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REDUCING BEHAVIORAL CONSTRAINTS TO SUPPLIERINTEGRATION: A SOCIO-TECHNICAL SYSTEMS

PERSPECTIVE

THOMAS J. KULLArizona State University

SCOTT C. ELLISUniversity of Kentucky

RAM NARASIMHANMichigan State University

Despite the benefits of supplier integration (SI), research suggests suchcollaborative initiatives are inhibited by behavioral constraints. Whilestudies tend to advance technical reasons that hinder SI, we draw fromsocio-technical system (STS) theory to suggest that the interaction amongsocial, technical, and environmental features can give rise to behaviorsthat constrain SI. We conceptualize buying and supplying firms as twodistinct social-technical systems and SI as a merging of technical systemsacross firms. We posit that behavioral constraints, which limit the realiza-tion of SI goals, arise when technical integration commences withoutappropriate a priori consideration for the social or environmental implica-tions of technical changes. Our conceptual development not only pro-poses specific social processes that increase the likelihood of behavioralconstraints during SI, but also suggests technical approaches to prevent

them. Further, we identify salient environmental contingencies affectingthe emergence of behavioral constraints. By extending STS theory to theinterorganizational context, we contribute to SI research by offering aholistic view of SI and proposing ways managers can address the chal-lenges that exist.

Keywords: behavioral supply management; supplier management; human judgmentand decision making; technology management; conceptual theory building

INTRODUCTIONSupply management problems continue to persist in

many well-known firms (Gilmore, 2006; Koch, 2004;Wailgum, 2007), threatening shareholder wealth

(Hendricks & Singhal, 2003, 2005), and leading firms

to compete through supplier integration (Petersen,

Handfield, & Ragatz, 2005). When supplier integra-

tion (SI) is not achieved (Heriot & Kulkarni, 2001;

Parker, Zsidisin, & Ragatz, 2008; Wagner, 2003), the

literature suggests that it is because of behavioral con-

straints (Fawcett, Fawcett, Watson, & Magnan, 2012).

Behavioral constraints are actions by employees that

inhibit company goals (Mabin & Balderstone, 2003),

and, within the SI context, relate to workgroups in a

buying or supplying firm impeding an SI initiative.

While research reveals useful approaches to addressing

such inhibitors of collaboration (Fawcett et al., 2012),literature lacks an explanation for why SI induces

behavioral constraints and, therefore, how to design

an SI initiative to prevent such behaviors from arising.

We address this by presenting and using socio-

technical systems (STS) theory to conceptually advance

explanations and solutions for behavioral constraints

to SI.

While SI can be technically challenging, there are

also social and environmental forces inhibiting it (Cai,

Jun, & Yang, 2010; Min, Kim, & Chen, 2008; Petersen,

Handfield, Lawson, & Cousins, 2008). SI is defined as

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the unification of processes within and between buy-

ing and supplying firms (Das, Narasimhan, & Talluri,

2006). This contrasts with supply chain integration

that involves both upstream customers and down-

stream suppliers (Fawcett & Magnan, 2002; Frohlich

& Westbrook, 2001). An SI design entails such activi-

ties as information technology investment, newprocess adoption, workflow redesign, planning and

control collaboration, and interorganizational projects

(Vijayasarathy, 2010). With our unit-of-analysis being

a focal buyersupplier dyad, we distinguish between

the process and state of SI. The process of SI represents

a collaborative intra- and inter-firm initiative within

the dyad to unify supply systems (Petersen et al.,

2008). The state of SI represents the degree to which

these systems are unified in forming the SI system.

While the SI initiative seeks a particular state of SI,

the emergence of behavioral constraints results in an

under-realized state of SI. In this paper, we use STS

theorys framework on the interplay of social, techni-

cal, and environmental systems to explain why these

behaviors emerge (Griffith & Dougherty, 2001; Pas-

more, 1988). To do this, we organize the many STS

features into conceptual classifications for developing

our propositions and advancing STS theory as a

means to understand issues relating to SI (Skilton,

2011). While STS theory historically is used to explain

intra-organizational phenomena (Trist & Bamforth,

1951; Trist & Murray, 1993), our study seeks to apply

STS theory to inter-organizational phenomena, show-

ing its usefulness for SI research and practice.

Supply chain literature has drawn upon various the-ories to understand SI-related phenomena. However,

these theories are insufficient in explaining behavioral

constraints to SI. For instance, while transaction cost

theory has been used to characterize efficiency reasons

for SI choices (see Lockstrom, Schadel, Moser, & Har-

rison, 2011; Thomas, Fugate, & Koukova, 2011), it

fails to acknowledge how SI choices are made for

social reasons (Petersen et al., 2008). Likewise, while

resource-dependence theory explains how SI processes

are affected by levels of dependence (see Cai & Yang,

2008; Paulraj & Chen, 2007), it fails to acknowledge

how SI processes emerge from technical design

choices firms make (Carter & Ragatz, 1991). Othertheories like the political economy paradigm (Stern &

Reve, 1980) acknowledge social issues as important

but do not give fine-grained, explanatory structure

useful for understanding SI. Similarly, system-design

theory has aided SI-related understanding (see Fawcett

et al., 2012), but in very general terms. STS advances

a perspective of SI that gives the requisite specificity to

describe social outcomes while going beyond the effi-

ciency- or power-based perspectives of traditional the-

ories. In viewing SI as a technical unification of two

STSs, we identify specific social processes that respond

to the technical unification and lead to behavioral

constraints. Moreover, we suggest changes to an SI

design that promote positive social responses, while

revealing environmental contingencies to help manag-

ers decide where resources should be deployed.

Our conceptual research challenges two assumptions

in the SI literature: (1) that SI designs are not the causeof behavioral constraints to SI, and (2) that negative

consequences of socialization are the result of opportu-

nistic and malicious intent. Rather, our STS perspective

suggests that the way SI initiatives are designed results

in unintended social processes that affect behaviors. As

such, we contribute to SI theory building in several

ways (see Ketchen & Hult, 2011): (1) we extend STS

theory to the inter-organizational context to provide a

framework for understanding behavioral constraints to

SI; (2) we consider a broad array of social, technical,

and environmental factors that inform socialization,

social capital, and dark-side streams of SI research (Ber-

nardes, 2010; Petersen et al., 2008; Villena, Revilla, &

Choi, 2011); (3) we suggest approaches for preventing

problems by designing SI initiatives that account for

social processes; and (4) we reveal fruitful avenues of SI

research and foreshadow new roles that supply manag-

ers will have in years to come. In sum, our paper offers

new interorganizational uses for STS theory while sug-

gesting multiple yet holistic avenues for improving the

theory and practice of SI.

SOCIO-TECHNICAL SYSTEMS THEORY

BACKGROUNDResearch has suggested that STS theory can help sup-

ply processes across organizations (Chen, Daugherty,

& Landry, 2009; Flynn, 2008; Hartley & Jones, 1997).

