CHAPTER
29
FINANCIAL AUTOMATION, PAST, PRESENT, AND FUTURE
JUAN
PABLO PARDO-GUERRA
Surely, nothing can be more plain or even
more trite common sense than the proposition that innovation . . . is at the
center of practically all the phenomena, difficulties, and problems of economic
life in capitalist society.
Joseph Schumpeter in Business Cycles
Economic theory asserts that
technological developments enhance the quality of markets. Financial markets
are no exception. Devices of different sorts are widely seen as factors that
have allowed for the consolidation of capital markets throughout the world.
Indeed, for economists such
as Robert Merton, the benefits of technology overflow the financial system,
contributing to the general performance of the economy. “Innovations in
telecommunications, information technology, and financial engineering,” argues
Merton (with Bodie 2005, “offer the practical prospect for multiple channels
for the |AQ: 1 financing of economic growth” Merton’s claims are
reflections of a larger body of work dealing with the historical development of
finance. The economic literature is rife with demonstrations of how the
adoption of specific technologies positively affected market quality—from
execution costs and bid-ask spreads to liquidity and systemic risk. Propelled
by fierce competition, technology is thus presented as the undisputed handmaiden
of finance.
The standard economic
approach to technology in financial markets, however, tends to reproduce a
well-known model of innovation: technological change is rendered as a shift in
the underlying production functions of the financial system; given a set of
inputs, technology may well alter the way in which the different factors of
production relate but is not deemed a transformative element of the fundamental
mechanisms of exchange.
Markets boil down to
exchange, and while technology may make exchange cheaper and more efficient, it
does not alter its basic economic nature; calculation remains embodied in the
economic agent, not her technological appendices. Technology is thereby cast as
neutral and unproblematic.
Such understanding of
technology is incomplete, though. The artifacts populating finance are not
merely instruments used to optimize the utility of rational agents. Rather,
technologies crystallize rules of exchange, formatting the possibilities of
action of market participants; as means of visualization and interaction, they
present and scope what is increasingly a disembodied and dislocated—though
highly material—marketplace; technologies also constitute part of the
distributed agencies of reflexion and calculation that keep markets moving; and
as innovations, market technologies are objects of political, contested
intervention. Technologies constitute an important part of the microstructure
of finance.
This chapter follows from
Bruce Carruthers’ observation on the relative marginalization of finance in
sociological thought. As Carruthers shows, while finance has not been
completely ignored within the literature, analyses of this sphere of human
activity are relatively dispersed and occur on the margins of core sociological
con- |AQ: 2 cerns. Typically, finance is relevant only insofar as
it alludes to other themes, be they capitalism (Arrighi 1994; Strange 1986),
firms and corporations (Fligstein 2001), disasters (Perrow 2010), or
globalization (Castells 2000). Recent contributions seem to challenge this
omission, dealing with finance as a valuable topic in itself rather than an
illustration of some broader social process (Knorr Cetina and Bruegger 2002;
MacKenzie 2003; Muniesa 2003; Preda 2009. Tellingly, much of this literature
consists of explorations of the role of market technologies. This is rightly
so. The day-to- day operation of the market rests an intricate mesh of
technological systems that define the spaces of possibilities of financial
action and, as such, have concrete and enduring effects on the dynamics of the
market. While rules of exchange (Fligstein
2000) may inform macro-action,
market microstructures are concretely manifested in technology.
This chapter deals with this
sociotechnical character of finance. Much of the historical development of
financial markets was framed by a type of technological change captured under
the rubric of automation. Accordingly, this chapter provides a historical-
sociological sketch of the drivers, manifestations, and possible consequences
of automation in financial markets. In providing what is an admittedly partial
sketch, it captures recent insights of the sociological literature on the place
of technology in finance, arguing that financial markets are intelligible only
if both their micro- and macrostructures are framed in the language of
sociotechnical dynamics.
The structure of this
chapter is as follows. The next section briefly reviews the concepts of
technology and automation in finance, and concludes by highlighting the different
drivers and spheres in which automation occurs. This is followed by a
description of how automation occurred in the different spheres of financial
practice, from settlement and clearing to trade execution. Finally, the chapter
offers thoughts on the scope of financial automation in the future.
Financial markets
intermediate the movement of capital between notionally “unproductive” savings
and “productive” investments. As such, they have played a key role in
technological innovation. By pooling and funneling idle money into novel
ventures and established institutions, these markets typically allowed states
and entrepreneurs to spread investment risks and pursue costly projects—from
the transcontinental railway systems of the nineteenth century to the
developments in pharmaceutics and biotechnology of recent decades.
Financial markets, however,
were traditionally spaces populated by relatively mundane technologies. For
most of their history, the bricks and mortar of finance were literally that:
bricks and mortar, framing the creation of contractual agreements of different
sorts. Indeed, even as late as the nineteenth century, the material cultures of
stock markets were formed by little more than chalk, ink, paper, marble, and
wood, fueled by the authority of interpersonal trust and the courts, and the
manual labor of armies of clerks.
The economic expansion of
the nineteenth century generally and the growth of markets in sovereign debt
and joint stock shares particularly posed novel possibilities for
entrepreneurs. As economic networks coalesced and financial institutions
stabilized, it became increasingly possible to, for instance, buy and sell
British sovereign debt in the exchanges of such cities as Paris and Amsterdam.
This form of geographic fragmentation of markets (that is, the fact that the
market for a specific contract existed in multiple sites rather than in a single
locale) entailed exploiting price differentials across exchanges—the price of a
contract in London need not have been the same as in Paris or Amsterdam owing
to the speed at which relevant information arrived at each city. Thus,
sophisticated entrepreneurs enabled with access and efficient communications
could make a profit through arbitrage: buying in the cheaper to sell in the
dearer marketplace. The adoption of telegraphs among financial institutions
largely responded to such profit opportunities.
How should we conceptualize
these innovations and, accordingly, the sociology of financial automation? The
adoption of telegraphs would seem to suggest that the canonical economic
representation is correct: technology improves efficiency but does little else
to the dynamics of the market. While Paris, London, and Amsterdam may have been
better interconnected, their local practices were largely unchanged. Here,
however, we can refer to three critical sociological perspectives in order to
better understand the imbrications of technologies and finance. At one level,
the now classical discussions in the sociology of technology of the 1980s shed
light on the dynamics of technological change. Following a different tradition,
debates on the role of technology within organizations allow us to gauge the
manner in which specific systems structured practice in the financial sphere.
