-
tributed on this direction as well.
ACKNOWLEDGMENT
We are deeply indebted to José Luis Díaz, Enrique
García and Aitor Vinos for their invaluable com-
ments and feedback in the analysis of the cases.
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SPECIAL ISSUE
Submitted 26.09.2016. Approved 07.03.2017.
Evaluated by double blind review process.
Scientific Editors: Ernesto Santibanez Gonzalez and Charbel Jabbour
COMPARING MADRID AND SALVADOR GHG
EMISSION INVENTORIES: IMPLICATIONS FOR
FUTURE RESEARCHES
ABSTRACT
This paper compares the Greenhouse Gas (GHG) emission inventories of Madrid and
Salvador and discusses some implications for future researches, focusing on city-
level carbon accounting (CLCA) of emissions from urban supply chains (USC) and
final consumers. To carry out this study, secondary data were collected from official
documents of municipal governments of these two cities. According to the results,
there are differences in stationary energy GHG emissions due to the big distinction
concerning electricity emission factors used by each city. Air transportation GHG
emissionsarealsoverydifferent.Thesetwocitiessharesomecommonfiguresregarding
road transportation and per capita waste sector GHG emissions. In the conclusion
section, we discuss opportunities for improvement of the cities’ GHG emission
inventories as well as some implications for policy-making and future researches on
carbon accounting, with focus on an integrated production-consumption system.
KEYWORDS | Greenhouse Gas emissions, urban supply-chain, city-level carbon
accounting, Salvador, Madrid.
José Celio Silveira Andrade
jcelio.andrade@gmail.com
Professor at Universidade Federal da Bahia, Escola de Administração – Salvador – BA, Brazil
Andrea Dameno
andreadamenonielsen@gmail.com
Researcher at Universidad Politécnica de Madrid – Madrid, Spain
Javier Pérez
javier.perez@etsii.upm.es
Lecturer at Universidad Politécnica de Madrid – Madrid, Spain
Juan Manuel de Andrés
jdeandres@etsii.upm.es
Lecturer at Universidad Politécnica de Madrid – Madrid, Spain
Julio Lumbreras
julio.lumbreras@upm.es
Professor at Universidad Politécnica de Madrid – Madrid, Spain
ISSN: 1984-3046© joscm | São Paulo | V. 10 | n. 1 | Jan-June 2017 |17-32

18 AUTHORS | José Celio Silveira Andrade | Andrea Dameno | Javier Pérez | Juan Manuel de Andrés | Julio Lumbreras
INTRODUCTION
Estimates show that the Greenhouse Gas (GHG)
emissions caused by three European consumption
areas (food, mobility and housing) showed no signifi-
cant reductions between 2000 and 2007. However,
when looking from a production perspective, in many
economic sectors, there has been reduction in GHG
emissions, or a decoupling between growth and emis-
sions. The GHG emissions of goods consumption in
the European Union (EU) are higher than the pro-
duction emissions of the goods produced there, with
the largest difference occurring in 2008 when con-
sumption emissions were about a third higher than
production emissions. Between 1995–2010, the EU
production emissions decreased, whereas consump-
tion emissions were slightly higher in 2010 than in
1995 (Gandy, Wiebe, Warmington, & Watson, 2014).
In 2009, the GHG emissions associated with EU con-
sumption equaled 4,407 million tonnes, which was
2% higher than in 1995. In comparison, the United
Nations Framework Convention on Climate Change
(UNFCCC) production-based (PB) estimate of 4,139
million tonnes in 2009 was 9% lower than in 1995.
These data indicate that, in order to meet its 2050 ob-
jectives and contribute fully to meeting the global 2°C
target, the EU will need to accelerate its implementa-
tion of new policies, while restructuring the ways that
Europe meets its demand for energy, food, transport
and housing (EEA, 2015).
Thus, making cities more sustainable is one of the
most vital challenges of the 21st century, especially
because cities exert a significant impact on the envi-
ronmental status quo. When it comes to tackling cli-
mate change cities play a key role. The ability of city
policy-makers and other stakeholders to take effec-
tive action depends on access to good quality data on
GHG emissions. Therefore, a greater emphasis placed
on the measurement of emissions and transparent
data on GHG emissions is crucial. City-level carbon
accounting (CLCA) standards are fundamental to en-
able city decision-makers to identify emission sources
and their drivers, to reduce the carbon dependence
of their economy and to stimulate opportunities for
more efficient urban supply chains (USC).