Because supply processes are STSs that transcend orga-

nizational boundaries (Glaser, 2008), inter-organiza-

tional factors can explain partnering behavior more

than intra-organizational factors (Hofer, Knemeyer, &

Dresner, 2009). Likewise, social factors in supply

chains have been noted to affect technical develop-

ment, implementation, and use (Choi & Liker, 2002).

To this point, Clegg (2000) states:

It is interesting that the examples to illustrate(STS) have all involved change within individual

companies, rather than across companies There

would seem, however, to be no reason why socio-

technical thinking should not be extended to

supply chains, partnerships and other networked

ways of working that cross company boundaries.

(p. 475)

The STS concept originated from studies of British

coal mining methods by the Tavistock Institute (Trist

& Bamforth, 1951). Early STS studies observed that

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employee behavior and work design were so inter-

twined that technical processes could not be under-

stood without understanding social processes (Emery,

1959; Trist & Bamforth, 1951). The original theory

focused on how work practices could increase produc-

tivity without large capital expenditures (Trist, 1981).

Researchers have since applied STS theory to manyfields: human relations (Cherns, 1976; Emery, 1959;

Miller, 1959; Pasmore, Francis, Haldeman, & Shani,

1982; Rice, 1958; Trist, Higgins, Murray, & Pollock,

1963); ergonomics (Clegg, 2000); applied psychology

(Cooper & Foster, 1971); engineering design (Griffith

& Dougherty, 2001); organizational behavior (Fox,

1995; Pasmore, 1988; Seiler, 1967; Susman & Chase,

1986); information technology (Mumford, 2006);

knowledge management (Pan & Scarbrough, 1998);

and general management (Cummings, 1978; Wood-

ward, 1958).

The supply chain field has used aspects of STS the-

ory: social reactions to factory automation (Susman &

Chase, 1986), human resource benefits in cellular

manufacturing (Huber & Brown, 1991), group norms

in self-directed logistics teams (Deeter-Schmelz,

1997), psychological ownership in quality manage-

ment (Manz & Stewart, 1997), socially built compe-

tencies in handling supply chain complexity (Closs,

Jacobs, Swink, & Webb, 2008), and behavioral impli-

cations of supply chain alignment (Glaser, 2008). Not

only do these various applications relate to SI par-

ticularly regarding information automation, work

practices, and structural alignment (Vijayasarathy,

2010) they also reveal the widespread need tounderstand how management practices and social

realities relate.

Although two themes comprise the STS perspective

STS design principles and STS theory (Griffith &

Dougherty, 2001) this paper focuses on STS theory.

STS design principles comprise a subset of STS theory

and have a prescriptive, action-research focus meant

to improve organizational design and the quality of

work life (Cherns, 1987; Clegg, 2000; Mumford,

2006). In contrast, STS theory provides a framework

for understanding relationships within organizations

without prescribing what should be done. The theory

aims to improve understanding before changingorganizational design by stating the underlying causes

for social and technical phenomena. Underscoring

STS theory is the view that managers have options in

designing organizational processes that is, because

socio-technical processes are not strictly determined,

managers have choices in how systems are

designed (Trist et al., 1963). Therefore, understanding

how STS processes interrelate enhances design choices,

and our study seeks to answer why STS processes

within and between firms affect behavioral constraints

to SI.

Elements of Socio-Technical Systems TheorySocio-technical system theory creates a framework to

analyze how components interrelate to affect organi-

zational outcomes while in relation to a relevant

external environment (Emery, 1959). STS theory uses

subordinate concepts and propositions to describe

and explain the behavior of organizations and theirmembers (Emery, 1959) while providing critical

insights into the relationships among people, technol-

ogy, and outcomes (Griffith & Dougherty, 2001).

These relationships can also be seen in exchange

relationships, such as when interpersonal ties form

between firms during supplier selection processes

(Huang, Gattiker, & Schwarz, 2008), or when logistics

managers face resistance to implementing electronic

log-book systems (Cantor, Corsi, & Grimm, 2009), or

when psychological reactions to time pressures hurt

technical knowledge flows (Thomas et al., 2011).

Viewing supply management problems through an

STS lens creates a foundation to explain how people

and processes interact across organizations to influ-

ence better outcomes.

Subsystem Definitions and Assumptions. Socio-tech-

nical system theory encompasses three general subsys-

tems1: technical, social, and environmental (Barko &

Pasmore, 1986; Carayon, 2006; Pasmore et al., 1982;

Seiler, 1967). The technical system consists of the

tools, techniques, artifacts, methods, configurations,

procedures, and knowledge used by organizational

employees to acquire inputs, transform inputs into

outputs, and provide output or services to clients or

customers (Pasmore, 1988, p. 55). The technicalcomponent creates a structure within which organiza-

tional members must operate (Emery, 1959). Organi-

zations add value through technical systems. Because

supply chain management methods such as process

integration, lean systems, enterprise resource planning,

and supplier development are designed to improve

performance, they too are part of the technical system.

The partial unification of this subsystem between buy-

ing and supplying firms is what encompasses SI (Das

et al., 2006; Vijayasarathy, 2010).

The social system is comprised of the people who

work in the organization and all that is human about

their presence (Pasmore, 1988, p. 25), such asattitudes, beliefs, relations, cultures, norms, politics,

behaviors, and emotions. Individuals and groups

achieve ends through social systems, sometimes at the

expense of the organization (Rice, 1958). People rely

on interpersonal contact for self-identity; groups use

social rewards and punishments to regulate members

1Some theorists incorporate organizational structure as a fourthsubsystem (Seiler, 1967), but the broad definition of technology

would include organizational structure (a.k.a. organizationaldesign) because designs are for organizational purposes.

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(Seiler, 1967). Supply chains also have social systems,

with formal and informal networks that cross firm

boundaries and influence behavior (Carter, Ellram, &

Tate, 2007). Individuals and groups in a supply chain

may therefore act for their own purposes, regardless

of supply chain requirements.

The environmental system envelops the social andtechnical systems. Because socio-technical processes

are nested and multilevel (Moray, 2000), the focal

STS defines the relevant environment. Our study

focuses on the buyersupplier dyad, which is com-

prised of a buying firm STS and a supplying firm STS.

Beyond these firms bounds are entities not directly

controlled by ownership or fiat (Ellis, Shockley, &

Henry, 2011). These entities are part of the environ-

mental system, which includes the relevant govern-

mental, economic, industrial, transportation, and

cultural firm contexts (Pasmore, 1988). As such, those

contextual forces surrounding the buyersupplier dyad

constitute the environmental systems of relevance.

Because a focal STS adapts and affects its environ-

ment, an STS is considered an open rather than a

closed system (Emery, 1959). Managers must pursue

strategies, select resources, and implement technolo-

gies aligned with environmental stressors (Rasmussen,

2000). For example, public safety concerns can insti-

gate the implementation of new technical reporting

processes (Carter et al., 2007) or new social sustain-

ability expectations (Tate, Ellram, & Kirchoff, 2010),

all of which influence upstream and downstream

supply chain practices.

