30competitive advantage with logistics information technology

Toward creating competitiveadvantage with logisticsinformation technologyBenjamin T. Hazen and Terry Anthony Byrd

Aviation and Supply Chain Management,Auburn University, Auburn, Alabama, USA

Abstract

Purpose Successfully implementing and exploiting the right information technologies is critical tomaintaining competitiveness in todays supply chain. However, simply adopting off-the-shelftechnologies may not necessarily induce this competitiveness unless the organization combines thesetechnologies with additional complimentary resources. This study draws on the logistics innovationliterature, resource-advantage theory, and the resource-based view of the firm with the purpose ofinvestigating performance outcomes of logistics information technology (LIT) adoption and theproposed moderating effect of a complimentary resource. The paper posits that combining LIT withpositive buyer-supplier relationships may set the stage for organizations to achieve competitiveadvantage.

Design/methodology/approach A meta-analysis of 48 studies that report outcomes of EDI orRFID adoption was performed. Regression was used to investigate the moderating effect of thebuyer-supplier relationship on the relationship between LIT adoption and performance outcomes.

Findings The findings suggest that adoption of LIT promotes enhanced levels of effectiveness,efficiency, and resiliency for the adopting firm and that the quality of the buyer-supplier relationshipmoderates the degree of efficiency and resiliency realized via adoption.

Research limitations/implications The results of this study suggest that adoption of a logisticsinnovation by itself may not necessarily produce a sustained competitive advantage. Instead, whencombined with complimentary firm resources, the innovation may yield a sustained competitiveadvantage for the adopting firm.

Originality/value Logistics innovation needs greater theoretical development in the literature.This research extends a foundational logistics innovation model by incorporating relevant theory topropose and test an additional dimension of the model.

Keywords Information technology, Innovation, Resource-based view, Radio frequency identification,Electronic data interchange, Meta-analysis, Competitive advantage

Paper type Research paper

1. IntroductionInformation technology (IT) has emerged as one of the most popular categories oftechnological innovation being implemented in the supply chain (Russell and Hoag,2004). Indeed, IT is purported to be one of the most managerially-relevant researchtopics in extant supply chain management (SCM) literature (Thomas et al., 2011).

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0960-0035.htm

The authors would like to thank Robert Overstreet and Fred Weigel for their assistancethroughout this research effort. An earlier version of this paper was presented at the Pacific AsiaConference for Information Systems in Brisbane, Australia. The authors would like to thank thetrack chairs, anonymous reviewers, and session attendees for their valuable feedback, whichhelped to strengthen this paper.

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International Journal of PhysicalDistribution & Logistics ManagementVol. 42 No. 1, 2012pp. 8-35q Emerald Group Publishing Limited0960-0035DOI 10.1108/09600031211202454

Although some firms have reported positive results from adoption of IT,implementation can be risky and expensive, especially if the ramifications andoutcomes of such innovations are not fully understood by the adopting firm (Heinrichand Simchi-Levi, 2005). Considering the Council of Supply Chain Managementsdefinition of logistics and Rogers (2003) definition of innovation, we define a logisticsinformation technology (LIT) innovation as an IT application that is perceived as newto the organization of adoption that is used for planning, implementing, and/orcontrolling procedures for the transportation and storage of goods and services fromthe point of origin to the point of consumption. Organizations looking to adopt LIT areoften interested in understanding how adopting such technologies will aid in achievingpositive operational and strategic benefits. However, inconsistent findings in theliterature suggest that additional phenomena may moderate the relationship betweenLIT adoption and positive performance outcomes (Narayanan et al., 2009).

The resource-based view (RBV) of the firm suggests that capital resources may beutilized to create competitive advantage (Barney, 1991). Although off-the-shelf ITusually does not directly induce competitive advantage, these technologies have beenshown to provide capabilities that may lead to enhanced measures of operationalperformance (Kros et al., 2011; Wade and Hulland, 2004). This operational perspective isbased on the argument that the first-order effects of IT innovation adoption occur at thefunctional/operational level via enhancing various aspects of efficiency, effectiveness,and resiliency (Barua et al., 1995; Grant, 1991). However, when combined with additionalorganizational resources, adoption of off-the-shelf information technologies mayprovide the foundation for a firm to realize sustained competitive advantage (Mata et al.,1995; Nevo and Wade, 2010; Ray et al., 2005). Thus, the RBV perspective provides anadequate context in which to examine the value of LIT adoption.

As with any innovation, firms generally adopt LIT for the purpose of realizingimproved measures of performance. However, the logistics arena may present a uniqueset of challenges because of the inherent inter- and intra-organizationalinterdependencies required for the effective transportation and storage of goods andservices. Thus, adoption of LIT may not automatically translate into realizedimprovements in performance for the adopting firm. For example, a study of electronicdata interchange (EDI) use in large German and US firms revealed a variety ofconflicting findings regarding the benefits of adoption (Reekers, 1994). Although EDIwas demonstrated to improve trading partner communication, data accuracy, andcustomer service, other anticipated benefits such as reductions in inventory andreductions in paperwork were not demonstrated. One explanation for theseinconsistencies may be found in lack of inter-organizational integration and/or forcedadoption by firms with more powerful market position (Reekers, 1994). This assertionis supported by the work of Riggins and Mukhopadhyay (1994), whose researchsuggests that firms that initiate inter-organizational systems should take into accountthe costs and benefits of the system to their trading partners if both firms are to reapmaximum benefits of system implementation. These findings may be explained bysocial exchange theory, which views the exchange relationship between specific actorsas being contingent upon rewarding reactions from others (Blau, 1964). When one firm iscoerced into adopting a collaborative technology that it believes will only benefit theother organization, then it may not be motivated toward successful implementation andusage. Conversely, firms who have cultivated a positive buyer-supplier relationship may

Logisticsinformationtechnology

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view the adoption of a given LIT innovation as mutually beneficial and thus put forth theeffort and resources that are necessary to reap positive rewards.

The first purpose of this study is to integrate existing (and often contradictory)research to draw conclusions regarding the nature of the relationship between LITinnovation adoption and performance outcomes. Accordingly, this study asks:

RQ1. Do LIT innovations induce positive performance outcomes for the adoptingfirm?

The second purpose of this study is to investigate whether the presence of acomplimentary firm resource, specifically a positive trading relationship, may enhance theperformance outcomes realized by LIT adoption. As such, our second research question is:

RQ2. How does the buyer-supplier relationship affect the relationship between LITadoption and performance outcomes?