Cities need to establish mitigation objectives and de-
velop environmental policies in order to hold back the
consequences of climate change. The most frequently
used analytic tool is the GHG emission inventory,
which estimates the emissions associated with the
activities of the city or country studied. The devel-
opment of these inventories is the first step towards
achieving the different goals set up by the regulatory
organism and they are particularly helpful in tracking
the progress over time.
In order to compare inventories and facilitate the in-
tegration of inventories from different cities, stan-
dardised methodologies for developing and reporting
GHG emissions have been developed. Considering
this, the Compact of Mayors, supported by 457 cities,
published the Global Protocol for Community-Scale
GHG Emission Inventories (GPC) in 2014. This inter-
nationally accepted methodology helps cities develop
their GHG inventories in a consistent and widely rec-
ognised way.
Therefore, most of the city-level GHG inventories us-
ing the GPC methodology are carried out focusing on
a production approach and they do not account for all
the emissions embedded in products and services con-
sumed in a city. The large and increasing share of GHG
emissions ‘hidden’ in imported goods underlines the
importance of calculating the carbon emissions and
impacts of USC and final consumers (Schaltegger &
Csutora, 2012).
This paper comparesthe GHG emission inventories of
Madrid and Salvador, which reported in 2015 their
2013 emissions to GPC, and it discusses some im-
plications for future researches focusing on CLCA of
GHG emissions from USC and final consumers.
These two cities were chosen for some reasons. Firstly,
Madrid has a long trajectory in doing the integration
of the air pollutant and the GHG emission invento-
ries. In fact, since 1999, the city has been producing
its two inventories following the Core Inventory of
Air Emissions (CORINAIR) methodology, which is
coordinated by the European Environment Agency
(EEA), and meets the requirements established by the
Intergovernmental Panel on Climate Change (IPCC)
and the Task Force on Emission Inventories and Pro-
jections of the United Nations Economic Commission
for Europe (TFEIP - UNECE).
Although Madrid has been producing GHG emission
inventories for more than 10 years, only in 2015 the
GPC methodology was implemented in order to re-
port the 2013 Madrid’s GHG emission inventories
(Madrid, 2015a). Even if Madrid’s experience regard-
ing the use of the GPC standards is not very long, it
does have a long experience in gathering data and
calculating emissions using international principles.
Therefore, the recent adoption of the GPC methodol-

19ARTICLES |Comparing Madrid and Salvador Ghg Emission Inventories: Implications for Future Researches
ogy has not implied a significant change for the city’s
usual inventory development. In fact, the distinction
mainly resides in a different activity classification,
which led to a reorganization of the results and the
calculation of some indirect emissions that were not
considered before.
On the other hand, Salvador’s first attempt to develop
a GHG emission inventory was in 2015, with 2013
emission data. This has been the only inventory pro-
duced so far by this Brazilian city and it was developed
using the GPC methodology. Then, Salvador is at an
initial stage of the development of GHG emission in-
ventories under the GPC framework. Thus, this com-
parison between GHG emission inventories from two
cities with different trajectories regarding their expe-
riences in producing air pollutant emission invento-
ries could provide useful contributions toscholars and
practitioners improving the quality of CLCA methods.
Secondly, this comparison acts as an evaluation meth-
od for the GHG emission inventories of Salvador and
Madrid. Comparing results from Madrid, to the first-
stage results from Salvador could contribute to these
Brazilian city decision-makers improving the quality
of the future inventories.
Additionally, the availability of the GHG emission in-
ventory data for these two cities and the existence of
an academic research collaboration between the Tech-
nical University of Madrid in Spain and Federal Uni-
versity of Bahia in Brazil about urban carbon account-
ing methods. It is important to point out that most of
GHG emission inventories of cities around the world
are not of open public access to academic researchers.
Finally, large cities like Madrid and Salvador are con-
sidered more consumers of goods and services than
producers. Then, this paper contributes to put into
discussion some challenges regarding the necessity of
a future urban carbon accounting academic research
agenda to switch the focus from current GHG inven-
tories to an integrated production-consumption car-
bon accounting system.