Lastly, recent insights on the place of technology in distributed forms of
economic action highlight the diversity of technology in the marketplace and
thereby the different forms and logics of automation deployed by actors across
finance.
The early literature in
science and technology studies presents technological change as a contingent
process requiring the alignment of, and successful negotiations between,
different interested actors (Bijker et al. 1987; Bijker and Law 1992; MacKenzie
and Wajcman 1999). Costs, efficiencies, and other seemingly objective measures
of performance alone do not determine the success of technologies; the meanings
and contexts of practice associated to novel artifacts and systems have to be
settled among all the relevant stakeholders before they become established
facts. Further, the articulation of such meaning is often riddled with struggle
and resistance—innovation is political—for technology is not about
materialities but about the social relationships they entail. Paraphrasing
Bijker and Law (1992), markets are built along with their objects and
artifacts.
The construction of market
institutions is not subordinate to innovation, though. Social and technological
change are better visualized as intertwined, codependent, mutually constructed
trajectories. This intricate relationship is particularly clear in the way in
which organizations adapt to innovations. As Wanda Orlikowski (1992) argued,
within organizations technology both structures action and serves as a
mechanism for the emergence of agency: artifacts may constrain human agency (a
standard keyboard, for instance, is ill-suited for designing a book cover), but
they also facilitate certain forms of action (the same keyboard allows
interacting with a specific software in order to write a book chapter).
Technology neither determines human action nor is it itself determined by
intentional design. The specific dynamics of technology are influenced by
prevailing institutional conditions which may well include normativities of
proper action as well as attitudes toward technology and the organization of
work itself. A change in such social conventions can become as radical in
transforming sociotechnical trajectories as a “radical” technical innovation.
Artifacts also congeal
agency, serving as coordinating elements in networks of human and nonhuman
actors. Pocket calculators shared by traders and programmed with specific
valuation formulas, as well as distributed software systems that present
similar views of the world to agents in distant places, allow for specific
forms of action coordination to emerge in the marketplace: in the first,
formulas may be performed into being (MacKenzie and Millo 2003) while in the
second sophisticated forms of valuation are achieved despite the absence of
copresence (Knorr Cetina and Bruegger 2002). Even something as seemingly
innocent as the telegraph—a cable connecting two distant financial centers
through information distributed piecemeal—can have profound repercussions in
the way in which market participants act and conceptualize their worlds. In his
meticulous account, Alex Preda (2009) showed how the adoption of the telegraph
changed the understanding of finance in the late nineteenth and early twentieth
centuries, leading to new forms of interaction between brokers, investors, and
the market.
To these three perspectives
we may add a fourth, comprised by a more general sociological understanding of
automation. Given its connections to capital, labor, and workplace processes,
automation is a recurrent theme within several traditions of sociological
thought. In the early years of mechanization, machines were rendered
revolutionary catalysts of change, be they virtuous substitutes for “the lowest
operations of the human
intellect” (Babbage, quoted
in Daston and Galison 2007), or perilous examples of “machinery dispensing]
with muscular power” (Marx, quoted in MacKenzie 1984).
Later authors saw the
spectre of automation as a corrosive force within the system of relations of
production, one that subjugated workers under the gears of the machine. In his
now classical analysis, for instance, Harry Braverman (1974) warned of the perils
posed by automation to the skilled worker: with its increased technical
sophistication, management could now do by mechanical means “that which it had
previously attempted to do by organizational and disciplinary means” (Braverman
1999). De-skilling was thus an unavoidable consequence of the displacement of
workers by machines, an example of the relentless technological logic of
capitalist production.
For other authors, however,
automation was less direct, possibly less nefarious. David Noble, for example,
insisted on a more nuanced approach to the effects of automation. For him as
for others (see Attewell 1987; Noble 1978), the dreams of management were tamed
by the realities of the shop floor: de-skilling was less frequent and intense
than Braverman anticipated; the embodied and often tacit skill sets of workers
proved difficult to replicate and substitute; and the new machineries of
industry perennially required—at one level or another—some degree of manual
intervention.
The trading floors of
finance are not the shop floors of heavy industry, though, calling for a
context-specific definition of automation. Although skilled shop-floor workers
and some of the relatively wealthy financial intermediaries faced similar
challenges and responded in similar ways to the rise of one form or another of
automation, their logics and possibilities of action were quite different.
Automation, in a sense, came to signify a specific form of finance and,
consequently, was embraced or challenged in a distinct manner by financial
practitioners. The relevant question is thus: How should we define financial
automation?
Financial automation is a
historically located process initiated in the mid- to late 1950s at the
confluence of several independent trajectories. At one level, automation
derived from the reorganization of the securities industry that resulted from a
rise and reconfiguration of financial activity during the immediate postwar
period, particularly in the United States (Friedman 1980). New traded
instruments, a newfound affluence, and finance-friendly policies in America led
the market capitalization of the companies forming the Dow Jones Industrial
Average to grow from around $216 billion in 1949 to more than $13.5 trillion
today (for a thoughtful account of financialization, see Krippner 2010). Onto
this tremendous growth, regulatory changes in Western countries facilitated the
introduction of specific forms of technological intervention in the market,
including rules that allowed mechanized forms of clearing and settlement as
well as electronic networks for dealing in securities. In addition, the
initial wave of financial automation fed from the expansion of information and
communication technologies into general business applications (Cortada 2005)
and the ensuing development of new organizational routines around such
technologies. Thus, automation was a collusion of three broad factors:
increased trading volumes, new technologies, and friendly regulatory
intervention.
While some authors would
suggest that in its broadest meaning financial automation has roots in the
development of tabulating machines during the late nineteenth century
(see, for instance, Yates
2005), as a category used by investors, regulators, and market participants
“automation” only became relevant in later times. In effect, to restrict the
definition of automation to the second half of the twentieth century brings to
bear the |AQ: 3 historical dimensions of the concept: to automate is
not merely to standardize and mechanize processes. Rather, automation implies
an attempt to create automaticity in a system, to give it some form of
endogenous automatic control. To automate is, in a sense, an explicit quest to
construct an automaton, to create a sophisticated machine that simulates,
perhaps even stands in place of, reality (Baudrillard 1996; Bedini 1964). This
dream, to a very significant extent, was only embraced by finance in relatively
recent times.
Financial automation is, above
all, a technological transformation, and, observed from the theoretical
perspectives described in this section, it is revealed to be a multifaceted
creature. In engaging with this creature, it is convenient to deploy an
analytical taxonomy sensitive to the institutional conditions and spheres of
financial practice as well as the drivers fueling technological development and
adoption. A taxonomy addressing the historical development of financial
automation is here defined in terms of two axes.