Socio-technical systems emerge where social, techni-cal, and environmental systems interact to create orga-

nizational outcomes (see Figure 1). All organizations

are STSs (Cooper & Foster, 1971), as are many aspects

of a supply chain (Choi & Liker, 2002). As Pasmore

states, whenever there are people, working together

in a system with technology, in an environment that

provides resources the system needs, there is the pos-

sibility of adapting STS thinking (1988 p. 155). STS

theory is not focused on social or technical system

self-interaction (Emery, 1959), such as how enterprise

resource planning systems impact six-sigma efforts

(Nauhria, Wadhwa, & Pandey, 2009), or how groups

impact employee satisfaction (Robinson & OLeary-Kelly, 1998). Instead, STS theory describes how results

emerge from interactions among social, technical, and

environmental systems. This macro-level perspective

suggests systemic causes for SI problems, creating new

opportunities for understanding and addressing

behavioral constraints to SI.

Pasmore et al. (1982) lay out assumptions made

within STS theory (shown in Table 1) that can be

grouped into descriptive assumptions (system comple-

mentarities, variance diffusion, boundary location, design

incongruence, and organizational choice) and prescriptive

assumptions (open systems, quality of work life, and joint

optimization). Descriptive assumptions depict how STS

subsystems interact and how managers have a role in

maintaining an STS. The prescriptive assumptions

emphasize that successful STSs require adaptation and

consideration of the human condition. Although the

definitions, boundaries, and assumptions traditionally

refer to a single organization, as buying and supplying

firms unify that they should find these concepts help-

ful in managing SI (Clegg, 2000). For instance, the

design incongruence assumption suggests that supplymanagement activities should adapt to changing cul-

tures and economic conditions (Carter, Maltz, Maltz,

Goh, & Yan, 2010).

Reciprocal Interactions. To further understand

how the elements of a STS influence each other,

Emery (1959), Seiler (1967), Pava (1986), Pasmore

(1988), and Fox (1995) provide detailed features for

the social, technical, and environmental systems

within the STS perspective. These features provide

building blocks for STS-based propositions and

enable SI researchers to identify pertinent STS pro-

cesses. We organize the features into distinct catego-

ries within each system to retain STS theorysuniqueness and generalizability while improving par-

simony and comprehensibility in relation to SI (Wac-

ker, 1998).

As shown in Table 2, we consolidate the technical

features into four technical system concepts that have

social implications. First are technical centralities

(T1) that represent the dominance and importance

of technical process characteristics (Emery, 1959).

Features related to this concept are (1) the levels of

automation that determine relative worker contribu-

tion and (2) the variation in importance of process

Social

System:

Group culture,

social network,

politics, etc.

Technical

System:

Equipment,

methods,

knowledge, etc.

Organizational Outcomes:

Performance, quality of work-

life, etc.

Environmental System:

Industry, government, society, etc.

FIGURE 1General Relationships within Socio-Technical Systems

Theory

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steps that determines an employees role significance.

Second are technical requisites (T2) that represent the

surrounding criteria for technical functioning (Pava,

1986). Features related to this concept are (1) the task

conditions (e.g., physical, psychosocial, knowledge)

from which workers infer their worth and (2) the sup-

port dependencies from which the value of role rela-

tions emerge (Emery, 1959). Third are technical

proximities (T3) that represent the closeness that tech-nical activities have with each other and the environ-

ment (Fox, 1995). Features related to this concept are

(1) spatiotemporal distributions that influence inter-

personal contact and information exchange and (2)

environmental contacts that influence boundary-span-

ning activities. Last are the technical flows (T4) that

represent the stream of value-accumulating artifacts

(e.g., products and ideas) (Fox, 1995). Related features

are (1) input variations that influence stress in the

workforce and (2) technical sequencing that influences

worker skills and knowledge exchange.

The features of a social system from STS theory that

have implications for the technical system are consoli-

dated into the four concepts shown in Table 3. First are

social positions (S1) that represent the locations within

the organizations social structure (Pasmore, 1988).

Features related to this concept are (1) the status land-

scape and (2) social networks, both of which infor-

mally challenge formal relations, controls, and

knowledge. Second are social values (S2) that representthe cultural attitudes within the organization (Pasmore,

1988; Seiler, 1967). Features related to this concept are

the (1) collective predispositions and (2) social needs,

both of which influence how members behave, what is

important, and how decisions are made regardless of

technical needs. Third are social associations (S3) that

represent the composite of functional memberships in

organizations (Seiler, 1967). Features related to this

concept are (1) social roles and (2) affiliations, which

give employees purpose (Kuhn 1976) and influence

levels of cooperation and control (Fox, 1995). Last are

TABLE 1

Assumptions of Socio-Technical Systems Theorya

Descriptive assumptionsSystem complementaritiesb Technical and social characteristics reinforce and/or deter each other.

Variance diffusion

c

Unplanned deviations from technical standards promulgate intothe socio-technical system, creating disturbances andnegative outcomes.

Boundary location Necessary disconnects exist within organizations and between theirenvironments, causing problems with control, coordination andknowledge and requiring managers to span these boundaries.

Design incongruenced Organizational designs eventually become inappropriate within achanging environmental context.

Organizational choice Organizations can be designed in different ways to achieve thesame ends, and knowledgeable choice exists at all levels ofthe organization.

Prescriptive assumptionsOpen systems Organizational survival requires adaptive transactions with a

continually changing external environment.Quality of work life Organizations must consider human needs in the design of work,

beyond the organizational benefits of joint optimization.Joint optimization Organizations function optimally only when both the technical and

social subsystems are designed to fit the demands of each otherand the external environment.

aBased upon Pasmore et al. (1982) in which these were referred to as STS elements.bPasmore et al. referred to this as support congruence, but the underlying issue relates to STS charac-teristics helping or hurting each other.cPasmore et al. referred to this as variance control, but the underlying issue relates to errors havingmultiple effects.dPasmore et al. referred to this as continuous learning, but the underlying issue relates to organiza-

tional designs losing their appropriateness.

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social experiences (S4) that represent the understand-

ings that result from social interactions (Fox, 1995;

Weick, 1995). Features related to this concept are senti-

ments (Seiler, 1967) and social endowments, both of

which are key influences on the efficacy of choices

made in the work place.

Pasmore et al. (1982) describe the way the social

and technical systems interact as multiordered,primary and secondary effects. Primary effects are those

that can be seen in Tables 2 and 3 as the direct reci-

procal influences among features. For instance, techni-

cal centralities (T1) influence the contribution and

significance of workers, which influence the attention

given to them and their influence in the firm that

is, their social position (S1) (Emery, 1959). In turn,

social position affects who is the source of knowledge

in a firm that is, the technical flows (T4) (Seiler,

1967). These primary effects are fairly obvious to see,

such as when employees realize that real-time data

improve customer service (Klein, 2007). Secondary

effects, however, are more difficult to understand

because of the delays and complexities within the

reciprocal STS influences (Pasmore et al., 1982). For

instance, employees may not see that assuring

real-time data requires higher levels of planning and

communication, more software customization, and

more trust between groups (Klein, 2007). Thus, a newlyimplemented technical system places a cascade of

demands across multiple levels of an organization

(Moray, 2000), obscuring the impact that a social or

technical change can have on the STS.