LITERATURE REVIEW
A number of international initiatives have been devel-
oped over the past decade to standardize the method-
ology for conducting a city GHG inventory. The most
widely referenced programs include: the International
Local Government GHG Emissions Analysis Protocol
(IEAP), developed by the Local Governments for Sus-
tainability(ICLEI)in2009;theInternationalStandard
for Determining GHG Emissions for Cities (ISDGC),
jointly developed by the World Bank, the United Na-
tions Environmental Programme (UNEP) and the
United Nations Human Settlements Programme (UN-
HABITAT) in 2010; the Baseline Emission Inventory/
Monitoring Emission Inventory Methodology (BEI/
MEI), developed by the Covenant of Mayors Initiative
in 2010; the U.S. Community Protocol for Accounting
and Reporting of GHG Emissions, developed by the
ICLEI USA in 2012; the Publicly Available Specifica-
tion (PAS) 2070:2014 for measurement of GHG emis-
sions of a city, developed by the British Standards In-
stitution (BSI) in 2013; and, finally, the GPC, jointly
developed by the World Resources Institute (WRI),
ICLEI and the Cities Climate Leadership Group (C40)
in 2014. These methodologies present differences
that range from the use of different emissions catego-
ries to the consideration of different GHG emission
boundaries (WRI, 2014).
Normally, the existing methodologies have two dis-
tinct focuses: PB inventories and consumption-based
(CB) inventories. Conceptually, CB inventories can
be thought of as: consumption equals PB emissions
minus the emissions from the production of exports
plus the emissions from the production of imports.
While PB inventories allocate GHG emissions to the
producer, CB inventories allocate emissions to the fi-
nal consumer.
CB methodologies typically account for a larger num-
ber of emissions as most goods and services con-
sumed in cities are not usually produced locally. Cities
import most of their goods and services from other
regions. The methods used following the principles of
consumption are very different from the ones used in
the more traditional approach of PB inventories. The
idea of allocating emissions to the final consumer is
not recent, but, given its complexity, there has not
been a global consensus on what type of methodology
to apply yet: Life-Cycle-Analysis (LCA) inventories,
Environmentally-Extended-Input-Output (EEIO)
matrixes, Compound Method based on Financial
Accounts (MC3) etc. (Peters, 2008; Cagiao, Gomez,
Domenech, Mainar, & Lanza, 2011; Larsen, Petters-
en, Solli, & Hertwich, 2013).
Some of the CLCA standard that adopted the CB
methodologies, like the PAS 2070 standard, recognize
cities as both consumers and producers of goods and
services. The PAS 2070 sets out requirements for the
assessment of GHG emissions of a city or urban area
by using two methodologies: Direct plus Supply Chain

(DPSC) and CB.
The DPSC methodology captures territorial GHG
emissions and those associated with the largest sup-
ply chain serving cities. It is consistent with the GPC.
Thus, the DPSC accounts for GHG emissions from
six source categories: stationary energy sources (en-
ergy use in residential buildings and commercial, in-
dustrial and government buildings and facilities), in
boundary and transboundary transportation, Indus-
trial Processes and Product Use (IPPU), Agriculture,
Forestry, Other Land Use (AFOLU), waste and waste-
water treatment and some goods and services (water
provision, food and drink and construction materi-
als). The CB methodology uses input-output modeling
to estimate direct and life cycle GHG emissions for all
goods and services consumed by residents of a city.
So, the PAS 2070 captures both direct GHG emissions
(from sources with the city boundary) as well as indi-
rect GHG emissions (from goods and services that are
produced outside the city boundary for consumption
and/or use within the city boundary).
Used to assess 2010 GHG emissions of London, the
PAS 2070 has estimated the total GHG emissions
using the DPSC and CB methodologies and has com-
pared them to previous results calculated using the
London Energy and Greenhouse Gas Inventory (LEG-
GI). The LEGGI covered GHG emissions only from the
combustion of energy used within the city boundary
(for transport and to power and heat homes/work-
places). According to the assessment results, the total
2010 GHG emissions of London calculated using the
CB methodology are 40% higher than those calculated
using the DPSC methodology and 156% higher than
those calculated using the LEGGI methodology (Minx
et al., 2013; BSI, 2014).
The London case study shows the difference between
PB and CB methodologies. Cities like London – and
any other large cities, which are considered more
“consumers of goods and services” than “producers”
– inevitably give rise to the production of GHG emis-
sions beyond their boundaries and highlight the need
to include a wider range of emission sources in their
GHG inventory.
In some countries like China, cities have higher per
capita GHG emissions than the national average be-
cause they concentrate industrial activities. Weber,
Peters, Guan, and Hubacek (2008) documented that,
in 2005, approximately 30% of Chinese emissions
were related to the production of exports and that
this share increased rapidly in the early 2000’s. On
the other hand, most Organisation for Economic Co-
operation and Development (OECD) countries show
the opposite trend (Hoornweg, Sugar, & Gomez,
2011) because the influence of the consumption of
imported goods and service on the cities’ GHG inven-
tories is higher than the national-scale ones. Weber
and Matthews (2007) created a multi-country input-
output model to estimate embodied carbon emissions
and forecasted that, if this trend continues, emissions
embodied in United States (US) imports will exceed
emissions of domestic production within 20 years.