To further develop these questions and adequately articulate the outcome of ourinvestigation, the remainder of this manuscript is organized as follows. First, we reviewrelevant background literature and develop hypotheses. The review begins with adiscussion of theories pertinent to logistics innovation diffusion, to include diffusion ofinnovation theory, resource-advantage (R-A) theory, and RBV. Next, the artifacts used tocharacterize LIT, namely EDI and radio frequency identification (RFID) are introduced.We then briefly discuss Section 2.3 as cited in the literature, which leads to developmentof our first set of hypotheses. Our conversation then turns to the proposed moderatingrole of buyer-supplier relationships, which leads to our second set of hypotheses.Because the purpose of this study is to not only integrate results of existing studies(which are often conflicting) to draw meaningful conclusions, but also to test formoderation, a meta-analysis method was deemed to be the most appropriate method toemploy (Glass, 1976; Hunter and Schmidt, 2004). We discuss the meta-analytic methodsused in this study to illustrate how extant empirical literature is utilized for analysis. Theresults of the research are then presented. Finally, we discuss the findings, to includepractical and theoretical implications, and end with limitations and recommendationsfor future research.

2. Background literature and hypotheses2.1 Logistics innovationRogers (2003) offers a generalized model of the innovation diffusion process, which hasbeen used extensively as the basis of innovation research in the SCM field. Skipper et al.(2009) examine the relationship between Rogers antecedents of innovation adoption(relative advantage, compatibility, ease of use, trialability, and observability) and afirms adoption of supply chain contingency planning processes, extending Rogerswork by proposing two additional antecedents (top management support andcentralization) from extant management information systems (MIS) literature (Mooreand Benbasat, 1991; Tornatzky and Klein, 1982). In addition, the IT implementationmodel (Kwon and Zmud, 1987; Zmud and Apple, 1992) has been used by a variety ofauthors to investigate IT diffusion within supply chain settings (Cooper and Zmud,1990; Premkumar et al., 1994). As demonstrated above, many innovation diffusionstudies in the SCM context have focused on IT artifacts (Chen J.V. et al., 2009;Germain et al., 1994; Patterson et al., 2003, 2004; Williams, 1994).

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Although research in the MIS and SCM fields has expanded upon diffusion ofinnovation theory to develop more discipline-specific conceptualizations of innovationdiffusion, the literature was previously scarce in offering a unified model of logisticsinnovation. Grawes (2009) recent review of logistics innovation research suggests sucha model of logistics innovation and provides a basis for further research. As Grawes(2009) review indicates, logistics innovation research has investigated a wide variety ofantecedents and outcomes. This model is shown in Figure 1.

Grawe (2009) proposes that diffusion of logistics innovation is positively related to afirms competitive advantage. This proposition is rooted in R-A theory and based on acritical survey of logistics innovation literature. As described by Hunt and Morgan(1996), the R-A theory of competition posits that organizations seek competitiveadvantage in the marketplace via obtaining a comparative advantage in resources,which then leads to superior financial performance. However, this proposition andaccompanying model do not clearly address how a firm may create competitiveadvantage from the adoption of logistics innovation. As suggested by Barney (1991) andthe RBV, a firm may only realize competitive advantage when it implements a valuecreating strategy that is not being implemented by current or potential competitors.Although adoption of a homogeneous and perfectly mobile resource (e.g. off-the-shelflogistics innovations such as EDI, RFID, containerization, etc.) may induce a short-termcompetitive advantage, such adoption likely will not foster sustained competitiveadvantage unless paired with heterogeneous firm resources or characteristics.

This current research seeks to extend current SCM innovation diffusion literature,and specifically the model presented by Grawe (2009), by investigating onecharacteristic that may aid in fostering competitive advantage for a firm viathe adoption of logistics innovation. By examining the moderating effect of thebuyer-supplier relationship on the relationship between adoption of LIT andperformance outcomes, this study proposes the introduction of a key construct thatmay strengthen the existing logistics innovation model. In doing so, we propose anadditional dimension to Grawes (2009) model that may bridge the gap between logisticsinnovation adoption and competitive advantage. Considering both R-A theory and RBV,we suggest that complementary firm resources, when combined with logisticsinnovation adoption, may allow a firm to realize competitive advantage over other firmswho adopt the same logistics innovation yet do not possess additional complementary

Figure 1.Logistics innovation

antecedents and outcomesSource: Grawe (2009, p. 364)

Environmental factorsOrganization of labor ()CompetitionCapital scarcity

Organizational factorsKnowledgeTechnologyRelationship network factorsFinancial resourcesManagement resources

Logistics innovation

Logistics innovation diffusion

Competitive advantage


11

firm resources. In this study, we examine the effect of buyer-supplier relationships as apotential complementary firm resource. If buyer-supplier relationships are found toinduce greater levels of effectiveness, efficiency, and/or resiliency, then it may provideevidence to warrant additional empirical investigation of the moderating effect ofadditional complimentary resources. This finding may suggest a slight modification toGrawes (2009) model to account for the moderating effect of complimentary firmresources.

The preceding discussion reveals how our study fits into the current body of SCMinnovation literature. Next, our discussion turns to the specific LIT innovations thatare investigated in this study.

2.2 LIT artifactsOne purpose of this research is to investigate the effect of LIT adoption on expectedperformance outcomes. To begin, we sought an unbiased method for choosing the mostappropriate LIT artifacts for the focus of investigation. Ideally, our study wouldinvestigate the entire population of IT that meet our definition of LIT. However,as with any research endeavor, we were required to adopt a valid sampling technique inorder to study a representative sample of our target population. Purposive sampling is anon-random sampling technique in which the researcher uses judgment in selectingcases for a specific purpose (Neuman, 2006). This sampling technique is appropriate toselect unique cases that may be especially informative (Neuman, 2006). Berelson (1952)suggests that revealing the focus of attention is one of the primary uses of contentanalysis. As such, we adapted procedures for problem-driven content analysissuggested by Krippendorff (2004) to determine which LIT artifacts may be mostappropriate and especially informative to study. In sum, this content analysis served asour purposive sampling technique because we posit that the IT most common in theSCM literature will likely offer the best insight into the nature of the population of LIT.

Krippendorffs (2004, p. 83) first component of content analysis involves unitizing,which is defined as the systematic distinguishing of segments of text images,voices, and other observables that are of interest to an analysis. In this study, wesought to determine which LIT are often addressed as the primary artifact of interest inthe extant SCM literature. Accordingly, the unit of analysis is an article in a SCMjournal that investigated a specific LIT.