Beyond the interrelations between social and tech-

nical systems, characteristics of the relevant environ-

mental system interact with an STS as summarized in

Table 4. First is equivocality (E1), which character-

izes the nature of interactions between the STS and

external subsystems. Features related to equivocality

are (1) turbulence the rate of change of external

TABLE 2

Technical System Featuresa

Feature Description of Feature and Impact on Social System

T1: Technical centralities Automation: The use of devices (e.g., mechanical, electronic)

for automatic decisions and effort; this determines therelative contribution of people.

Operational impact: The criticality, focus, and skilldemands of activities vary; this influences the significanceof certain work roles.

T2: Technical requisites Condition: The situational task demands in the work setting(e.g., physical and psychosocial) or in the artifacts (e.g.,products and ideas); these can be over/under stimulatingand distracting; workers infer what is valuable by these conditions.

Support dependence: The degree to which processesneed other functions (e.g., maintenance, engineering) tomaintain proper conditions; this influences the value of

role relations.

b

T3: Technical proximities Spatiotemporal distributions: The layout among and timebetween workers, machines, and process steps; theseinfluence coordination and communication requirements,interpersonal contact, and information exchange.

Environmental contact: The importance of inbound and outboundlinkages with the external environment; this creates demands forboundary-spanning management and coordination.b

T4: Technical flows Input variance: The variation from upstream inputs; this continuallystresses labor/skill requirements, straining individuals, workgroups,and management.

Sequencing: The way unit operations (value adding activities) aregrouped into production phases; this influences demands for labor

skills, shared information and knowledge, and coordination.aExpanded from Fox (1995) and Emery (1959).bCharacterizes the boundary conditions for the supply chain management function.

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resources and demands (Pasmore, 1988), (2) com-

plexity the number of inter-relationships among

external resources and demands (Pasmore, 1988),

and (3) connectivity the number and type of link-

ages with entities in the environment (Seiler, 1967).

Turbulence and complexity influence STS-environmentalignment and necessitate adaptations to support the

survival of the STS. Through interactions and associ-

ated information flows, connectivity provides the

means through which the STS gains awareness of the

turbulence and complexity inherent within the envi-

ronment. Second is opportunity (E2), which includes

environmental features influencing the range of feasi-

ble STS designs that satisfy external demands. Fea-

tures related to this concept are (1) resource

alternatives availability of technological, human,

or organizational inputs to facilitate STS designs or

adaptations (Pasmore, 1988) and (2) environmental

mutability the ability of the STS to modify the

elements of the environment, influencing how

constrained the STS is, and whether an internal ver-

sus an external focus is needed for survival (Pasmore,

1988).The above-mentioned STS concepts provide the

basis for the SI propositions given in the next section.

A SOCIO-TECHNICAL PERSPECTIVE ONSUPPLIER INTEGRATION

In this section, we develop STS-based propositions

regarding behavioral constraints pertaining to SI.

Propositions one and two relate to within-firm social

events (i.e., regarding social position and social value);

propositions three and four relate to between-firm

TABLE 3

Social System Featuresa

Feature Description of Feature and Impact on Technical System

S1: Social positions Status landscape: The varying degrees of importance and leadership

among people; these will challenge formally given authorityregarding influence and sources of knowledge.

Social networks: The network of interpersonal relations distributessocial knowledge and opportunities for helpfulness; this createsforms of reciprocity that challenge official knowledge and duties.

S2: Social values Collective predispositions: The shared mental models, motivations,values, norms, self-identity, fairness, and psychological contracts;these each compete with what is important to organizationalperformance.

Social needs: The presence of personal worker goals andinterdependencies; these threaten formally specified organizationalgoals depending upon their over- or under-specification.

S3: Social associations Social roles

b

: The nature of responsibilities (i.e., work roles) withinthe social organization; this impacts cooperative behavior,responsibility for variation in processes and outputs, territoriesand resource allocation.

Affiliations: The influence of informal group membership,accompanied by rewards and punishments; this creates formsof motivation and challenges formal workgroup control.

S4: Social experiences Sentiments: The collective emotional role-experience of workers(i.e. inherent attractiveness, dependence perceptions, justice,subordination, self-worth, trust, and social isolation); thisinfluences decision making and contradict assumed rationality.

Endowments: The basic talents, acquired skills, knowledge,expertise, and professional standards; these create technical

dependencies, allow technical deficiencies, and introducenon-organizational standards in decisions.

aExpanded from Fox (1995), through reexamination of Emery (1959), Seiler (1967), Pasmore (1988).bTerm introduced by Emery (1959) that Fox later divided into four sub-features that can be summarizedas follows: (1) codependency in work roles, (2) output responsibility, (3) distribution of resourceallocation responsibility, and (4) responsibility diffusion of variances.

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boundary-spanning functions. Yet during SI, the

importance of sales/marketing managers may diminish

as technologies that automatically communicate needsreduce the need for intervention (Do Cho & Chang,

2008). Similarly, as the state of SI increases, the PSM

coordination role may be reduced (Emmelhainz, 1987;

Gelderman & van Weele, 2005), threatening its social

position in the buying firm. The SI initiative, therefore,

can threaten existing social positions, particularly

within the traditional boundary-spanning functions,

while concurrently giving social position opportunities

for a firms engineering, production, or IT functions.

Interestingly, while literature suggests that high PSM

social position is needed for instigating an SI initiative

(Paulraj & Chen, 2007), the STS perspective suggests

that PSM social position can be threatened as SI is

implemented.As social position is threatened, behavioral con-

straints will emerge. According to STS theory, workers

within functions have their own goals beyond those

of the organization (S2 in Table 3), and maintaining

ones functional social position is significant (Seiler,

1967). Threats to social position from technical cen-

tralities can be met with resistance (Pasmore, 1988),

that is, sabotage, withdrawal, reducing commitment,

and ignoring requests (Kirkman & Shapiro, 1997).

Such resistance may manifest itself in the types of

technical choices employees make (see Table 1). For

Social

System

Technical

System

Sales / Marketing

Operations,

R & D, and others

Technical

System

Social

System

Purchasing

Operations,

R & D, and others

Social

System

Technical

Systems

Sales / Marketing

Social

System

Purchasing

Operations,

R & D, and others

Supplier Buyer

Supplier Buyer

After Supplier Integration

Before Supplier Integration

Operations,

R & D, and others

Supplier Environment Buyer Environment

Supplier Outcomes Buyer Outcomes

Suppl ier Environment Buyer Environment

Supplier Outcomes Buyer Outcomes

FIGURE 2A Socio-Technical Perspective for Supplier Integration

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to choices that avoid animosity (i.e., acquiescing to

maintain harmony), at the risk of compromising

technical benefits (Sheth & Parvatiyar, 1995). Ulterior

social motives create behavioral constraints by com-

promising implementation requirements, extending

execution time, and obfuscating technical criteria, thus

disabling the technical unification of processes.