At one level, we must distinguish between
the relevant spheres of financial activity within which technologies are
adopted. In broad terms, financial activity can be conceptualized as occurring
in three overlapping domains of practice: execution, information dissemination,
and settlement. Each of these domains of practice entails different institutional
actors and conditions. Thus, firms involved in settlement and clearing are notably
different from those involved in selling and distributing information to the
marketplace. A different level is given by the distinct drivers of
technological development and adoption. Such drivers capture the institutional
rationale leading firms and policymakers to acquire or campaign for particular
systems and technological solutions. Historically, we can speak of four such
drivers, namely costs, efficiency, control, and surveillance. The drivers are
further described below.
Projects of financial
automation often occur in connection to the deployment of four specific logics.
The first and perhaps most prominent is pecuniary, and this is largely
compatible with canonical economic theories of technological change. For
proponents of automation, developing and adopting new technologies responds to
cost incentives that can materialize as reductions in skilled labor force and
increases in the productivity of specific processes. A historical illustration
is given by the automation of settlement and clearing. Described in Charles
Babbage’s account of the “original” computer at the Bankers’ Clearing House in
London (Babbage 1835), settlement is the process whereby the deals reached in
the marketplace are formalized, and securities and cash are exchanged between
buyers and sellers. But settlement was traditionally a labor-intensive activity,
requiring a gargantuan computer formed by armies of couriers, skilled clerks,
countless pencils, paper, calculating machines, and the occasional lawyer, all
of whom
would work in unison to match, confer, and
finalize every single trade in the market. Consequently, changes in settlement
were driven primordially by cost. Current forms of settlement have substituted
the humans and paper jams of the past with electronic relational databases,
telecommunication networks, enterprise management software, and technicians of
several sorts that match and confer orders at much lower costs (Pardo- Guerra
2010; Wells 2000).
Although costs and
efficiencies are related, the latter is not necessarily an implication of the
former. Bearing a long and illustrious intellectual history (Alexander 2008),
efficiency is much a techno-economic measure as it is an object of ideological
intervention. Within finance, efficiency is often presented as a defining
characteristic of virtuous mar kets (Fama 1970). Indeed, the discursive
supremacy of efficiency has fueled some of the most historically relevant
projects of automation. The emergence of the National Market System in the
United States, for instance, was arguably influenced by ideals of efficiency as
paramount to fairness and justice in the national marketplace (see the work of
Mendelson and Peake 1979). In this sense, automation is a project informed by
the nor- mativities and politics of efficiency, shared by market participants,
regulators, and technologists. Technology is not only a solution to the
cost-benefit challenges of economic competition, importantly, it is framed as a
worthy element that will make markets more transparent, efficient, and fairer.
Technology is, in this sense, the means for the realization of an ideal (and
ideological) marketplace.
The third driver is
organizational: implementing automated systems is not merely a response to
exogenous market signals, fundamentally it is also an intelligible solution to
problems of governance, command, and control. Automated technologies are introduced
to achieve fairness among a set of market participants by, for instance, giving
equal access to market information (Preda 2006), but technologies are also
introduced to configure regimes of governance and accountability within
specific domains, as demonstrated by the hierarchical accounting systems of
financial institutions (Hatherly, Leung, and MacKenzie 2008; Power 2007). A
shared database is not only a convenient tool for collective work: crucially,
it is a mechanism for managing a project and its participants; it is as much
an instrument of power as it is one of distributed cognition.
Automation also entails shifting the
boundaries of what and who is visible. Markets, however technological and
automated they may seem, have always required some level of manual
intervention, be it in the form of the trader’s judgment in calibrating
specific automated trading systems or incarnate in the technologists who design
and maintain the platforms of exchange. Behind the machines of automated
finance one will always
find one form or another of human agency. Financial automation, in this sense, is coupled to specific forms of organizational self-representation that render some people invisible while making others more prominent. Like the chief engineer of heavy industry, elite financial managers gain visibility for their ability to coordinate the machinery of the market. And, like the skilled worker on the shop floor, “traditional” traders lose some of their political and symbolic prominence to novel types of intermediaries, such as individuals with training in science and engineering, who have an allegedly closer control of sophisticated market technologies. Automation can be, as Marx once argued, a means for dispensing with human power, for reconfiguring organizations around the needs of a specific group. Automation is as much about cost and efficiency as it is about control.
find one form or another of human agency. Financial automation, in this sense, is coupled to specific forms of organizational self-representation that render some people invisible while making others more prominent. Like the chief engineer of heavy industry, elite financial managers gain visibility for their ability to coordinate the machinery of the market. And, like the skilled worker on the shop floor, “traditional” traders lose some of their political and symbolic prominence to novel types of intermediaries, such as individuals with training in science and engineering, who have an allegedly closer control of sophisticated market technologies. Automation can be, as Marx once argued, a means for dispensing with human power, for reconfiguring organizations around the needs of a specific group. Automation is as much about cost and efficiency as it is about control.
Automated technologies stand at the core of
most of the practices in the financial services industry, embodying the
equations, algorithms, and forms of visualization through which intermediaries
engage with the market, gauge risk, and construct collective strategies
(Beunza and Stark 2004; Knorr Cetina and Bruegger 2002; MacKenzie 2003; Mayall
2006; Preda 2009). But, owing to their capacity to record vast quantities of
data, such technologies are also useful in monitoring the (mis)behavior of
market participants (Williams 2009). Support for automation has often come
from regulatory agencies that see in electronic systems the possibility of
complete surveillance. Indeed, the image of technology as means for achieving
total control, command, and intelligence over the world is not new (see, for
instance, Edwards 1996; Mirowski 2002) and has roots in technocratic discourses
across the political spectrum (Boettke 2006).
These drivers had different expressions
across the three spheres of financial activity (execution, information
dissemination, and settlement). To illustrate the role played by these drivers
in shaping the evolution of financial technologies, this section explores how
automation evolved in different spheres of practice. We will start our
exploration from the end of the trade (settlement) to its initiation (advice),
reflecting to some extent on the historical diffusion of automation within
finance.
Exchange ultimately requires
the transfer of money and property rights between buyers and sellers. Keeping
track of and successfully completing financial transactions there
fore requires vast
calculative efforts: matching deals, correcting for errors, and controlling
the transfer of certificates and money across physical and electronic domains.