To locate articles that meet the above criteria, the top 20 SCM journals for researchusefulness as identified by Menachof et al. (2009, p. 151) were considered. These journalsare shown in Table I in alphabetical order. Of note, since the purpose of the contentanalysis is to determine the most relevant IT artifacts in SCM literature,interdisciplinary journal titles such as Harvard Business Review and ManagementSciencewere not included. As such, 14 of the top 20 journals identified by Menachof et al.(2009) were utilized for content analysis. The selected journals were searched viaABI/INFORM Complete, Business Source Premier, and ScienceDirect databases.A keyword search for information technology or information system was conductedfor each journal and the number of results was recorded. Titles and abstracts were thenreviewed to determine if a specific LIT was addressed as the primary focus of the article.The nomenclature of the LIT artifact was then noted and the total number of articles perjournal that addressed LIT as a primary focus was recorded. Articles addressing thegeneral use of IT or loosely defined terms such as EBusiness were not counted.

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At this point in the content analysis, we had compiled a listing of 28 unique ITinnovation artifacts in the logistics literature. Many of these technologies did notreceive much attention. For example, IT such as transportation routing systems andknowledge management systems only emerged twice. However, this allowed the topLIT to be easily identified. EDI and RFID emerged as the two LIT that are addressedmost often in the SCM literature, accounting for 32 percent of all articles in which IT isthe primary focus. Because they conform to our strict definition of LIT and theytogether comprise nearly one-third of the SCM literature which addresses IT, we choseto adopt EDI and RFID to represent LIT in our study. The results of this contentanalysis are illustrated in Table I.

RFID is a type of automated data collection system that uses radio waves to identifyobjects (Angeles, 2005). Interest in RFID applications in the supply chain has generateda rapidly growing body of knowledge in recent years. Some posit that use mandatesfrom industry leaders such as Wal-Mart has quickly brought RFID to the attention ofacademicians and practitioners alike (Visich et al., 2007). This has motivated manyauthors to discuss cases of RFID implementation success and suggest anecdotal orperceived outcomes of RFID adoption. Academicians are currently working to developthe body of empirical literature investigating actual benefits derived from RFID use(Visich et al., 2009).

EDI is a technology used to exchange information and data across organizations(Germain and Droge, 1995) and may be defined as, business to business transfer ofrepetitive business processes involving direct routing of information from one computerto another without human interference, according to predefined information formats andrules (Holland et al., 1992, p. 539). Unlike RFID, EDI research has spanned the last two

JournalTerm found in abstract/

citationIT

innovationsa EDI RFID

European Journal of Operational Research 169 25 1 1International Journal of Logistics Management 16 1 0 0International Journal of Logistics: Research andApplications 17 9 1 4International Journal of Operations andProduction Management 95 14 1 0International Journal of Physical Distributionand Logistics Management 109 18 3 1Journal of Business Logistics 45 14 3 1Journal of Operations Management 43 16 1 0Journal of Purchasing and Supply Management 12 4 3 0Journal of Supply Chain Management: A GlobalReview 29 4 2 0Operations Research 32 8 0 0Supply Chain Management Review 39 1 0 0Supply Chain Management: An InternationalJournal 41 7 2 2Transportation Journal 21 4 2 1Transportation Research: Part E 11 4 0 1Total 668 125 19 11

Note: aThe specific IT innovation was the primary focus of the article

Table I.Results of content

analysis


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decades and is widely viewed as a relatively mature technology (Narayanan et al., 2009).However, although the literature is insightful in examining many phenomenasurrounding EDI (e.g. antecedents to adoption, implementation techniques, etc.), thequantitative academic literature investigating actual operational benefits is notwell assimilated and sometimes inconclusive (Ahmad and Schroeder, 2001;Narayanan et al., 2009).

In this study, we combine EDI and RFID into a single unit of analysis that we labelLIT. No one sample is ever perfectly reflective of the population. However, becausethese technologies are widely used in logistics and meet our definition of LIT, webelieve that EDI and RFID may be representative of most LIT artifacts. We chose tostudy two LITs in lieu of just one for two specific reasons. First, research into theperformance outcomes of just one LIT may limit the genralizability of conclusionsdrawn from this study. Although we are still careful to generalize our results to all LIT,the study of just one technology would limit our ability to generalize even further.Second, the study of more than one LIT will provide more data for analysis. Wepropose that combining these LITs into one unit of analysis may be appropriateprovided the performance outcomes of each are shown to be statistically homogenous(which will be demonstrated later in this manuscript). The expected benefits of theseLITs are discussed in the following section.

2.3 Expected performance outcomes of LIT adoptionA variety of expected performance outcomes of LIT adoption are touted in theliterature. As such, many EDI and RFID diffusion studies even suggest thatanticipation of benefits derived from the implementation of LIT is a key antecedent toadoption (Crum et al., 1996; Premkumar, 2003). Benefits investigated in the literaturerange from reduced order cycle times and inventory levels (Leonard and Davis, 2006) toreduced labor costs and increased profits (Samad et al., 2010). Some suggest that thiswide range of benefits related to LIT adoption seems to have perpetuated manyinconsistencies in construct development and measurement in the literature(Narayanan et al., 2009). This problem is exacerbated by the fact that LIT researchis published in academic journals representing nearly 100 different subject categories(Irani et al., 2010). Therefore, in order to adequately investigate our research questions,these outcomes must be organized in such a way as to allow for proper analysis. Tothis end, we adopt and modify a typology of performance outcomes proposed in recentliterature (Karimi et al., 2007).

Although each individual technology boasts a unique set of anticipated benefits, wesuggest that the vast majority of the performance outcomes (both anticipated andactual) resulting from the adoption of any LIT may be categorized into one of threehigher order outcomes. We define a performance outcome as any result that affects abusiness function of the organization, whether in a positive or negative manner.Examples of specific performance outcomes in the literature are offered in Table II.In this study, we adapt a typology used by Karimi et al. (2007) to classify performanceoutcomes within one of the following three categories:

(1) Efficiency. Encompasses performance outcomes that reduce cost, reduce cycletime, or increase productivity.

(2) Effectiveness. Encompasses performance outcomes that improve decisionmaking, improve planning, improve resource management, or improve delivery.

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(3) Resiliency. Encompasses performance outcomes that build flexibility intoinfrastructure, encourage differentiation of products and services, or establishor maintain external linkages to multiple customers and suppliers.

Of note, we use resiliency in our topology, whereas Karimi et al. (2007) instead useflexibility. We use resiliency in our study in lieu of flexibility because resiliencyaccounts for creating both redundancy and flexibility (Christopher and Peck, 2004;Sheffi, 2005; Sheffi and Rice, 2005). Thus, our use of resiliency will allow us to bettercategorize those performance outcomes that, although important in the supply chaincontext, do not necessarily fall within the categories of efficiency or effectiveness.Table II gives an example of the categorization of performance outcomes used in thisstudy. The method for categorizing these outcomes and enhancing reliability of theprocess is described later in Section 3.