Thus, a large and increasing share of European and US
GHG emissions are embedded in imported goods as a
‘carbon rucksack’ (Schaltegger & Csutora, 2012).
Such divergence between production and consump-
tion perspective trends is common (Hoff, Nykvist &
Carson, 2014; Tukker et al., 2014). However, it should
be borne in mind that CB methodologies are subject
to greater data uncertainty and shorter time series,
as well as difficulties in defining system boundaries.
EEIO matrixes are still barely developed at city scale
and growing complexity of city’s supply chains poses
substantial challenges to this kind of carbon account-
ing and makes it more difficult to use CB methodolo-
gies in policy-making (Wiedmann et al., 2013).
Therefore, hybrid carbon accounting, which combines
economic approaches of input-output analysis with
physical approaches, should be used as an approach
for urban supply chain and final consumers account-
ing when physical material flows cannot be measured
or only at exorbitantly high costs (Settanni, Tassielli,
& Notarnicola, 2011). Physical material flows are ap-
proximated based on financial information and are as-
sumed proportional to monetary flows. Such applica-
tions, however, should be treated with caution, as the
accuracy of hybrid accounting information is far lower
than when using physical primary data. The applica-
tion of hybrid carbon accounting may be justified by
high data collection costs or unavailability of data due
to confidentiality problems, but this should not be an
excuse when primary physical carbon data can be col-
lected with reasonable effort (Schaltegger & Csutora,
2012). Tsai et al. (2012) provided a practical example
on how input-output analysis can be combined with
activity-based costing to more effectively link physical
material flows and economic flows of costs.
Thus, PB methodologies have been further developed
and they have a more solid background as compared
to CB and hybrid methods. The methodologies used
for GHG emission calculation are more standardized

and they allow easier comparison among cities. It is
inside this framework that the GPC methodology is
presented.
GPC is built upon the worldwide used IPPC Guide-
lines, which provide detailed guidance on data col-
lection and calculation of GHG emissions. The GPC
methodology provides a robust framework for gen-
erating GHG emission inventories, divides emission
sources into sectors that have been globally adopted,
and proposes two different approaches for reporting
the results: scope and city-induced frameworks.
It has been adopted by more programs and initiatives
including the Compact of Mayors, the Carbon Disclo-
sure Project (CDP) reporting platform, the PAS2070
and International Organization for Standardization
(ISO) 37120:2014 (Sustainable Development of Com-
munities). Up to date, more than 100 cities have used
GPC to measure GHG emissions (WRI, 2014).
Scope framework
This approach adds up emissions by scope. GHG emis-
sions can occur inside and outside the city bound-
ary. Three scopes are objectively defined in order to
cover all relevant GHG emissions and avoiding double
counting. This is shown in Figure 1:
Figure 1. GPC Scope Framework: sources and bound-
aries of city GHG emissions
Source: WRI (2014)
Scope 1 accounts the GHG emissions from stationary energy, transportation, waste, IPPU and AFOLU sources

located physically within the city boundary. This scope
(called territorial emissions) allows for the separate
accounting of all GHG emissions produced within
the geographic boundary of the city, consistent with
national-level GHG reporting.
The scope 2 considers the GHG emissions that occur
due to the consumption of grid-supplied electricity,
heat, steam and/or cooling within the city boundary.
GHG emissions associated with electricity are one of
the biggest areas of variability among cities and can
be essential in order to mitigate emissions.
Finally, the scope 3 accounts the GHG emissions that
occur outside the city boundary because of activities
that take place within the city boundary. The GPC
includes scope 3 accounting for a limited number of
emission sources, including transmission and distri-
bution losses associated with grid-supplied energy,
andwastegeneratedinthecitybutdisposedortreated
outside the city boundary and out-of-boundary trans-
portation. Cities may optionally report other Scope
3 sources associated with activity in a city—such as
GHG emissions embodied in fuels, water, food&drink
and construction materials.
CB methodologies are an alternative to the sector-
based approach to measure city emissions adopted by
the GPC. It focuses on the consumption of all goods
and services by residents of a city, and GHG emissions
are reported by consumption category rather than the
emission source categories set out in the GPC. The CB
methodologies allocate GHG emissions to the final
consumers of goods and services rather than to the
original producers of those GHG emissions. As such,
GHG emissions from visitors’ activities and the pro-
duction of goods and services within the city bound-
ary that are exported for consumption outside the
city boundary are excluded.