Effectively, the earliest forms of financial automation occurred in settlement
operations in the early twentieth century, with the application of tabulating
machines initially (c.i94os) and computers subsequently (c.i96os) to the accounting
systems of the back office. The criticality of these systems (and thus, the
possibilities for automation) was made evident in a series of episodes of
systemic stress, when trading levels exceeded the capacity of manual order
processing and required more efficient settlement systems (e.g., Wall Street’s
paper jam of 1963; see Wells 2000).
After the initial wave of
settlement automation, back-office settlement and clearing operations moved
away from in-house systems onto independent, often collaborative, ventures.
This integration of settlement was driven not only by costs and economies of
scale but, as importantly, by notions of control; while settlement was
traditionally a responsibility of stock exchanges, it was taken under the
control of consortiums formed by end users such as institutional investors and
investment banks.
This reconfiguration, which
started in the late 1980s, resulted from two interrelated processes. At one
level, the dynamics of settlement responded to the physical possibilities presented
by the internationalization of finance of the second half of the twentieth
century: as firms extended their reach throughout the globe, high-reliability
proprietary communications networks became increasingly attractive mechanisms
for information exchange and made possible for things to be settled across
borders (Loader 2005). The costs associated with maintaining the infrastructure
of proprietary networks, however, were often prohibitive unless syndicated,
leading to industry-wide initiatives that provided a common platform for
communication. Similarly, the fact that the shared networks were based on
standardized protocols of data inputting and message transmission allowed for
reductions in operational risks associated with the use of free texts in financial
communications (these risks emerge due to differing interpretations of a
specific input, which can be reduced through standardization; see the analysis
of SWIFT by Scott and Zachariadis 2010).
The consolidation of
clearing and settlement also follows from the imperatives associated with the
mechanics of settlement, including reducing conflicts around error correction
and isolating risk along rational/functional lines. At the organizational
level, for instance, clearing institutions provided a relatively neutral ground
for matching trades, one which would have been difficult to internalize by the
firms that originated orders. By centralizing the operation under a single
institutional arrangement, clearing houses provide a legitimate mechanism for
resolving conflicting trade reports. Such a role, furthermore, made clearing
and settlement institutions repositories of specialized forms of legal and
bureaucratic knowledge that would have been costly to create and maintain
within traditional trading venues such as stock exchanges, and medium-sized
broking firms and investment banks.
At a regulatory level,
innovations such as the dematerialization of shares followed from attempts by
policymakers to minimize risks borne out of the physicality of paper as a
medium of legal instruments (Cerny 1994). These regulatory shifts were fueled
by
notions of efficiency,
deeming physical shares inadequate for a globalized economy. As a measure of
financial policy, operational risks in settlement are often seen as incompatible
with market risks, requiring the creation of distinct, legally independent,
institutions. Although such rationalization of risks by no means implies the
detachment of clearing and settlement from trade (Millo et al. 2005), it
nevertheless implies a transformed industrial organization and, concomitantly,
the emergence of novel organizational cultures, expertise, and systemic
interdependencies.
An interesting element of
the technological trajectories of clearing and settlement concerns their
relation to the temporalities of markets and how they reflect technological
and economic notions of efficiency (Miyazaki 2003). Clearing and settlement are
performed over relatively long temporal windows—for instance, regulations
stipulate that settlement should occur within days of a transaction, rather
than hours, minutes, or seconds—the systems implemented in this area tend not
to be time-critical but, rather, to focus on achieving resilience, stability,
and reach. Such characteristics are visible in the development and evolution of
so-called large-value payment systems (LVPS). Designed as conduits for large
monetary transfers between financial institutions (notably, banks), LVPS
constitute the technological backbone for mobilizing financial capital across
the world.
Yet, a key aspect
configuring the shape of such systems is their attempt to minimize “systemic
risks” derived from the discontinuities of everyday financial exchange. The
unsettled deals remaining at the end of a working day are sources of risks. An
illustration of this is provided by the fund transfer system of the United
States’ Federal Reserve—Fedwire. Established in 1918 as a proprietary
telegraphic network that allowed funds to be transferred between the 12 Federal
Reserve Banks in America, Fedwire was opened to nonmember users in 1981 (FRBNY
2010). Since clearing is a discontinuous process, “financially healthy” users
of Fedwire are allowed to incur in daylight over- |AQ: 6 drafts. Such
overdrafts, however, can be considerable. While the value of transactions in
Fedwire in 2003 was in the order of $704 trillion (Martin 2005), daily
overdrafts stood at around $65 billion in 2008 (Federal Reserve 2009). As a
form of debt, the overdraft bears a settlement risk. A default can have serious
consequences on the stability of the market by unravelling a series of large
unsettled positions.
With the growing volumes of
international transactions and the overall organizational complexity of
clearing, settlement, and payment systems (BIS 2008), real-time communications
and processing are increasingly forwarded as logical bridges between continuous
intraday trading and seamless payment. In effect, under the normative umbrella
of efficiency, a trend exists within financial markets to consolidate the industrial
organization of settlement (BIS 2005) and accelerate its pace of operations in
order to bring them into line with the speed of trading. Arguably, the
technological developments in clearing and settlement are making financial
markets resemble their economic idealizations by reducing the separation
between the trades as conducted on the screen and those conducted on the books:
with real-time settlement, execution will be tantamount to exchange.
FINANCIAL AUTOMATION, PAST, PRESENT, AND FUTURE
577
A thread linking the
evolution of different automated market systems is the provision of electronic
forms of market information. Automation in finance is embedded in an earlier
proliferation of electronic communication systems, which included entities such
as the telegraphic networks of Reuters (Read 1992) that served as predecessors
to the latency-sensitive networks of today’s trading venues. Not only do these
forms of information dissemination shape the forms of apprehension of market
participants (Preda 2009), but they also shape the possibilities of evolution
for the system as a whole.
Market information is
undoubtedly central to modern finance. Market information sets the pace for the
market serving as the basis for future economic action and as an obligatory
referent for justifying past behaviors. Market information, in particular, is
the element that closes the self-referring loop of the financial space: it is
created by the market for the consumption of market participants. Yet market
information is a peculiar object of consumption. Its afterlife is null, its
contents are varied, and its effects unpredictable by definition (Knorr Cetina
2010). It is, furthermore, customarily attached to the technicalities of
financial communication, from the codes and protocols of accounting that imbue
company reports to the very architecture of the information networks that
distribute data across the world. Indeed, the automation of the dissemination
of market information has been the basis of much of the automation of trading
and settlement services, since these two necessitate information in order to
operate.