This studys RQ1 investigates the effect of LIT adoption on the performanceoutcomes noted above and reads: do LIT innovations induce positive performanceoutcomes for the adopting firm? The concept of LIT is operationalized in this study viaEDI and RFID. Performance outcomes are operationalized via efficiency, effectiveness,and resiliency and are measured via amalgamation of the variables investigated in theliterature. This study uses three hypotheses to explore the relationship posited by ourresearch question.

Our first hypothesis is concerned with the relationship between LIT adoption andbusiness process efficiencies. Efficiency is a measure of productivity in which what hasbeen accomplished is measured against what is possible to accomplish. A technologymay be defined as a means of uncertainty reduction (Rogers, 2003, p. 13). Thus, bydefinition, any technology should enhance the efficiency of the process in which it isapplied. However, this has not always been demonstrated in the literature. Iskandar et al.(2001) found that employees in firms utilizing EDI perceived no reduction in the numberof employees required to support operations. These findings are congruent with that ofSriram and Banerjee (1994), who found that EDI did not necessarily reduce employeeworkload. Sriram and Banerjee (1994) found that employees were often still required toapprove routine orders, monitor suppliers, and provide a signature for EDI orders. Thislack of reduction in labor may be due to the fact that EDI does not always completelyautomate the processes in which it is applied, which results in the continuance

Performance category

Performance outcome Efficiency Effectiveness ResiliencyReduce processing costs XImprove equipment utilization XImprove planning process XImprove responsiveness XFacilitate decision making XImprove relationship with trading partner XDecrease number of administrative employees XReduce cycle times XIncrease productivity XEnhance channel cooperation XReduce delivery of incorrect product X

Table II.Example of performance

outcome categorization


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of processing work for staff to complete. In addition, EDI may sometimes merely convertthe type of work that employees are required to carry out. For example, although EDImay reduce paperwork processing for some organizations, it may also increase theamount of work required at computer terminals.

Although instances are cited above which support the idea that LIT does not improvelevels of efficiency for an organization, additional research suggests that LIT doesimprove efficiencies. Indeed, consistent with R-A theory, the literature offers manyexamples where use of LIT has been shown to be related to increased efficiencies. Forinstance, contrary to the findings noted above, Wang et al. (2010) demonstrated viasimulation how LIT may significantly reduce manpower requirements. Othersimulation studies offer similar findings regarding efficiencies derived from ITimplementation (Hou and Huang, 2006; Veronneau and Roy, 2009). In addition, Hou andHuang (2006) demonstrated a variety of operational efficiencies (e.g. reduced time forproduct identification) derived from use of LIT. Similarly, Bendavid et al.s (2009) casestudy of B-to-B e-commerce applications in the supply chain suggests that thesetechnologies may yield significant reductions in transaction time while also reducingcosts. Because of the results of these and similar studies, we posit that:

H1. Organizational adoption of LIT increases business process efficiencies.

Our next hypothesis is concerned with the relationship between LIT adoption andbusiness process effectiveness. We define effectiveness as the degree to which businessobjectives are achieved. Thus, measures of effectiveness are usually concerned withhigher-order organizational outcomes. For instance, efficiency may be concerned withreducing order processing costs, whereas effectiveness is concerned with whether ornot process initiatives affect the bottom line.

The literature offers many examples where LIT is shown to increase effectiveness,which also lends support for R-A theory. Srinivasan et al. (1994) demonstrated thecomplimentary effect of LIT on manufacturing supply chains that utilize just-in-time( JIT) practices. Their study demonstrated a large reduction in shipments withdiscrepancies when EDI was employed along with JIT. Chow et al. (2006) found similarbenefits in shipping accuracy via use of RFID. Furthermore, Clark and Hammonds(1997) examination of LIT in the grocery industry found that EDI adoption led toincreased inventory turns and reduced stock-outs. Hardgrave et al. (2008) reachedsimilar conclusions regarding increased effectiveness in his examination of RFID useat Wal-Mart.

In contrast, other studies have concluded insignificant relationships between LITadoption and measures of effectiveness. Crum et al.s (1996) study concluded that EDIdid not improve decision making for firms in the motor carrier industry. Further,Leonard and Davis (2006) realized non-significant results when investigating therelationship between adoption of LIT and a variety of effectiveness measures, toinclude increased fill rates and reduced stock-outs. Thus, we seek to determine if thesecontradictory results are an anomaly by investigating whether or not:

H2. Organizational adoption of LIT increases business process effectiveness.

Our third hypothesis concerns the relationship between LIT adoption and businessprocess resiliency. We define resiliency as the ability to return to normal performancelevels following supply chain disruption (Zsidisin and Wagner, 2010, p. 3).

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Although resiliency rarely translates into immediate increases in efficiencies,effectiveness, or short-term profits, resiliency facilitates an organizations preparationto encounter future, unknown events. This preparedness, then, often leads to an increasein (or at least a retention of) efficiency, effectiveness, and profit in the future.

Both extant research and R-A theory suggest that adoption of IT facilitatesincreased resiliency in the logistics setting. Rogers et al.s (1992) study of EDI usein warehousing suggests that firms using EDI are significantly more able toaccommodate special or abnormal requests and events than firms that do not use EDI.Choes (2008) research in the Korean manufacturing industry corroborates the findingsof Rogers et al. (1992) and suggests that EDI facilitates increased speed and volume ofnew product creation and product changeover, thus increasing operational resiliency.Lim and Palvia (2001) posit that this increased resiliency is achieved primarily viareduction in paperwork and standardization of procedures. However, others haveshown that EDI also leads to expansion of a firms supplier base and increased marketchannel formalization, which also enhances a firms capacity to adapt to marketconditions (Manabe et al., 2005; Vijayasarathy and Robey, 1997). On the other hand,conflicting research suggests that EDI does not benefit channel relationships andcoordination (Johansson and Palsson, 2009; Nakayama, 2003). Thus, we investigatewhether or not:

H3. Organizational adoption of LIT increases business process resiliency.