CB inventories typically use an input-output model,
which links household consumption patterns and
trade flows to energy use and GHG emissions, and
their categories cut across those set out in the GPC.
So, CB approach is complementary to the GPC and it
provides a different insight into a city’s GHG emission
profile.
For example, King County in the U.S. state of Wash-
ington carried out a study published in 2010 using
2008 data to estimate the emissions associated with
all goods and services consumed by the region’s two
million residents, regardless of where the emissions
were produced. Total emissions were estimated at 55
million MtCO2e, of which over a quarter was released
outside the US. Overall, emissions associated with lo-
cal consumption by residents, governments and busi-
nesses, including the production of goods, food and
services from outside the County, were more than
twice as high as emissions that occurred inside the
County’s borders. King County’s “geographic-plus”
based inventory separately estimated regional emis-
sions at 23 million MtCO2e, using a methodology
similar to the GPC. The difference in emissions re-
flects the different sources covered by the two meth-
odologies. Some sources are included in both inven-
tories and, therefore, the results should not be added
together in order to evict double-accounting (WRI,
2014).
City-induced framework
This approach gives cities the option of selecting be-
tween two reporting levels: BASIC or BASIC+. These
levels cover specific scopes in different categories of
activities, being the BASIC+ level the one that pro-
vides further analysis. The BASIC+ reporting level
includes the three BASIC categories (stationary en-
ergy, transportation and waste) and aggregates IPPU,
AFOLU and any other emissions occurring outside
the geographic boundary due to city activities (WRI,
2014).
Stationary energy, the first BASIC reporting level cat-
egory, includes scope 1 and 2 GHG emissions. A major
part of the emissions associated with stationary en-
ergy is produced due to residential, commercial and
institutional buildings and facilities heating systems;
energy industries; and manufacturing industries and
construction. Looking at these emissions, the types of
fuels employed to produce energy, the levels of energy
efficiency of constructions and the climate are the
main determinant for stationary energy GHG emis-
sions. Therefore, cities with a higher heating or cool-
ing need and a higher level of fossil fuel energy con-
sumption will normally have higher GHG emission
rates related to stationary energy. So, the thermal and
electrical energies play an important role in this GHG
emission category, and it presents a strict relationship
between the level of economic welfare and the quanti-
ties of energy consumed (Croci, Melandri, & Molteni,
2011).
The second one, the transportation category, also cov-
ers the scopes 1 and 2 GHG emissions. In scope 1 it
covers the fugitive emissions from transportation of
primary fossil fuels and in scope 2 it covers all jour-

neys by road, rail, water and air, including inter-city
and international travel. GHG emissions are produced
directly by the combustion of fuel orindirectly by the
use of grid-supplied electricity. Empirical relation-
ships have been established between transportation
energy use and population density, with an inverse in-
teraction (Kennedy et al., 2009). Cities that are spread
out result in heavy reliance on fossil fuel-powered au-
tomobiles and, therefore, account for higher trans-
portation-related GHG emissions. On the other hand,
cities with higher population density and with an ex-
tensive public transportation network that enables
them to satisfy a bigger quota of passengers, normally
present significantly lower emissions associated with
transportation (Sugar, 2010). The form of a city, the
features of the vehicle stock, the type and the prices
of fuels utilized are determinants of GHG transporta-
tion emissions (Croci et al, 2011).
Finally, the third onecovers the GHG emissions as-
sociated with waste category and it includes scopes
1, 2 and 3. The GHG emissions computed within this
category are produced due to the inside and outside
of city boundary waste and wastewater generation,
treatment and disposal.
Management of urban solid waste systems has been
implemented in most developed countries, not only
with the purpose of optimization of resources, but
also with the purpose of reducing GHG emissions. Ur-
ban solid waste volume increases with economic and
demographic growth and some studies indicate that
treatment and disposal of it is third one of the ma-
jor contributors to GHG emissions after residential,
commercial and institutional buildings and facilities;
and transportation (Lu, Sun, Ren, & He, 2015). Thus,
the per capita GHG emissions and urban solid waste
generation are closely correlated to city wealth (Hoo-
rnweg et al., 2011). It is a fact that the cities in the
world’s poorest regions with lowest per capita GHG
emissions have lower waste generation rates.