^ Owing
to its importance, the main driver of the automation of market information is ^
control: over its
production, dissemination, and use. The initial waves of automation in
information dissemination trace to the nineteenth century, when telegraphs were
introduced to finance (Preda 2006, 2009). These technologies, however, were
not truly automated in a modern sense—they required armies of clerks to feed
and interpret information.
Automated information
systems emerged with the adoption of computer technologies which, coupled to
communication networks, allowed for new forms of data dissemination. In
London, for instance, the introduction of automated information systems in the
late 1960s and early 1970s occurred as a result of the technological spillovers
from settlement (that is, the investments in computers that were purchased for
settlement but could be put to additional uses), as well as the realization
that distributing information was a profitable venture in itself (Pardo-Guerra
2010a, 2010b). The control of information in London by means of sophisticated
telecommunications systems represented not only a narrow commercial strategy
but, more broadly, control over the marketplace; it was, above all, a
demonstration of power of the main trading venue in Britain, the London Stock
Exchange (LSE). It was only in the 1990s that regulatory intervention
“unbundled” the stock exchange’s relative monopoly, obliging it to distribute
market information to secondary resellers under principles of fairness,
equality, and efficiency.
In
America, the automation of market information was driven primarily by regulatory
concerns. The historical predominance of the New York Stock Exchange (NYSE)
over the national securities market provided
an incentive for the Securities and Exchange Commission (SEC) to endeavor to
put in place a comprehensive program of automation that included the creation
of a consolidated system for market information, one that would link different
trading venues through electronic means. Thus, starting in the late 1960s, a
series of technological systems were deployed to create a national infrastructure
for the flow of market information. In America, the automation of market
information was also a response to control, but, unlike Britain, control was
not of an institution over the market but rather of the regulator over an
institution, the NYSE. The politics of technology in American markets are
largely comprehensible in these terms, as a contest between the once
monopolistic force of the NYSE and the regulatory imperatives of the SEC.
Importantly, the automation
of information dissemination was crucial in allowing for the development of a
third sphere of automated finance: execution. The automation of trades requires
a stable framework of information dissemination, providing equal data on market
events as well as a robust infrastructure for communication through which
actors could engage in exchange. Indeed, some of the most salient examples of
automated trading were the product of the development of sophisticated
informational networks (such as Reuter’s trading systems, which became the
standard for the foreign exchange market from the 1970s onward). Without a
standard platform for information dissemination, automated exchange would be
simply unfeasible.
The automation of trading is
a recent example of changes introduced into the financial system by
technological change. It is not surprising that the demise of physical,
face-to-face trading and the rise of new modes of financial activity through
electronic networks are canonically presented as the exemplars of financial
automation (Castells 2000) and its organizational correlate, financial
globalization (O’Brien 1991; Shiller 2003). The increased use of electronic
systems in the everyday operation of finance is symptomatic of the
institutional developments of the financial services industry over the past
half-century. However, the introduction of these systems did not initially
imply a complete automation and geographic de-location of trading. Most of the
early waves of trading automation located in the 1970s and 1980s concentrated
on the provision of electronic price and quote dissemination services rather
than on the automation of trading per se. Considerable technological,
regulatory, and organizational efforts were required for these automating
technologies to allow trades to move off the floor of stock exchanges and into
the offices of investment banks and other intermediaries.
The consolidation of
automated trading—visible in some recent trends in the use of computer systems
that automatically create orders and submit them to the market without direct
human intervention—was the product of developments that occurred primarily in
the 1990s and early 2000s. For instance, the automation of execution largely
followed the development of
novel investment strategies that were intensive on trading, requiring such
things as adjusting portfolios in real time to changes in the market or in the
expectations of market participants (examples of these are the strategies
followed by hedge funds, which advocated automated trading since the 1990s).
Conceptions of efficiency and control had to congeal in order for automated
trading to become a common feature of financial markets: market participants
had to develop new expectations of the speed of finance as well as instruments
to deal with an increasingly technological and fragmented marketplace. The
automation of trading was not merely a reactive adoption of ready-made
technologies in response to competitive pressures. Quite the contrary, trading
automation was fueled by numerous pressures, with economic incentives providing
but one of a constellation of justifications for technological change.
The historical trajectories
of trading automation are thus varied. In some cases, such as that of the LSE,
automation was almost serendipitous product of, first, the acquisition of
computers to mechanize back-office operations and, second, the hiring of
specialists to implement, maintain, and progress technological systems within
the organization. For the leadership of the stock exchange up to the 1960s,
technology was merely an aid to laborious tasks such as account keeping and
data transmission. As a British broker of the 1970s warned those tempted to
feed their business into a computer, “dealing done that way will never be fun.
Dealing certainly ought to be, and I think that between humans it usually is”
(Paul Bazalgette, quoted in Kynaston 2001). This vision was contrasted by the
views of the LSE’s technological experts. For George Hayter, one of the leading
technology managers of the stock exchange, the market was “100 percent
information. . . . Starting with market information to the broker and his
client, generating an order, [and ending in the] contractual exchange of
ownership and exchange for money. . . . The whole blazing thing is actually
information flow, from start to finish” (Hayter, quoted in Pardo-Guerra 2010).
A relatively small, stable, and politically autonomous group, the heads of
technology departments within the stock exchange drove much of the policies of
market automation. Undeniably fueled by the regulatory incentives of Margaret
Thatcher’s government, the automation of the LSE’s front office in the late
1980s (in the form of automated quotations and execution systems) was thus an
organizational outcome of the empowerment of technologists and their
conceptions of efficiency, derived from the departmental units created to
rationalize the adoption of information technologies for the back office in
the 1960s (Pardo- Guerra 2010).
Other trajectories of market
automation involved qualitatively different processes. The automation of the
Paris Bourse, for instance, was framed by a constant negotiation of the
technical translation of accuracy, fairness, and justice in the construction of
its first automated quotation system, the Cotation Assistee en Continu (CAC).
Introduced in 1986 for dealing in the less liquid securities, and implemented
over the entire market in 1989, CAC was originally planned as a technological
solution to the long-standing informational asymmetries of the open outcry
system that traditionally characterized exchange on the Parisian trading floor.
The development of CAC, however, encountered problems notably different from
those that percolated systems production in the City of
London. Derived from
Toronto’s Computer Assisted Trading System (CATS), the construction of CAC was
not mired in the difficulties of creating a new system from scratch or of
erecting a new and competitive mechanism on the basis of legacy systems as had
been the case of the LSE. While the crux of British finance was grappling with
the organizational politics of an expanding material market agencement, French finance was entangled in the
politics of the algorithmic configurations that were to substitute face-
to-face trading (Muniesa 2003). With automation, order queuing, trader
anonymity, and the definitional and procedural aspects of informational
intermediation became contested issues upon which actors had to settle in order
to allow the symbols presented by the automated quotation system to be
perceived as accurate and legitimate sources of economic action (Muniesa 2007).