2.4 Buyer-supplier relationshipsIn order to transfer products from the point of origin to the point of consumption, inter-and intra-organizational collaboration is inherently a key component of the supplychain. As with any collaborative effort, the relationship and level of integrationbetween participants may significantly impact the performance outcomes sought byeach party (Tan et al., 2010). In this study, we define the buyer-supplier relationship asthe quality of the relationship between buyers and suppliers. This relationship may beidentified via eight key dimensions:

(1) communication and information sharing;

(2) cooperation;

(3) trust;

(4) commitment;

(5) relationship value;

(6) power imbalance and interdependence;

(7) adaptation; and

(8) conflict (Boeck and Wamba, 2008).

In this study, we consider relationships consisting of the characteristics of:


(2) cooperation;

(3) trust;

(4) commitment;


17

(5) relationship value; and/or

(6) willingness to adapt as being positive relationships.

Conversely, relationships where these six characteristics are indicated in a negativesense or if indications of power imbalance or conflict are present, we consider to benegative relationships.

Over the past two decades, a variety of studies have demonstrated the positiveoutcomes derived from buyer-supplier co-operation in the supply chain. Larson (1994)found that supply chain relationships consisting of greater levels of trust, respect,cooperation, teamwork, unified purpose, and communication resulted in higher levels ofproduct quality and lower total costs for both the buyer and supplier. Additionally, Kleinand Rais (2009) study of strategic information flows within the supply chain suggeststhat positive supply chain relationships marked by increased strategic informationflows between partners yields significant financial and operational performanceoutcomes. In their study, both buyers and suppliers realized improved management ofassets, reduced operations costs, enhanced productivity, improved planning, flexibility,and control of resources.

These positive outcomes derived from positive buyer-supplier relationships may beexplained by social exchange theory, which views the exchange relationship betweenspecific actors as being contingent upon rewarding reactions from others (Blau, 1964).As discussed above, the adoption of LIT is an inherently collaborative venture. Forexample, for EDI to work effectively, both organizations must agree to adopt and utilizethe technology in a manner that benefits both parties. Thus, when buyer-supplierrelationships are characterized in accord with Boeck and Wambas (2008) dimensions ofa positive relationship, both the buyers and supplier should realize increased levelsof efficiency, effectiveness, and resiliency from the adoption of LIT. In contrast, negativeor undeveloped relationships should decrease the levels of efficiency, effectiveness, andresiliency that may be realized by both firms. As such, we propose that the typeof buyer-supplier relationship (positive, negative, or undeveloped) moderates the degreeof efficiency, effectiveness, and resiliency that a firm may realize via LIT adoption.Accordingly, we propose:

H4a. The relationship between adoption of LIT and business process efficienciesrealized by an organization is moderated by the firms buyer-supplierrelationships. That is, positive relationships increase efficiencies whereasun-developed or poor relationships decrease efficiencies.

H4b. The relationship between adoption of LIT and business process effectivenessrealized by an organization is moderated by the firms buyer-supplierrelationships. That is, positive relationships increase effectiveness whereasun-developed or poor relationships decrease effectiveness.

H4c. The relationship between adoption of LIT and business process resiliencyrealized by an organization is moderated by the firms buyer-supplierrelationships. That is, positive relationships increase resiliency whereasun-developed or poor relationships decrease resiliency.

Figure 2 shows this studys research model.

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To examine the relationships suggested in our model, this study utilizes data derivedfrom existing empirical studies and meta-analytic techniques to investigate therelationship between popular LIT innovations and the hypothesized performanceoutcomes realized by adoption of these technologies. These specific methods arediscussed in the following section.

3. MethodThe purpose of this study is to:

. investigate the relationship between LIT innovation adoption and theperformance outcomes realized by such adoption; and

. test the moderating effect of the buyer-supplier relationship.

To achieve this purpose, we employed a meta-analysis method. We chose ameta-analysis approach for two distinct reasons. First, as noted previously, we havefound conflicting findings in extant literature. Meta-analysis is often used to assimilateresults of existing studies and integrate findings, thus allowing one to draw meaningfulconclusions from a large body of research (Glass, 1976). Second, meta-analysis is notedas an effective method for testing moderation (Hunter and Schmidt, 2004), which we seekto accomplish in this study. Thus, to achieve our research objectives, meta-analysisseemed to be the most desirable method to employ. Not only does this method allow us toinvestigate both of our research questions, but it also facilitates an additionalcontribution to the literature by summarizing a stream of research. The remainder of thissection describes our research method.

3.1 Search for empirical articlesTo begin, relevant manuscripts reporting empirical research findings were sought.To be included in the analysis, the research effort must report the subjective

Figure 2.Research model

Logistics InformationTechnology

Effectiveness

Resiliency

EfficiencyH1

H2

H3

H4a-c

Outcomes

EDI

Buyer-SupplierRelationship

RFID


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or objective measure of an actual performance outcome that could be logicallyattributed to the adoption of EDI or RFID. Because few articles were identified inthe core SCM journals investigated earlier, no discipline restrictions were placed on thesearch in order to find an adequate number of manuscripts. No date restrictions wereapplied to our search; however, due to the nature of the artifacts under investigation,very few studies before 1990 were uncovered. In addition, the literature search wasconducted in October 2010, thus 2010 literature made available on or before this timeperiod was used. Finally, many trade magazines report performance outcomesresulting from LIT adoption. However, we limited our search to academic publicationsso as to use articles that are the result of rigorous academic research.

Two separate searches were conducted, using the same procedure for each LIT.Abstracts were searched using the keywords: EDI or electronic data interchange;RFID or radio frequency identification. No date restrictions were used and the onlyadditional search filter was for scholarly articles. We began by searching the onlinedatabases most extensively used by supply chain researchers as reported byMenachof et al. (2009). Accordingly, we searched the EBSCO Business Source Premierand ProQuest databases for articles that met the selection criteria. The search resultsfrom each database were analyzed to uncover articles that met the criteria. If cursoryreading of the title and abstract suggested any possibility that the article met thecriteria, then it was downloaded and printed. Finally, the articles were thoroughlyreviewed to extract adoption outcomes and commensurate correlations. Table IIIillustrates the number of articles yielded in this stage of the search process. In sum,48 unique articles were used for analysis; 35 for EDI and 13 for RFID.

As noted in Table III, twice as many EDI articles met our criteria for analysis thandid RFID articles. Upon investigation into this phenomenon, we concluded that this isbecause of the research lifecycle of EDI and RFID. A steady stream of academic EDIresearch appears to have begun in the early 1990s and hit its peak during the late 1990sand early 2000s. After approximately 2002, research of this artifact seems to havetapered off. Conversely, a steady stream of academic research involving RFID seems tohave begun in the mid-2000s and is likely in the midst of its popularity at this time.Figure 3 shows these research trends. Of note, our literature search was conductedbefore the end of 2010, which is why the RFID research appears to have tapered off inthis year when, in reality, it is likely at its peak.