Proposition 3a: During the SI process, the attractive-

ness of social associations between firms increases the

likelihood for behavioral constraints.

While the attractiveness of social associations with a

partner firm may constrain SI, technical designs can

control social associations and keep technical goals

salient. Studies in the dark side of close buyersupplier relationships suggest that an ideal degree of

association is desirable. Anderson and Jap (2005)

show that social associations promote trust, but are

leveraged to ignore product quality irregularities. Gu,

Hung, and Tse (2008) find that close social relations

facilitate channel effectiveness but stunt the flow of

new ideas. Similarly, empirical findings imply a curvi-

linear relationship between behavioral constraints and

social capital, thereby suggesting an optimal level of

relatedness (Villena et al., 2011). Designing the SI ini-

tiative to manage the degree of relatedness and keep

technical goals salient will diminish the behavioral

constraints that stem from social associations between

firms.

SI initiatives that are designed with technical prox-

imities and flows (T3 and T4 in Table 2) that managesocial associations between firms can be useful, such

as assuring spatiotemporal variety between firms

through job rotations or through computer-supported

networking that can control tie strength (Wellman

et al., 1996). Formal codes of conduct based on

external professional standards can counteract the

influence of between-firm informal connections

(Wilkinson, 1992). Requiring specific information to

accompany SI decisions (e.g., formalized costs and

competitive analyses) necessitates the involvement of

departments from both firms with less professional

affiliation (e.g., engineers and accountants). This creates

norms of procedural justice, assures the alignment of SIchoices and goals, and mitigates the utility of social jus-

tifications (Tyler, Dienhart, & Thomas, 2008). Last,

because social associations are attractive for information

access (Seiler, 1967), such attraction can be reduced by

assuring that the SI design contains sufficient technical

information flows to provide individuals with explicit

knowledge needed (Ogden, Petersen, Carter, & Mon-

czka, 2005). Without designing these preventative mea-

sures into the SI initiative before engaging in

collaboration, behavioral constraints to SI will more

likely have to be addressed postintegration.

Proposition 3b: Behavioral constraints from social

associations are reduced by designing the SI initiative

with technical proximities and flows that manage between-

firm relatedness to assure technical goal salience.

Social Experiences between Firms during SI

Changes to the technical flows (T4 in Table 2)between firms can bring about social experiences (S4

in Table 3) that reduce confidence in the SI system

and induce behavioral constraints. Such unassuring

social experiences that SI invokes directly or indirectly

lead to the discomforts observed by Fawcett et al.

(2012). The direct experience from SI is that the source

of input variance changes (Halley & Nollet, 2002): A

supplying firms demand variance source becomes the

buying firms downstream boundary (Walton & Gupta,

1999) and the buying firms supply variance source

becomes the supplying firms upstream boundary (Kull

& Closs, 2008). Because firms have a history of investing

monetarily and cognitively to handle input variation

(Pasmore, 1988), new and unexpected input variances

strain firms and functions (Emery, 1959; Pasmore et al.,

1982). The resulting ambiguity leads to uncertainty,

anxiety, and cognitive dissonance in which negative sen-

timents emerge (Seiler, 1967). These social experiences

erode confidence and heighten distrust of the SI system,

creating more obstacles and resistance to collaboration

(Fawcettet al., 2012; Nyaga, Whipple, & Lynch, 2010).

The indirect effect from SI occurs from the re-

sequencing of work during the SI process. SI increases

coordination and interaction between like-functions

across the buyersupplier dyad (Koufteros, Cheng, &Lai, 2007). Through interaction, a common language

and standardized approaches to collaboration evolve,

increasing opportunities for functional counterparts to

transfer tacit knowledge across firm boundaries

(Nonaka & von Krogh, 2009). While enhanced tacit

knowledge transfer increases the ease with which func-

tional managers can complete tasks, it decreases the

explicit technical knowledge available for system-wide

dissemination (Pan & Scarbrough, 1999). In this way,

SI can enable socialized knowledge to those engaged in

tacit knowledge transfers between firms, but can dis-

able explicit knowledge to those other functions mak-

ing between-firm decisions. The result for these otherfunctions is increased ambiguity and reduced confi-

dence in the SI system (Weick, 1995), leading to the

resistance to change or distrusting of information

observed by Fawcettet al. (2012). As an example, when

engineers between firms tacitly coordinate designs,

buying personnel will be less informed explicitly of

technical specifications, creating coordination difficul-

ties and unassured experiences in the SI system. While

personnel could be instructed to keep other functions

informed, formal incentives typically do not reward

such cross-functional actions (Oliva & Watson, 2011).

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Proposition 4a: During the SI process, unassuring

social experiences between firms increase the likeli-

hood for behavioral constraints.

The above-mentioned behavioral constraints result

from inattention to social experiences that STS theory

would view as inevitable when technical systems arechanged for SI purposes (Pasmore, 1988). Avoiding

such behavioral constraints before an SI initiative

begins, therefore, requires designing technical flows

and centralities that bridge social-to-technical linkages.

For instance, negative affect from novel variance is

largely caused by an underinvestment in educating

employees about the forces involved in SI (Fawcett,

Magnan, & McCarter, 2008). Beginning an SI initiative

with technical training to educate buying and supply

firm personnel on likely future variances can prepare

them. Other ways to build in knowledge flows are

to design technical systems that provide access to

upstream and downstream visibility (Barratt & Oke,

2007) and to require that technical briefings be

communicated. Investing in these technical flows can

prevent negative affective experiences and resistance.

Social processes can be technically supported, such

as by using technical systems to facilitate socialization.

Firms continue to struggle to balance their IT systems

and supply chain strategies (Thun, 2010). Evidence

shows that, through the use of electronic collabora-

tion tools, a buyersupplier dyad can improve collab-

oration and knowledge (Costa & Tavares, 2012;

Fayard, Lee, Leitch, & Kettinger, 2012). Automating

the tacit-to-explicit process can relieve the burden ofemployees having to do so. Using social networking

technology, between-firm blogging, and even text mes-

saging are approaches to make social experiences

explicit (Raghuram, 1996). In many ways, if the tech-

nical system remains connected to the social system,

then social experiences will not be left unattended

and the meaning of SI will not be lost.

Proposition 4b: Behavioral constraints are reduced

by designing the SI initiative with technical flows and

centralities that give attention to social experiences.