For machines to serve as the basis for exchange, the politics of meaning had to
cool down.
Both Paris and London share
the commonality that governmental intervention— whether in the form of
specialized reports, as in the case of French financial reform, or the threat
of anti-monopolistic actions, as was the case of Britain—influenced the pace
and direction of automation. The guiding role of regulation, however, is
visible in the paths taken by the technological infrastructures of the American
financial sphere. Financial markets in America were configured by two different
influences: competition and regulation. The American financial system reflected
a fragmented history, with different trading venues competing to capture a
larger share of the market. For instance, although prominent and emblematic of
Wall Street, the NYSE shared the financial space with regional exchanges—from
San Francisco and Philadelphia to Chicago and Boston—national trading
venues—including the American Stock Exchange and the National Association of
Securities Dealers—and so-called “Electronic Communication Networks” like
Instinet.
Competition was tempered by the centralizing
agency of the SEC, which since the 1930s was the uncontested regulator for
banking and financial industries. Through its political clout, the sec proved fundamental in
catalyzing the automation of American finance. Authorized by Congress in 1961,
the sec
created
a special group responsible for studying and investigating the “adequacy, for
the protection of investors, of the rules of national securities exchanges and
national securities associations” (HCC 1961). Published in 1963, the Report of
the Special Study Group stressed the advantages of automation and electronic
quote dissemination in “vastly increasing the flow of market information and .
. . insuring better executions for the public” (SEC 1963). Surveying the
future, the Special Study prepared the grounds for digital finance. From their
consultation with specialists in electronic technologies, the Special Study
Group noted
the potentiality of a system which would
select the best bids and offers, execute orders, and clear transactions.
Transmitting and receiving units would be installed in the offices of all
subscribing broker-dealers. Wholesale dealers and other broker- dealer
subscribers could enter quotations (and size of market) into a central computer
for indexing under the appropriate security and could interrogate the computer
to determine the highest bid and lowest offer, selected by the computer,
together with the number of shares bid and offered at such prices. (SEC 1963)
FINANCIAL AUTOMATION, PAST, PRESENT, AND
FUTURE 581
The fragmented marketplace,
the “lack of central location,” could thus be “overcome by the use of a single,
central computer” from which information about trading would flow to both the
professional dealer and the public.
Information technologies became instruments
of control and regulation. By the mid- 1970s, the US Congress and the SEC
extended their regulatory control through the transformation of the
infrastructures of American finance. Amendments to the Securities Exchange Act
in 1975, in particular, mandated the development of a National Market System
(NMS), giving oversight and control over its establishment to the SEC. The
objectives of the NMS resounded both with the ideals of economic theory and the
regulatory imperatives of the SEC. The novel arrangement was to enhance the
economic efficiency of transactions, ensure fair competition, provide broad
availability of information, and—subjected to best execution policies—guarantee
the possibility of automating trades. Toward the end of the 1970s, a suite of
technological systems gave shape to the NMS: while the Consolidated Tape System
unified the reporting of trades, the Consolidated Quotation System created
streams of market information from the trading venues to data vendors.
Where are these innovations
heading? In the past two decades, automation has spread throughout finance,
redefining much of the way in which markets operate. It is now common to
encounter discussions among both regulators and market participants that boil
down to controversies on the technological infrastructure of the marketplace.
The levels of technological sophistication of investment firms are historically
unparalleled. And the very pace of innovation is increasingly hectic: the chip
maker Intel, for instance, operates a research and development center in
Slough, UK, that caters specifically to the needs of the high-speed,
latency-sensitive sectors of the securities industry. The same drivers apply as
before: costs, efficiency, control, and surveillance interact to shape the
trajectories of market technologies in the present as much as they did in the
past.
An interesting feature of
current trends of technological innovation in finance that derives from the
combination of these drivers and the sociological nature of economic knowledge
is the emergence of what could be referred to as a pattern of fragmented
innovation. Fragmented innovation may well constitute a descriptor for the
future of finance, a future largely configured through the dynamics of
technology in general and automation in particular.
Fragmented innovation
derives from the interaction of three aspects of the financial system:
competition, innovation, and knowledge. It is clear that economic considerations
remain at the core of most of the developments in finance and, compounded with
regulatory pressures toward increased competition, costs are paramount to the
survival of firms and their financial innovations. Firms within the financial
system—from traditional investment banks to sophisticated funds—have to
compete fiercely to attract
business and maximize
returns. Such competition can occur in numerous ways. However, most forms of
competition are based on either technological advantages (for instance,
possessing a fast system that outpaces those of competitors) or technical
advantages (such as having better trend-prediction algorithms or risk control
models). Effectively, trading takes place in a knowledge-intensive domain in
which technology and technique are paramount: information is not only the blood
of the marketplace, it is the ultimate source of profits, making algorithms and
a few microseconds of execution speeds features that separate winners from
losers.
But in such a
knowledge-intensive domain, secrecy is bound to emerge. Indeed, preliminary
evidence suggests that in the most technologically intensive pole of the investment
domain (that of high-frequency traders, which are highly automated,
sophisticated market participants who utilize algorithms to trade thousands of
shares in fractions of a second), interfirm communication is particularly
scarce: information about strategies, algorithms, and system configurations is
worth its weight in gold. Hence, incentives do not exist for systemic
coordinated innovation; innovation occurs largely in secretive silos, all of
which are aimed in the same direction: increasing the speed and reducing the
costs of the system.
The outcome of such a process is one in
which structural uncertainty emerges: every actor in the marketplace uses its
own standards, algorithms, and processes, hiding them from competitors.
Furthermore, there is no incentive for transparency, given that transparency
has a negative impact on profits. Under such structural uncertainty the market
becomes more difficult to predict and regulate; it becomes impossible to know the market. The mechanisms of coordination that exist
in an open market and which link disparate sets of local knowledge (von Hayek
1949) are lost in a fragmented system, catalyzed by the pressure of
competition. The market becomes less tractable among its participants and, in
the event of mistakes, more prone to oscillations. The extreme events of the
so-called flash crash of May 6, 2010, demonstrated the fragmented technological
fabric of finance and may be evidence of this pattern of innovation: despite
months of work and gigabytes of data, the commission convened to analyze the
flash crash was unable to produce an account of the events that convinced most
market participants. Ironically, the same technologies once introduced as
instruments of surveillance and control have colluded to create an increasingly
unknowable system.