3.2 Meta-analysisTo investigate hypotheses one through three (the relationship between LIT andefficiency, effectiveness, and resiliency), we sought to find the average correlationcoefficients across studies. To begin, we extracted all performance outcomes and theirassociated effect size from each article. Some articles investigated only one outcome

Database EDI RFID

ProQuest 1,043 664EBSCO Business Source Premier 721 958Search total 1,764 1,622Unique articles examined in-depth 191 92Articles used for analysis 35 13

Table III.Keyword search results

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from a single sample while others investigated greater than ten outcomes from multiplesamples. This data and the appropriate article descriptives were recorded in aspreadsheet. In sum, 336 performance outcomes were recorded. We then categorizedeach performance outcome into its commensurate category: efficiency, effectiveness, orresiliency. The first author categorized each performance outcome with regard tothe definition of each as provided in Section 2.3. To enhance the reliability of thiscategorization, two additional raters independently categorized a sample of the outcomevariables. Krippendorffs alpha for the categorization was calculated to be 0.94, which isabove the recommended minimum of 0.80 for drawing meaningful conclusions(Krippendorff, 2004). In sum, 111 performance outcomes were categorized as efficiency,129 performance outcomes were categorized as effectiveness, and 96 performanceoutcomes were categorized as resiliency.

After categorizing the performance outcomes, we used meta-analysis proceduresoutlined by Hunter and Schmidt (2004) to correct for sampling error and obtain theappropriate corrected average correlations. In addition to calculating the correctedaverage correlation for efficiency, effectiveness, and resiliency, we calculated thestandard error of the corrected average correlations in order to present appropriateconfidence intervals. The formulae used for the corrected average correlations andstandard error are:

r P

NiriPNi

SEr SDrffiffiffik

p

where r is the corrected average correlation, N is the combined sample size, SEr is thestandard error of the corrected average correlation, SDr is the standard deviation of theuncorrected average correlation, and k is the number of correlations. In addition, weused Rosenthals (1979) file drawer analysis to determine the robustness of our resultsto unpublished or omitted studies.

Upon calculating the appropriate effect sizes, we turned to analysis of themoderator, buyer-supplier relationships. To begin, each article was examined by thefirst author to determine if the article offered any indication of the relationship betweenbuyers and suppliers. If present, this information was typically found in Section 3

Figure 3.EDI and RFID

research trends

EDI Research

201020001990

10

5

0

Year of Article Publication

Fre

qu

ency

201020001990

10

5

0

Year of Article Publication

Fre

qu

ency

RFID Research Logisticsinformationtechnology

21

where the research setting or sample is discussed or in Section 4 if some indicationof relationship was measured in the study. Using the eight dimensions outlined byBoeck and Wamba (2008) as a guide, articles that indicated relationships consisting of:


(2) cooperation;

(3) trust;

(4) commitment;

(5) relationship value; or

(6) willingness to adapt were labeled as positive relationship.

If these six dimensions were indicated in a negative sense or if indications of powerimbalance or conflict were present, the article was labeled as negative relationship.

If none of these issues were addressed in the article, it was labeled as norelationship indicated. Reliability of this measurement technique was again enhancedvia use of two additional raters. These raters used the same method as the first authorto examine a sample of the articles. Near perfect agreement was reached afterindependently rating each article.

To account for different sample sizes between studies, a weighted least squaresregression was used to test for the significance of the moderator variable in each of thethree relationships (Hunter and Schmidt, 2004). This procedure entailed testing thesignificance of regression coefficients in a regression model with the moderatorvariable (buyer-supplier relationship) as the predictor variable and the correlationbetween LIT adoption and the performance outcome (efficiency, effectiveness, orresiliency) as the outcome variable. The moderator variable was dummy coded with 0for no relationship or negative relationship indicated and 1 for positive relationshipindicated. Using this approach, three separate regressions were conducted (one for eachcategory of outcome).

4. ResultsOur analysis began by comparing the performance outcomes of EDI with theperformance outcomes of RFID. As stated previously, we feel it is appropriate tocombine EDI and RFID into one unit of analysis only if the outcomes realized by eachare statistically homogeneous. Results of two-sample t-tests suggest no difference inefficiency (t127 1.54, p 0.120), effectiveness (t109 0.55, p 0.583), or resiliency(t94 1.0, p 0.326) outcomes between EDI and RFID.

Next, we conducted our meta-analysis in accordance with the method prescribed byHunter and Schmidt (2004) to test for relationships between LIT adoption andperformance outcomes (H1 through H3). We also conducted the file drawer analysis inaccord with Rosenthal (1979). Results are shown in Table IV.

The regression analysis of the moderating effect of buyer-supplier relationshipsindicated significant results for efficiency (F1,127 8.0, p 0.005) and resiliency(F1,94 6.56, p 0.012). However, the moderating effect of buyer-supplier relationshipwas found to be insignificant for effectiveness (F1,109 1.34, p 0.249). Comparison ofmoderated and unmoderated effect sizes for efficiency, effectiveness, and resiliency arereported in Table V.

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5. DiscussionThe results of this study provide evidence in support of our hypothesized relationships(H1-H3) between LIT adoption and efficiency, effectiveness, and resiliencyperformance outcomes (corrected mean r 0.40, 0.34, and 0.18, respectively). Giventhese results, we feel comfortable in concluding that, consistent with R-A theory, LITadoption generally leads to positive performance outcomes. We also conclude thatconflicting results are likely caused by unaccounted for moderating variables orartifacts specific to a particular study.

Our study also suggests that the quality of the buyer-supplier relationshipmoderates the relationship between LIT adoption and performance outcomes, thusproviding partial support for H4 and providing a possible explanation for some of theconflicting results of past studies. Specifically, our study suggests that the moderatingrelationship is significant for efficiency and resiliency outcomes (H4a and H4c), but notfor effectiveness outcomes (H4b). Table VI illustrates some examples from theliterature where the buyer-supplier relationship appears to moderate the relationshipbetween LIT adoption and performance outcomes.

As illustrated in Table VI, studies that indicate a positive buyer-supplier relationshiptend to yield, on average, larger effect sizes than studies that indicated a negativerelationship or did not indicate any relationship. These findings suggest theoreticalimplications for future research and are discussed further in the next section.