Waste treatment strategies are especially important
in order to tackle GHG emissions, as cities grow and
consume more resources, there is a clear relationship
between emissions and waste. Chinese cities and oth-
er cities in developing countries that experiment an
incredibly rapid pace of growth have correctly iden-
tified this relationship and several thorough stud-
ies have been carried out in order to apply the best
policies concerning solid waste treatment (Yang et
al., 2011; Lin & Huang, 2009; Guerrero, Mass, & Ho-
gland, 2013).
METHODOLOGY
As previously explained, the GPC standards have been
chosen in order to compare the GHG emissions from
Madrid to Salvador. In order to carry out this study,
no primary data were collected and only public sec-
ondary data sources were used. For Madrid as well
as for Salvador, public secondary data were collected
from official and institutional documents of munici-
pal and national governments (GPC reports, energy
balance, urban waste management reports, airport
traffic reports etc.).
Table 1 provides Madrid and Salvador’s information.
They were used as references to estimate the GHG
emission inventory boundariesin GPC reports of
these cities.
Table 1. Madrid and Salvador’s information from GPC
reports
City Madrid Salvador
Year 2013 2013
Description
Capital of Spain; the third largest city in
the EU
Capital of the state of Bahia; the third
largest city in Brazil
Area (km2) 606 693
Average temperature (ºC) 15 25.3
Population (million) 3.2 2.9
Density (inhab./km2) 5,292 4,190
GDP (million US$) 103,261 18,521
Source: Madrid (2015a, 2015b, 2014a) and Salvador (2015)
Tables 2 and 3 present the data about the GHG emissions of Madrid and Salvador from GPC reports:

Table 2. GHG emissions of Madrid in 2013 from GPC report
Madrid
GHG Emissions Source (By Sector) Total GHGs (tonnes CO2e)
Scope 1 Scope 2 Scope 3 BASIC BASIC+
Stationary energy
Energy use 2,860 2,985 374.042 5,845 6,219
Energy generation sup-
plied to the grid
190.900 - - - -
Transportation All emissions 2,660 265.751 33.300 2,926 2,959
Waste
Waste generated in the city 431.481 - - 431.481 431.481
Waste generated outside
city
5.776 - - - -
IPPU All emissions 679.742 - - - 679.742
AFOLU All emissions -32.432 - - - -32.432
Other scope 3 All emissions - - - - -
Total 6,796 3,251 407.342 9,202 10,257
Source: Madrid (2015a, 2015b)
Table 3. GHG emissions of Salvador in 2013 from GPC report
Salvador
GHG Emissions Source (By Sector) Total GHGs (tonnes CO2e)
Scope 1 Scope 2 Scope 3 BASIC
Stationary energy
Energy use 303.734 366.395 - 670.129
Energy generation supplied to the grid - - - -
Transportation All emissions 2,151 - - 2,151
Waste
Waste generated in the city 205.218 - 90.402 295.621
Waste generated outside city 3.515 - - -
IPPU All emissions - - - -
AFOLU All emissions - - - -
Other scope 3 All emissions - - - -
Total 2,663 366.395 90.402 3,117
Source: Salvador (2015)
In 2015 Madrid decided to adopt the GPC methodology to report its 2013 GHG emissions at BASIC and BA-
SIC+ levels (see Table 2). On the other hand, Salvador only covers the BASIC reporting level of the GPC (see
Table 3) as this wasthe first attempt to develop a GHG emission inventory. Therefore, it is only possible to com-
pare Salvador and Madrid at a BASIC reporting level.
So, in order to compare and discuss the results of Ma-
drid and Salvador, the following GHG emission indi-
cators and relations were used:
• Per capita urban and national emissions;
• Per capita emission by scope and sector;
• Per capita emissions associated with transportation;
• Relation between the per capita scope 2 emissions
and per capita electricity consumption from sta-
tionary sources;
• Relation between population density and per capita
emissions from road transportation;
• Relation between waste generation rate, per capita
total emissions and GPD;
RESULTS AND DISCUSSIONS
Figure 2 shows the differences between per capita ur-
ban and national GHG emissions from Salvador ver-
sus Brazil, and from Madrid versus Spain.
Figure 2. Percapita urban and national GHG emissions
from Salvador/Brazil and Madrid/Spain

JOSCM - Journal of Operations and Supply Chain Management – Vol. 10, n. 1 - Jan/Jun 2017

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JOSCM - Journal of Operations and Supply Chain Management – Vol. 10, n. 1 - Jan/Jun 2017