Environmental Influences during SIWhile firms social and technical features interact

during SI, we propose environmental contingencies to

influence such interaction. Regarding environmental

equivocality (E1 in Table 4), the effects of turbulence,

complexity, and connectivity will motivate technical

system changes that increase the likelihood for behav-

ioral constraints. Prior to SI, the STS of the buying

and supply firms will have environments comprised

of unique sets of resources, demands, and stakehold-

ers (Pasmore, 1988). In the course of SI, however,

each firms connectivity becomes relevant to the other

as joint approaches to coordinated decision making

displace unilateral actions. Inherently, then, SI leads

to more complex decision frames as the aggregated

resource constraints and demands of partner firms

impose a greater number of decision variables along

with an increased number of known, unknown, andconflicting inter-relationships (Carayon, 2006). Draw-

ing from STS theory (Pasmore, 1988), the equivocality

inherent in an environment characterized by high lev-

els of dyadic connectivity suggests that external issues

will have greater influence during SI. High equivocal-

ity constrains the number and type of technical

systems that (1) are feasible within both the buyers

and suppliers environment and (2) accomplish the

intended goals of the integration effort. Accordingly,

equivocality increases the likelihood for and the

degree of technical system adaptations that, in accor-

dance with P1a, P2a, P3a, and P4a, increase the likeli-

hood of behavioral constraints to SI.

Recent integration efforts between Apple Inc. and Fox-

conn provide insights into environmental equivocality,

the need for technical adaptations, and behavioral con-

straints. Foxconn is a large electronics manufacturer

with high connectivity to Chinas government and

labor markets (Weir, 2012). Foxconn has achieved pro-

duction efficiencies through human resource tech-

niques that are viewed as intolerable to some Western

societies (Duhigg & Greenhouse, 2012). In contrast,

Apple is highly connected to various stakeholders who

demand fair treatment of workers (Weir, 2012). Each

firms ties to stakeholders with disparate aims addedsubstantial complexity to their SI efforts and led to

behavioral constraints. For example, in response to

environmental demands for increased corporate social

responsibility, Apple sought to integrate its strategy

with Foxconn by having Foxconn reduce worker hours,

increase worker pay, and improve worker living condi-

tions (i.e., change the technical requisites, T2 in

Table 2). However, Foxconn resisted change and imple-

mented both superfluous and deceptive solutions to

pacify concerns, installing managerial appointees to

represent worker groups and unions, and instructing

employees to mislead auditors so that labor violations

might go undetected (Duhigg & Greenhouse, 2012).

Proposition 5a: During the SI process, environmen-

tal equivocality increases the likelihood for STS-based

behavioral constraints.

Whereas equivocality limits the number of technical

solutions that are mutually acceptable to partner firms

during SI, we propose that environmental opportunity

resource alternatives and mutability has the

opposite effect and reduces the likelihood for behav-

ioral constraints. First, resource alternatives represent

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the number and type of resources from which the

buying and supplying firms may select during SI. An

environment with a high variety of resource alterna-

tives allows discretion in technical system design by

facilitating a rich set of possible technical solutions to

accommodate SI. The inherent degrees of freedom in

technical system design increase the likelihood that thefirms can (1) design a technical system that satisfies

environmental demands, (2) preserve the primary fea-

tures of their existing technical and social systems, and

(3) meet the goals of the SI effort. For example, in the

case of collaborative planning, forecasting, and replen-

ishment, a variety of environmental resources may be

available like translation tools and web intermediaries

that allow unification of information flows despite hav-

ing different information systems (Pramatari 2007).

This allows partner firms to continue using existing

internal automation tools to synchronize technical

flows while preserving technical centralities and, in

turn, reducing the likelihood of behavioral constraints.

Second, mutability also reduces the likelihood of

behavioral constraints to SI, yet it does so by drawing

on firms abilities to change the environment rather

than react to it (Pasmore, 1988). That is, in facing

dysfunctional social reactions to technical changes,

firms can influence a mutable environment in a way

conducive to SI. For instance, the dyads customers

may be flexible in requirements or the dyads suppli-

ers may be flexible in deliveries (Lao, Hong, & Rao,

2010; Zhang & Tseng, 2009). By enabling the creation

of a more favorable environment, mutability renders

external demands and resource constraints less rele-vant (Pasmore, 1988). Hence, a highly mutable envi-

ronment increases the likelihood that the buyer and

supplier can enact mutually acceptable technical

features that meet SI objectives while preserving the

primary features of both parties STS. In so doing,

firms may avoid behavioral constraints to SI.

Proposition 5b: During the SI process, environmen-

tal opportunity and mutability decrease the likelihood

for STS-based behavioral constraints.

IMPLICATIONS AND FUTURE RESEARCHIn this paper, we demonstrate how STS theory pro-

vides a novel perspective to aid theoretical and practi-

cal insights to SI. Research has generally been

asymmetric in its approach to the social and technical

influences within SI, focusing on either one or the

other, but not both. This is likely because theories

such as transaction cost economics theory generally

ignore social factors (Ireland & Webb, 2007), while

theories such as social capital theory generally ignore

technical factors (Monczka, Petersen, Handfield, & Ra-

gatz, 1998). Although some SI literature compensates

for asymmetry by combining theories (Hofer et al.,

2009; Ireland & Webb, 2007; Krause, Handfield, &

Tyler, 2007; Lai, 2009), the single framework of STS

theory enables a self-contained systems perspective

that can move SI literature forward.

Our propositions demonstrate the usefulness of STStheory to SI literature in three ways. First, we extend

Fawcett et al. (2012) to explain why behavioral con-

straints result from specific social processes in reaction

to an SI initiative. We point to the importance of

social positions and values within firms, as well as

social associations and experiences between firms. In

suggesting these root causes, STS theory explains why

inhibitors emerge from a technical collaboration

effort. Second, in being attentive to inevitable social

responses to an SI initiative, we suggest technical

designs that can aid the SI process. Technical elements

of the SI design that is, the centralities, requisites,

proximities, and flows each have a role to play.

STS theory shows that the approach taken to SI

should be carefully considered prior to the initiative.

Third, environmental contingencies are proposed that

prepare managers for the particular challenges they

face in the SI process. SI literature must account for

factors beyond the buyersupplier dyad, and STS

theory aids in that endeavor. In sum, the macro view

presented in our propositions opens SI research to

STS theory for explaining phenomena involving the

social, technical, and environmental processes ever

present in supply systems.

Theoretical ImplicationsThis paper contributes to theory in multiple ways.

In describing why behavioral constraints emerge from

SI, we demonstrate how social attributes that are inti-

mately linked to supply systems can inhibit SI. For

instance as Proposition 1a implies, functions resist SI

not because the initiative is new, but because their

social position is threatened. Also as Proposition 2b

suggests, conflicts emerge not because functions can-

not get along, but because the SI process can change

underlying values. Moreover, our propositions have

theoretical value in suggesting a myriad of behaviors

constraining SI beyond those observed by Fawcettet al. (2012). Based on STS theory, we suggest such

behaviors as co-opting the routing of information

(P1a), diverging abilities to communicate (P2a), bas-

ing decisions on social harmony (P3a), and failing to

keep knowledge explicit (P4a). By highlighting social

processes as root causes and by suggesting unexpected

symptoms for constraints to SI, our research provides

a novel perspective useful for SI.