5.1 Implications for theory and future researchThe findings support the relationships posited by R-A theory and RBV in thatcomplementary firm resources may allow a firm to realize competitive advantage vialogistics innovation adoption. As suggested by our results, positive buyer-supplierrelationships induce larger effect sizes for the relationships between LIT adoption

Outcome k n Mean r SDr Corrected mean r SEr 95% CI File drawer k

Efficiency 129 9,911 0.41 0.28 0.40 0.02 0.37, 0.42 73,199Effectiveness 111 9,514 0.39 0.29 0.34 0.03 0.31, 0.37 45,457Resiliency 96 7,807 0.23 0.33 0.18 0.03 0.15, 0.21 10,673

Note: k number of correlations, n total sample size, mean r uncorrected mean correlation, SDr standard deviation of average uncorrected correlation, corrected mean r average correctedcorrelation, SEr standard error of corrected correlation, 95 percent CI lower and upper limits of95 percent confidence interval, file drawer k number of studies averaging null results that must befound to conclude that overall results were due to sampling bias at p , 0.05

Table IV.Meta-analysis of

relationship betweenperformance outcomes

and LIT adoption

Corrected mean rOutcome No/negative relationship Positive relationship Difference

Efficiency 0.34 0.43 0.09 *

Effectiveness 0.34 0.35 0.01Resiliency 0.13 0.31 0.18 *

Note: Significant at: *p , 0.01Table V.

Effect size comparison


23

and measures of efficiency and resiliency. This larger effect implies a competitiveadvantage for firms that adopt LIT and possess a complimentary firm resource (suchas a positive buyer-supplier relationship) over firms that adopt LIT and do not possessthe complementary resource. Given our findings, we suggest expanding Grawes (2009)logistics innovation model, as shown in Figure 4. Components in bold constitute ouradditions to Grawes (2009) original model.

Consistent with literature regarding RBV (Barney, 1991), we posit that the adoptionof a logistics innovation leads to generally positive outcomes in lieu of leading directlyto competitive advantage, as it does in the original model. Most logistics innovationsare not necessarily a resource that can directly invoke sustained competitive advantageas they often do not embody all three criteria of such a resource: they are not:

(1) valuable;

(2) heterogeneously distributed across firms; and

(3) imperfectly mobile (Mata et al., 1995).

Being an innovation used for logistics purposes makes meeting these requirementsespecially difficult given the collaborative nature of the discipline and the subsequentrequirement for multiple firms to employ similar technologies in order to work in unison.However, as demonstrated in our study, when complimentary resources are combinedwith logistics innovations, performance outcomes are enhanced. This significantincrease in performance may, in turn, lead to competitive advantage. This idea iscongruent with past literature that suggests resource complementarity may play

Study OutcomeB-S

relationshipEffectsize

Correctedmean r a D

Teo et al. (1995) Efficiency (decreaseddocument prep costs)

Positive 0.60 0.40 0.20

Iskandar et al. (2001) Efficiency (decreased admincosts)

Negative 0.10 0.40 20.30

Philip and Pedersen(1997)

Resiliency (stronger tradingrelations)

Positive 0.58 0.18 0.40

Johansson andPalsson (2009)

Resiliency (enhanced externalcoordination)

Noneindicated

0.06 0.18 20.12

Note: aCorrected mean r for entire study sampleTable VI.

Figure 4.Updated logisticsinnovation model

Source: Adapted from Grawe (2009)

Environmental factorsOrganization of labor ()CompetitionCapital scarcity

Organizational factorsKnowledgeTechnologyRelationship network factorsFinancial resourcesManagement resources

Logistics innovation

Logistics innovation diffusion

Competitive advantage

Complimentaryfirm resources

Performanceoutcomes

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an important role in RBV theory because of its ability to create competitive advantagevia combining two otherwise non-competitive advantage-inducing resources (Wade andHulland, 2004). Accordingly, we add complimentary firm resources as a moderator inGrawes (2009) model.

Our results suggest that buyer-supplier relationships do not moderate therelationship between LIT adoption and effectiveness outcomes. Thus, measures ofeffectiveness observed in the literature may not be as dependent on relationships withbuyers and suppliers as measures of efficiency and resiliency. This may be becauseeffectiveness measures (e.g. improved internal decision making, etc.) often addressinternal processes that are unaffected by or insulated from external organizations orevents, whereas measures of efficiency and resiliency (e.g. reduced transaction errorrates and improved inter-organizational data sharing, respectively) encompassprocesses that are generally more affected by external relationships. In short, ourresults indicate that the buyer-supplier relationship may not serve as a complimentaryresource to measures of effectiveness. As such, we suggest that other complementaryfirm resources may moderate the relationship between LIT adoption and measures ofeffectiveness. For example, absorptive capacity, defined as an organizations ability torecognize, assimilate, and apply new information (Cohen and Levinthal, 1990),may complement an organizations adoption of LIT in such a way as to increase levels ofeffectiveness outcomes. We recommend that future logistics innovation studies look toidentify and test additional complementary resources, understanding that eachinnovation will require different types of complimentary resources to producecompetitive advantage.

Because we found some studies that indicated positive relationships yet stillrealized insignificant results, we believe that additional variables likely moderate therelationship between LIT adoption and performance. Given our review of theliterature used in this study, we posit that additional variables worth investigatingmay be time since adoption, market position, firm size, organizational learningabilities, and absorptive capacity. These variables have been demonstrated to affectperformance outcomes in previous studies (Chen Y.-S. et al., 2009; Liu and Forsythe,2011; Zhao et al., 2011), and may affect the degree of performance achieved via LITadoption. In addition, MIS literature suggests that degree to which IT is assimilatedwithin business processes affects the degree of performance derived from thetechnology (Rai et al., 2009; Setia et al., 2011). This suggests that firms seeking toobtain competitive advantage should do more than just adopt an LIT; instead, theyshould take steps to integrate the technology into all applicable business processes inorder to maximize the performance achieved from adoption. Because we did not findsufficient existing data to analyze these possible effects via our meta-analysis, werecommend new studies be designed to specifically test the potential moderatorsnoted above.

Another future research direction entails investigating performance outcomes andmoderating effects of complementary resources in regard to the emerging area ofinternet-based/e-business applications. The emergence of e-business as an importantLIT resource has evoked attention from practitioners and academics alike(Porterfield et al., 2010; Smart, 2010; Wagner and Sweeney, 2010). Integration of thesupply chain via e-business offers a variety of new challenges and opportunities fororganizations (Srinivasan, 2010). However, we suspect that, although the medium may


25

have changed, the underlying principles examined in our study remain the same.In this regard, the findings of a study by Wiengarten et al. (2011) suggest that adoptionof e-business applications not only have a positive impact on operational performance,but that this relationship is moderated by the level in which key suppliers are ready andwilling to engage in e-business with the adopting firm. The results of Wiengarten et al.(2011) thus support our assertion that the findings of our study maygeneralize to other LITs, such as e-business. Future research can determine if ourassertion holds.