The pervasive presence of
technology in the financial sphere may give the impression that markets are
evolving toward an increasingly automated state. This may be true from one
perspective, but such claim would miss a critical aspect of technological
development in finance: manual intervention is always present as technologies
remain irrelevant outside of the networks of humans and nonhumans in which they
acquire meaning. In trading, decision-making remains a highly interpersonal activ-
FINANCIAL AUTOMATION, PAST, PRESENT, AND
FUTURE 583
ity, populated by a
plurality of instruments and devices that are utilized in judging the state of
the market and constructing positions in the system. And despite the growth of
algorithmic systems that automate some of the decision-making process,
fine-tuning parameters and responding to market surprises is an activity in
which expertise and experience remain key referents. Even in the highly
electronic domain of market information, there remain numerous instances of
manual intervention. Documents have to be read, interpreted, and reformatted
before they become information and are distributed to users. Automation is
always incomplete, and it is precisely its inherent incompleteness which
fuels, to an extent, further technological change in the marketplace.
Automation has important
consequences on the evolution of markets. At the end of the day, automation
requires armies of technologists, who through the years have become central to
the growth and reconfiguration of finance. Expert technologists involved in the
automation of financial centers are, in a way, the human tails of the market’s
microstructures. Traditionally conceptualized in terms of the formal rules of
exchange that define the interactions of the marketplace (O’Hara 1995), market
microstructures are also comprehensible in terms of the material arrangements
that shape, constrain, and make possible the practices of financial agents
(cf., Beunza and Stark 2004; Zwick and Dholakia 2006). Here, technologists—from
engineers to managers, from programmers to vendors—must be understood not as
providers of instrumental platforms, of crystallizations of rules of exchange,
but as active shapers and modifiers, expert constructors of the platforms of interaction,
of the microstructures of the market itself.
Considering engineers and technologists—that
is, the key agents of automation—as active participants in the history of
finance implies embracing their heterogeneous practices and promissory expectations
as elements that shape the evolution of finance. Finance is not merely driven
by a quest for profits. It is as much driven by pragmatic ideologies of
efficiency as by the political discourse of control. Indeed, the forms of decentralized
innovation that characterize the development of financial systems are central
to an explanation of the dynamics of financial change. There is, in this sense,
no single trajectory, no standardized route for market evolution, but rather
an ecology of instruments, platforms, techniques, and worldviews that define
the past, present, and future of action in the financial sphere.
Alexander, J. K. (2008).
The Mantra of Efficiency: From Waterwheel to Social Control. Baltimore,
MD: Johns Hopkins University Press.
Arrighi, G. (1994). The Long
Twentieth Century: Money, Power, and the Origins of Our Times.
New York: Verso.
Attewell, P. (1987). “The
Deskilling Controversy.” Work and
Occupations, 14/3: 323-46. Babbage, C. (1835). On the Economy of Machinery and Manufactures (4th edn). London:
C. Knight.
Baudrillard, J. (1996). The System of Objects. New York: Verso.
Bedini, Silvio A. (1964).
“The Role of Automata in the History of Technology.” Technology and Culture, 5/1: 24-42.
Beunza, D. and Stark, D.
(2004). “Tools of the Trade: The Socio-Technology of Arbitrage in a Wall Street
Trading Room.” Industrial and
Corporate Change, 13/2: 369-400.
Bijker, W. E. and Law, J. (1992). Shaping
Technology/Building Society: Studies in Sociotechnical Change. Cambridge, MA: MIT Press.
------ , Hughes, T. P., Pinch, T. J., and
American Council of Learned Societies. (1987). The Social
Construction of Technological
Systems: New Directions in the Sociology and History of Technology. Cambridge, MA: MIT Press.
BIS (Bank for International
Settlements) (2005). New
Developments in Large-Value Payment Systems. Basel: Bank for International Settlements.
------ (2008). The Interdependencies of Payment and
Settlement Systems. Basel: BIS.
Boettke, P. 2006. “Hayek and
Market Socialism,” in E. Feser (ed.), The Cambridge Companion to Hayek. Cambridge: Cambridge University Press.
Braverman, H. (1974). Labor and Monopoly
Capital: The Degradation of Work in the Twentieth
Century. New York: Monthly Review
Press. |AQ:
7
------ (1999). “Technology and Capitalist
Control,” in D. MacKenzie and J. Wajcman (eds.),
The Social Shaping of Technology. Maidenhead: Open University
Press. |AQ:
8
Castells, M. (2000).
“Information Technology and Global Capitalism,” in A. Giddens and
W. Hutton (eds.), On the Edge: Living with Global Capitalism. London: Jonathan Cape. |AQ:
9
Cerny, P. G. (1994). “The
Dynamics of Financial Globalization: Technology, Market Structure, and Policy
Response.” Policy Sciences, 27/4: 319-42.
Cortada, J. W. (2005). The Digital Hand, Volume
2: How Computers Changed the Work of American Financial, Telecommunications,
Media, and Entertainment Industries. New York:
Oxford University Press.
Daston, L. and Galison, P.
(2007). Objectivity. Brooklyn, NY: Zone Books.
Edwards, P. N. (1996). The Closed World Computers
and the Politics of Discourse in Cold War America. Cambridge, MA: MIT Press.
Federal
Reserve (2009). Fedwire Funds
Transfer System. |AQ:
10|
Fligstein, N. (2001). The Architecture of
Markets: An Economic Sociology of Twenty-First Century Capitalist Societies. Princeton, NJ: Princeton
University Press.
FRBNY (Federal Reserve Bank
of New York) (2010). Fedwire"
and National Settlement |AQ: 11 Services.
Friedman, B. (1980). Post-War Changes in the
American Financial Markets. Cambridge:
National Bureau of Economic
Research.
Hatherly, D., Leung, D., and
MacKenzie, D. (2008). “The Finitist Accountant,” in T. Pinch and R. Swedberg
(eds.), Living in a Material
World: Economic Sociology Meets Science and Technology Studies. Cambridge: MIT Press. |AQ: 12
HCC
(House Commerce Committee) (1961). Securities Market Investigation. |AQ:
13|
Knorr Cetina, K. (2010).
“The Epistemics of Information.” Journal
of Consumer Culture, 10/2:
171-201.
------ and Bruegger, U. (2002). Global
Microstructures: The Virtual Societies of Financial
Markets. American Journal of Sociology, 107/4: 905-50.