Our research provides a perspective not common to

supply chain research: Technical systems change social

systems. Typically, literature argues that certain social

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attributes, like having the right culture, must be present

before implementing technical systems (McIvor &

McHugh, 2000). By contrast, the STS perspective of our

propositions adds that technical systems are antecedent

to social attributes. Because social attributes and

processes are a root of behavioral constraints, SI

research requires a deeper understanding of the specifictechnical elements that induce particular social

processes. Each of our b propositions provides

insights into these inter-relationships and gives sugges-

tions for creating SI designs that account for social

processes. We note that while we propose how social

processes can be negative, social change may actually

be positive. For instance, linking suppliers to high qual-

ity buyer processes may improve attention to detail in

the supplying firm (Naveh & Erez, 2004). Recognizing

that social systems change as a result of SI, the STS per-

spective opens SI research to explore positive and nega-

tive social implications of technical change.

Important insights are revealed in Proposition 5:

Behavioral constraints to SI are influenced by the rele-

vant environment. This is the open-system perspective

upon, which STS is based (Pasmore et al., 1982). A

partner firms STS should be seen as a system adapted

to survive in its unique environment. When firms seek

to synchronize processes, any modifications to each

others STS could disrupt the adapted balance with

the environment. Therefore, how dramatic the techni-

cal change will be or how free firms are in designing

their SI system deeply depend on both firms environ-

mental characteristics. We see this in reports of buyers

becoming familiar with the suppliers suppliers (Choi& Linton, 2011) or using predictive analysis of sup-

plier bankruptcy because of environmental troubles

(Harrington & OConnor, 2009). Yet, more theoretical

guidance is needed. Our Proposition 5 suggests to

researchers and managers the environmental proper-

ties to assess and for which to prepare. In a global

competitive environment increasingly linked through

information and social networks, theories like STS will

be increasingly useful.

Our advancement of STS theory contributes to con-

temporary discourse of theories that incorporate

aspects of social capital and socialization. For

instance, we offer a caution in that once a functionlike PSM attains high social capital (Bernardes, 2010),

it may constrain initiatives that change its critical

social position. Additionally, in contrast to literature

that conceptualizes socialization in terms of shared

understanding (Petersen et al., 2008), our theoretical

development advances a much broader view of social-

ization. Drawing from core STS principles, we posit

that social positions, values, associations, and experi-

ences represent important attributes of social processes

that affect shared understanding. Further, our concep-

tualization of STS challenges the sign and directional-

ity of causal relationships between socialization and

integration. Whereas Petersen et al. (2008) assert that

the behavioral norms established through socializa-

tion facilitate higher levels of SI, our broader concep-

tualization of social systems provides theoretical

rationale that supports a contrary view in which

(1) SI causes changes to social processes and (2) thesesocial processes may hinder SI.

Last, our assertions that social and technical attri-

butes may inhibit SI efforts lends to a growing stream

of research that extols the dark side of closer buyer

supplier relationships. This line of inquiry suggests

that close supplier relationships do not always

achieve their intended aims (Dyer & Hatch, 2006),

nor are they achieved without substantive coordina-

tion cost or supply risk (Goffin, Lemke, & Szwejczew-

ski, 2006). Such concerns refute the implicit notion

that tighter buyersupplier linkages are uncondition-

ally advantageous. While such literature has high-

lighted that close social ties may also enable

opportunism (Anderson & Jap, 2005) or inhibit tech-

nical innovations (Choi & Linton, 2011), little theo-

retical grounding is given as to how to optimize the

degree of social relatedness. Drawing from STS the-

ory, our propositions advance a rationale as to why a

dark side emerges from the inherent, a priori technical

designs of the SI initiative, and suggest technical

designs to manage the level of relatedness between

firms. In doing this, we guide evidence-based research

into how to address the dark side of SI that literature

has revealed.

Managerial ImplicationsOur propositions extend literature to provide a

novel SI perspective for managers by showing how

careful consideration is needed prior to engaging in a

collaborative SI initiative. While Fawcett et al. (2012)

suggest strong managerial commitment, changed

mindsets, and thorough communication, our perspec-

tive complements this by suggesting SI designs prior

to collaboration can prevent inhibiting forces from

needing to be overcome. Our macro view shows that

firms should assess where their STS differs from their

partner firms before integrating to improve upfront SI

designs that avoid problems. The practice of sendingengineers to supplier locations long before recom-

mending technical supplier changes (Liker & Choi,

2004) can provide opportunities to learn partner firm

STS and environmental features. Our propositions

provide the beginnings of a roadmap for such vis-

its. Managers can assess how changes to technical

centralities and requisites will affect within-firm social

positions and associations, and how technical proxim-

ities and flow will affect between-firm social associa-

tions and experiences. By adopting a macro view of

SI, in which integration is perceived as a joining of

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two distinct STSs, firms are better prepared to deal

with the challenges of SI initiatives.

The SI design strategies suggested here have a domi-

nant theme: Assure that technical designs attend to

inevitable social processes. Because the STS perspective

assumes that social and technical processes tightly

couple, social change will follow technical change insome way; the concern is how. Our propositions

provide the insight that if social change is inevitable

then design should incorporate that knowledge. For

instance, as Proposition 3b suggests, because between-

firm social associations are expected and behavioral

constraints are inevitable, designs should be made to

manage the degree of relatedness. Literature is clear

that people at work have needs and behaviors beyond

simplistic models of rationality (Pasmore, 1988;

Weick, 1995). Although inter-organizational and sup-

ply chain behavior research is still nascent, it is clear

that supply chain practices affect and are affected by

behavior. In our propositions, we advance managerial

concepts and guidelines that enable direct acknowl-

edgement and accommodation of socially induced

behavior to ultimately achieve SI goals.

We advise managers to consider their partners envi-

ronment while planning SI initiatives. Whereas extant

literature suggests the influential role of ones own

environment in driving coordination behaviors (Ellis

et al., 2011), managers receive little direction as to the

constraining and enabling roles of partners environ-

ments. Through Propositions 5a and 5b, we assert

that equivocality and opportunity have opposing

effects on the number and variety of technical designsthat are feasible SI solutions for both the buyer and

supplier. Our theory, then, suggests to managers that

equivocal environments likely require more significant

investments in social systems to avoid behavioral con-

straints to SI. In contrast, partnering with a firm that

can marshal resources from external systems or

actively change its environment is likely to diminish

the need for such investments.

We point executives to the importance of social

competence and STS learning. Regarding social com-

petence, we see that managing perceptions of social

position advances SI efforts. Threats associated with

perceived loss of social position represent a formativerationale motivating employees to withdraw their SI

support. Similarly, the emergence of between-firm

social experiences, and the behavioral constraints that

ensue, point to SI phenomena that cannot be ignored.