5.2 Implications for practiceThis study provides two primary implications for practitioners. First, our resultssuggest that, in most cases, adoption of RFID or EDI leads to positive results for theadopting firm. However, the results also suggest that additional factors may help orhinder a firms ability to attain increased performance via LIT adoption. Our studylooked only at buyer-supplier relationships as a complimentary resource; othercomplimentary resources likely exist. Most importantly, this study reaffirms the ideathat organizations and technology adoption do not operate in a vacuum. Thus, firmslooking to adopt LIT should carefully examine the possible interaction effects betweentheir firm, their partners, the LIT, and the unique circumstances and situations inwhich the new technology is to be employed.

Second, this study emphasizes the importance of fostering positive buyer-supplierrelationships in the supply chain and offers evidence in support of the benefits thatmay be realized by firms who maintain positive relationships with their tradingpartners. Given our definition of LIT and the nature of the supply chain, LITs areinherently collaborative technologies. However, some firms have undoubtedly adoptedthese technologies without first building positive relationships or even despite poorrelationships with their partners. Although some firms may still realize positive resultsdespite coerced integration or poor relationships (Deitz et al., 2009), our study suggeststhat it would behoove most firms interested in using any LIT to first work towardbuilding positive relationships with their trading partners if they hope to achievemaximum benefits from the employment of the technology. The benefits ofcollaboration and building positive relationships have been demonstrated in a varietyof settings in the supply chain literature (Daugherty, 2011; Klein and Rai, 2009; Larson,1994; Schulz and Blecken, 2010). Our study provides additional evidence that shouldmotivate firms to continue to foster positive relationships.

5.3 LimitationsMeta-analysis is generally accepted as a viable and valid research method, and isused often to explore the hypothesized effects of moderating variables.However, dependence on secondary data derived from the research published by avariety of authors in a number of journals from varying disciplines over a wide range ofyears is likely the most serious validity threat to our study. To reduce this validity threat,we carefully selected only published empirical studies to use in our analysis. In addition,we used meta-analysis techniques that have been demonstrated to mitigate such validitythreats (Hunter and Schmidt, 2004). We suggest future research efforts in this areaemploy primary data in hopes of corroborating the findings of this study.

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An additional limitation of this study is common to most studies that rely onsecondary data or the assimilation of others research, which is the omission of relevantresearch studies in our analysis. Although we thoroughly searched what we feelare the most appropriate databases for research that met our criteria, some research mayhave been overlooked and thus not included in our analysis. In addition, publication biasmay have artificially inflated the number of studies we found that report significantand/or positive results. To address this potential limitation, we used Rosenthals (1979)file drawer analysis to estimate the number of unpublished or otherwise omitted studiesrequired to challenge the significance of this studys findings. Results of our analyses(illustrated in Table IV) suggest that our findings regarding the relationships tested inthis study are robust to the omission of contradictory research.

Finally, we assume that our sampling strategy led us to investigate LITs (e.g. EDIand RFID) that are representative of the population of LIT. The results of our studysuggest that adoption of IT for logistics purposes may lead to increased levels ofperformance for the adopting firm and that complimentary firm resources may affectthe degree of performance. However, caution must be used when making suchgeneralizations. For example, as discussed previously, e-business applications offer avariety of new opportunities and challenges for the supply chain. Undoubtedly, theseopportunities and challenges differ from those presented by EDI and RFID, which mayaffect the degree to which our findings apply. Only future research can test thegeneralizability of our findings by investigating other LITs.

6. ConclusionThis paper serves to assimilate extant literature regarding the relationship between LITadoption and measures of performance in terms of efficiency, effectiveness, and resiliency.Using a meta-analysis approach and the data reported in 48 empirical EDI and RFIDresearch articles, we found that the implementation of LIT innovation generally producespositive performance outcomes for the adopting organization. We also examined themoderating effect of buyer-supplier relationships on the relationship between LITadoption and positive performance outcomes and found that positive buyer-supplierrelationships greatly enhance levels of efficiency and resiliency outcomes realized by LITadoption. This finding offers one possible explanation for the incongruent findings of pastresearch. The buyer-supplier relationship was not shown to be a significant moderator ofthe relationship between LIT adoption and effectiveness outcomes, which suggests thatcomplimentary firm resources must truly be complimentary to both the specific LIT andthe desired outcome if they are to help the firm achieve competitive advantage.

Our findings also provide support for the extension of Grawes (2009) logisticsinnovation model. In respect to RBV, we suggest that logistics innovation is a directantecedent to performance outcomes, but not necessarily to competitive advantage.We also suggest that this relationship is moderated by complimentary firm resources.Through examining the role of buyer-supplier relationships, our study supports theidea of resource complementarity as a potential means for realizing competitiveadvantage. Practitioners should consider complementarity when adopting LIT withthe understanding that additional organizational factors may serve to help or hinderthe attainment of desired outcomes. With this in mind, we proposed an updatedlogistics innovation model, which presents a foundation for future research regardingthe outcomes of logistics innovation adoption.


27

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Appendix

About the authorsBenjamin T. Hazen is a PhD candidate in the Aviation and Supply Chain Management Departmentat Auburn University and an active duty US Air Force maintenance officer. His research interestsinclude reverse logistics, innovation, information systems, and sustainability. His research hasbeen accepted to several journals, to include International Journal of Production Economics,International Journal of Logistics Management, International Journal of Logistics Systems andManagement, and International Journal of Physical Distribution and Logistics Management.He earned his MBA from the California State University at Dominguez Hills, his MA inOrganisational Leadership from Gonzaga University, and his BS in Business Administration fromColorado Christian University. The views expressed in this article are those of the author and donot reflect the official policy or position of the United States Air Force, Department of Defence,or the US Government. Benjamin T. Hazen is the corresponding author and can be contacted at:[email protected]

Terry Anthony Byrd is Bray Distinguished Professor of Management Information Systems(MIS) and Chair of the Aviation and Supply Chain Management Department in the College ofBusiness, Auburn University. He holds a BS in Electrical Engineering from the University ofMassachusetts at Amherst and a PhD in MIS from the University of South Carolina. His researchhas appeared inMISQuarterly, Journal ofManagement Information Systems,European Journal ofInformation Systems, Decision Sciences, OMEGA, Interfaces and other leading journals. Hiscurrent research interests focus on the design, development, implementation, diffusion, andinfusion of information technology in facilitating a variety of individual, group, o

30competitive advantage with logistics information technology

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