Krippner, G. R. (2010). Capitalizing on Crisis:
The Political Origins of the Rise of Finance. Cambridge, MA: Harvard University Press.
Kynaston, D. 2001. The City of London: A Club
No More, 1945-2000. London: Chatto &
Windus.
financial automation, past,
present, and future 585
Loader, D. (2005). “The Role of the Clearing
House,” In Clearing and
Settlement of Derivatives.
Oxford:
Butterworth-Heinemann. |AQ:
14
MacKenzie, D. (1984). “Marx and the Machine”
Technology and Culture, 25/3: 473-502.
------ (2003). “An Equation and its Worlds” Social Studies of Science, 33/6: 831-68.
------ and Millo, Y.
(2003). “Constructing a Market, Performing Theory: The Historical
Sociology of a Financial Derivatives
Exchange” American Journal of
Sociology,
109/1:
107-45.
MacKenzie, D. and Wajcman, J. (1999). The Social Shaping of Technology (2nd edn).
Philadelphia: Open University Press.
Martin, A. (2005). “Recent
Evolution of Large-Value Payment Systems: Balancing Liquidity and Risk.” Federal Reserve of Kansas City Economic Review, 2005/1: 33-57.
Mayall, M. (2006). ‘“Seeing
the Market’: Technical Analysis in Trading Styles” Journal for the Theory of Social Behaviour, 36/2: 119-40.
Mendelson, M. and Peake, J. W. (1979). “The
ABCs of Trading on a National Market System.”
Financial Analysts Journal, 35/5: 31-42.
Merton, R. and Bodie, Z.
(2005). “Design of Financial Systems: Towards a Synthesis of Function and
Structure” Journal of Investment
Management, 3/1: 1-23.
Millo, Y., Muniesa, F., Panourgias, N. S.,
and Scott, S. V. (2005). “Organised Detachment:
Clearinghouse Mechanisms in Financial
Markets” Information and
Organization, 15/3:
229-46.
Mirowski, P.
(2002). Machine Dreams: Economics Becomes a Cyborg Science. Cambridge:
Cambridge University Press.
Miyazaki, H. (2003). “The Temporalities of the Market.”
American Anthropologist, 105/2:
0 255-65 # Muniesa, F. (2003). “Des marches comme
algorithmes: sociologie de la cotation electronique a la Bourse de Paris” PhD
thesis, Ecole des Mines de Paris, Paris.
------ (2007). “Market Technologies and the Pragmatics of
Prices” Economy and Society, 36/3:
377-95.
Noble, D. (1978). “Social
Choice in Machine Design: The Case of Automatically Controlled Machine Tools,
and a Challenge for Labor” Politics
& Society, 8: 313-47.
O’Brien, R. (1991). Global
Financial Integration: The End of Geography. London: Pinter Publishers.
O’Hara, M. (1995). Market Microstructure Theory. Cambridge, MA: Blackwell
Publishers.
Orlikowski, W. J. (1992).
“The Duality of Technology: Rethinking the Concept of Technology in
Organizations.” Organization
Science,
3/3: 398-27.
Pardo-Guerra, J. P. (2010a). “The Automated
House: The Digitalization of the London Stock Exchange, 1955-1990,” in B.
Batiz-Lazo, J. C. Maixe-Altes, and P. Thomes (eds.), Technological Innovation in Retail Finance:
International Historical Perspectives. London: Routledge. |AQ: 15|
------ (2010b). “Creating Flows of Interpersonal Bits: The
Automation of the London Stock
Exchange, c. 1955-1990” Economy and Society, 39/1: 84-109.
Perrow, C. (2010). The Next
Catastrophe: Reducing our Vulnerabilities to Natural, Industrial, and Terrorist
Disasters. Princeton, NJ: Princeton University Press.
Power, M. (2007). Organized
Uncertainty: Designing a World of Risk Management. New York:
Oxford University Press.
Preda, A. (2006). “Socio-Technical Agency in
Financial Markets” Social Studies
of Science,
36/5: 753-82.
------ (2009a). “Brief
Encounters: Calculation and the Interaction Order of Anonymous
Electronic
Markets” Accounting, Organizations and Society, 34/5: 675-93.
586
JUAN PABLO PARDO-GUERRA
------ (2009b). Framing Finance: The Boundaries of
Markets and Modern Capitalism. Chicago:
University of Chicago Press.
Read, D. (1992). The Power of News: The
History of Reuters, 1849-1989. Oxford: Oxford University Press.
Scott, S. and Zachariadis, M. (2010). “A
Historical Analysis of Core Financial Services Infrastructure: Society for
Worldwide Interbank Financial Telecommunication (S.W.I.F.T.).” Information
Systems and Innovation Group, Department of Management, LSE, Working Paper No.
182.
SEC (Securities and Exchange Commission)
(1963). Report of Special Study
of Securities Markets. Washington: U.S. Government Printing Office.
Shiller, R. J. (2003). The New Financial Order: Risk in the 21st Century. Princeton, NJ: Princeton
University Press.
Strange, S. (1986). Casino Capitalism. Oxford: Basil Blackwell.
Von Hayek, F. A. (1949). Individualism and Economic Order. London: Routledge &
Kegan Paul.
Wells, W. (2000). “Certificates and Computers:
The Remaking of Wall Street, 1967 to 1971.” The Business History Review, 74/2: 193-235.
Williams, J. W. (2009). “Envisioning
Financial Disorder: Financial Surveillance and the Securities Industry.” Economy and Society, 38/3: 460-91.
Yates, J. (2005). Structuring the
Information Age: Life Insurance and Technology in the Twentieth Century. Baltimore, MD: Johns
Hopkins University Press.
Zwick,
D. and Dholakia, N. (2006). “Bringing the Market to Life: Screen Aesthetics and
the Epistemic Consumption Object.” Marketing Theory, 6/1: 41-62.
AQ1: Pl. add page no. of quote.
AQ2: Pl. specify if 2009a or b (see comment
in References).
AQ3: Pl. reword for clarity. Brings to bear
the concept on what?
AQ4: Please specify whether the reference “Pardo-Guera
2010a or 2010b.”
AQ5: Pl. add to References.
AQ6: Pl. clarify: does this mean ‘allowed to
incur overdrafts during daylight hours’? AQ7: Pl. add page range.
AQ8: Pl. add page range.
AQ9: Pl. add page range.
AQ10:
Pl. add publication details.
AQ11: Pl. add publication details.
AQ12: Pl. add page range.
AQ13: Pl. add publication
details.
AQ14: Pl. add page range.
沒有留言:
張貼留言