Building social competence where managers are

astutely aware of social conditions and future social

changes is shown in our propositions to be of signifi-

cant value. Walmarts supplier sustainability initiative

provides a useful example (Plambeck & Denend,

2008) where an SI practice (i.e., sustainability) was

successfully implemented because Walmart accounted

for the social processes involved in persuading suppli-

ers to implement the practice. Regarding STS learning,

socio-technical principles advocate the importance of

knowledge acquisition and assimilation for systematic

adaptations (Pasmore et al., 1982). We demonstrate

that the degree of socio-technical interrelatedness is

quite high in the buyersupplier dyad. Accordingly,our theory suggests that resources and strategic

support are insufficient to assure SI goals (Bernardes,

2010). Rather, a learning orientation is required that

advocates exploratory SI practices that cultivate knowl-

edge of the dyads STS landscape. Only through exper-

imentation and continual learning can the particular

STS processes in an SI initiative be known. While our

presentation provides the general relationships to

expect, SI advantages will be gained if managers learn

and discover the specific STS challenges they face.

Last, are the traditional boundary-spanning func-

tions like PSM truly prepared for the future as SI

becomes common? PSM and sales/marketing are

likely aware that SI will change their positions. In fact,

literature suggests that a strong PSM social position is

needed for firms to consider SI as a strategy (Paulraj

& Chen, 2007). The STS perspective also suggests that

as SI is implemented, PSMs social position will be

threatened. Yet the macro view provided by the STS

perspective suggests broader, facilitating purposes for

boundary-spanning functions. The difficulty in unify-

ing STSs is evident (Fawcett et al., 2008) and, thus,

shows that new facilitating roles are needed. The STS

perspective prepares an SI initiative a priori for these

eventualities. Our propositions point to a number ofskills typically not considered supply chain related.

For example, a role for cross-functional facilitators

between firms will be needed. This means an increas-

ingly nonoperational role within the supply process,

but rather a role of monitoring and consulting as to

its ebbs and flows. Are the PSM and sales/marketing

functions appropriately prepared for these roles? Addi-

tionally, are the traditional boundary-spanning func-

tions able to monitor the economic landscape and

competitive landscape of their partner firms? Are these

functions ready to acquire the financial, engineering,

and operational skill sets to support explorative

activities, such as strategic cost analysis, multiechelonSCM, and CPFR, that facilitate STS adaptations?

Clearly, if firms are destined to form higher levels of

connectivity then many of these activities will be

required, but are firms prepared to do so? These ques-

tions need to be considered carefully to derive full

benefits from SI.

Future ResearchOur STS-SI model can be empirically examined

through various means, such as industry surveys or

case analyses. For instance, survey data of cross-indus-

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try SI instances can test if STS reasons exist for why

buying and supplying firms experience behavioral

constraints. Most likely this would entail multilevel

analysis because SI requires multiple functions nested

within a buyersupplier dyad, which are also nested

with specific industrial environments. Scale develop-

ment reflecting the key STS concepts is guided by ourTables 24. Measures could be developed to assess the

degree of difference experienced before, during, and

after an SI initiative, while seeking associations with

the various behavioral constraints and SI technical

designs suggested. Alternatively, case analyses guided

by STS theory can investigate how specific STS concepts

lead to or mitigate particular behavioral constraints,

especially interesting would be the process of social

value change and divergence brought on by discontin-

uous technical changes. Both of these empirical

approaches may provide new insights into how social

processes emerge during the SI process and empiri-

cally validate the utility of STS theory applied to the

inter-organizational context.

Researchers can also employ alternate methods to

examine how phenomena like social position threats

affect SI efforts. In particular, researchers could design

behavioral experiments using supply chain simula-

tions (Eckerd & Bendoly, 2011) where study partici-

pants are assigned the various roles. Initially,

participants would perform typical supply chain

functions managing material replenishments,

communicating requirements, coordinating supplier

involvement and different treatments of social

position would be given within the simulation. Then,an SI initiative would begin where the participant is

allowed to choose different degrees of involvement in

the supply process. Moreover, researchers could exper-

iment with different approaches toward SI, modifying

the Table 4 characteristics of the environment. Finally,

before-and-after questionnaires would measure the

presence of various STS components, the perceptions

of participants, and behavioral constraints observed.

Using experimental methodologies, STS can be a

fertile perspective for such behavioral work.

As organizational boundaries blur, theories used to

describe intra-organizational processes will become

more applicable in future research. While our paperextends STS theory to the inter-organizational context,

other SCM research has similarly carried out so with

theories such as dynamic capabilities (Fawcett, Wallin,

Allred, Fawcett, & Magnan, 2010) and resource-based

perspectives (Pagell, Wu, & Wasserman, 2010). Apply-

ing new theories to SI expands, but also complicates

what researchers and managers need to consider.

Eventually, just as STS theory has developed a coher-

ent set of normative STS principles, future research

should similarly update a set of SI principles a

repository of evidence-based practices. In addition,

questions will need to be answered like how costly is

social change to a firm? When should technical

designs be compromised for social benefit? Seiler

(1967) emphasizes that true system understanding

requires investigating the trade-offs within an STS.

Although incorporating social goals into technicaldesigns makes SI more challenging, STS theory pro-

vides the detailed, systemic view that future SI

researchers can use to describe and improve supply

chain processes.

CONCLUSIONWhile our theory offers novel insights into SI phe-

nomena, there are several limitations to our study. As

with any conceptual work, data will be needed to test

our propositions. Our suggestions for future research

help move research in that direction. We also note

that our theory is limited to the buyersupplier dyad

and does not address other STS processes that induce

constraints across three or more firms. Our theory

focuses on issues germane to the SI process, not with

issues long after SI has occurred. This is another limi-

tation because quite often disruptions occur in stable,

integrated supply systems with important effects on

competitive performance. Last, we note that STS the-

ory is inherently limited to influences across social,

technical, and environmental systems, not within

these systems themselves. Such a limitation misses

important within-system factors that just as likely can

constrain SI.Despite these limitations, our research provides a

robust platform for the advancement of STS theory

within the context of SI. In extending Fawcett et al.

(2012) and echoing behavioral supply chain research

(Siemsen, 2011), we assert that technical systems do

not exist in isolation; rather, technical systems are

closely coupled with social systems that are jointly

embedded in the environment. Hence, SI problems

require researchers and managers to consider the more

systemic causes for the variations observed. This paper

provides a means for such consideration by extending

STS theory from an intra- to an inter-organizational

context. Through presenting STS theorys pertinenttenets as related to SI, we provide a framework

explaining and preventing behavioral constraints to

SI. Our STS-based propositions will help managers

prepare and design more effective SI initiatives. When

Emery and Trist developed STS fifty years ago, busi-

nesses were significantly less interconnected: Earlier

work examined the social and technical systems

within a given organization. As organizational bound-

aries blur, STS theory becomes relevant when examin-

ing systems spanning multiple firms. Research has

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shown the usefulness of STS theory within organiza-

tions; future research will show how supply chains

can benefit from STS theory.

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