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RFID technology by Logistics companies in China: A technology diffusion

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The assimilation of RFID technology by Chinese companies: A

technology diffusion perspective

ABSTRACT

RFID (Radio frequency identification) is an emerging technology that attracts attention of supply chain

participants. However, most Chinese firms just adopt this innovation without fully utilizing its benefits.

Extant IS research also only focuses on factors that impact its adoption rather than its post adoption.

Assimilation theories suggest that most information technologies exhibit an “assimilation gap” which

means the widespread usage tends to lag behind their adoption. Drawing upon the TOE framework, we

investigate antecedents that influence RFID assimilation into these Chinese companies. Empirical results

indicate factors including IT infrastructure, managerial capability, absorptive capacity and environmental

uncertainty all have significant influence on RFID assimilation.

Keywords

Innovation assimilation, RFID technology, TOE framework, DOI theory

1.0 INTRODUCTION

In recent years, RFID (Radio Frequency Identification) has emerged as a new technology to

increase operations efficiency in warehouse management and inventory monitoring. Compared with

traditional bar code, RFID can identify tagged products without line of sight and track the status of

products when they are received or shipped away from the warehouse in real-time. Therefore, product

inventory status can be captured with less labor force and thus it can increase inventory management

efficiency.

Most recent RFID related research focus on its adoption. These research includes Lin and Ho

[1]’s empirical study on the RFID technology adoption for logistics service providers in China, Tsai et al

[2]’s investigation of RFID adoption intention from Taiwanese retail chains, and Wang et al [3]’s

investigation of RFID adoption in Taiwanese manufacturing industries. However, adoption is only one

part of an assimilation process, which cannot ensure wide-scale assimilation. Only through wide-scale

assimilation can the benefits of RFID technology be fully realized. As indicated by Chatterjee et al. [4],

many firms have failed to achieve deeper integration their organizational practices, which goes beyond

initial adoption and they thus cannot realize the full potential of this innovation. Because of the distinction

between adoption (or acquisition) and its degree of deployment or routinization, the antecedents and

mechanisms of innovation deployment may be different from the drivers of innovation adoption.

According to the literature review of Fichman [5] and Zhu et al. [6], the post adoption stages of

assimilation are especially worthy of a focused study.

Moreover, China’s RFID market is still in infancy, especially in manufacturing industry [7].

Compared with developed countries such as USA where RFID industry chain includes mature and large-

scale projects from giant business (such as Wal-Mart), most RFID projects in China are relatively small

and are still in a pilot test stage. As a world-class manufacturing center, Chinese manufacturing

companies are facing pressure from more retailers, distributors, and suppliers to provide RFID-compatible

technology platforms. Thus, exploring the assimilation process in Chinese firms and promote the

technology’s deep integration is a topic worthy of study.

From theoretical perspective, most RFID related research focus on western developed countries

rather than developing countries such as China. However, different cultural contexts and environmental

settings may generate different results. For example, Chau et al. [8] investigated the assimilation of

Internet technologies in China and find contrary to the popular idea in the West that environmental

uncertainty plays positive influence on a firm’s proactive and innovative strategies, environmental

uncertainty plays negative roles on Chinese firms’ Internet assimilation. Again according to Chau et al.

[8], Chinese firms also have the highest concern for the regulatory environment in which they and their

business partners reside. It is because the Chinese government still maintained powerful political

influence and control over the development of innovations. These differences motivate us to investigate

how RFID can be assimilated in Chinese firms and how this process is different from Western countries.

In this paper, we follow Zhu et al. [9] and conceptualize assimilation as the full life-cycle that not

only includes a company’s evaluation of an innovation and its adoption but also its full-scale deployment,

in which an innovation “becomes an integral part of the value chain activities”. This conceptualization is

different from adoption in several aspects: the involvement of vendors is lowered, the system is “rolled

out” for routine usage by the operational-level users, and radical customizations such as process

reengineering are complete at this stage.

Motivated by above theoretical gaps, we propose an integrative model to address the following

questions: What factors (including technological, organizational, and environmental factors) impact RFID

assimilation in the Chinese context? An integrative theoretical model combining diffusion of innovation

theory, institutional theory is built to address this problem. The research model is tested against data

collected from logistics companies in Hong Kong and Pearl River Delta Region of China that have

already assimilated RFID technology in different stages. Structural equation modeling is used to test each

factor’s influence across the assimilation processes.

2.0 REVIEW OF THEORIES ON INNOVATION ASSIMILATION

In this chapter, we first illustrate the differences between adoption and assimilation and then

review literatures of innovation assimilation, trying to find out antecedents of different innovations.

2.0.1 Differences between adoption and assimilation

Adoption is a widely investigated research topic in IS research. It refers to the physical acquisition or

purchase of an innovation [10]. Many existing RFID related research focus on this stage. For example,

Lin and Ho [1] conducted an empirical study on the RFID technology adoption for logistics service

providers in China. They find that explicitness and accumulation of technology, organizational

encouragement for innovation, quality of human resources, and governmental support all significantly

influence RFID adoption intention of Chinese logistics companies. Tsai et al. [2] investigated

determinants of RFID adoption intention from Taiwanese retail chains and found relative advantage,

complexity; supply chain integration and organizational readiness all have significant influences on RFID

adoption intention of Taiwanese retailers. Wang et al. [3] studied determinants of RFID adoption in

Taiwan’s manufacturing industry and find six variables including: compatibility, complexity, firm size,

information intensity, competitive pressure and trading partner pressures significantly influence adoption

intention. According to Rogers, adoption is regarded as management authorizing purchase of the

technology, rather than capturing whether the firm has actually deployed the technology or moves beyond

a trail stage towards routinizing the technology for everyday use. Especially for technologies with high

implementation complexity, little or no actual implementation occurs after technology adoption, which

was known as the assimilation gap [11].

Previous literature has different conceptualizations of innovation assimilation. According to Fichman and

Carroll [5], assimilation is the extent to which a firm has progressed through stages of innovation

deployment—from initial awareness and adoption to general deployment and routinization. In Zhu et al.

[6]’s investigation of e-business assimilation, they define assimilation as a series of stages from a firm’s

initial evaluation of E-business at the pre-adoption stage (i.e., initiation) to its formal adoption and finally

to its full-scale deployment at the post-implementation stage in which E-business becomes an integral part

of the value chain activities (i.e., routinization). In Bala et al. [12] ‘s investigation of inter-organizational

business process standards, they conceptualize it as four stages of IBPS assimilation: awareness, adoption

(or rejection), limited deployment, and general deployment. And they only focus on the subsequent stages

except the awareness because of the practical and theoretical importance of the subsequent stages.

Consistent with previous research, we define RFID assimilation as “the extent to which a firm has

progressed through stages of innovation deployment-from initial awareness and adoption to general

deployment or routinization.”

2.1 Antecedents of Innovation Assimilation

In this section, we introduce literature related with TOE framework to identify the antecedents of

different innovations assimilation. TOE framework identifies the influencing factors under the technology,

organization, and environment categories that can impact IS-related decisions [13]. Most innovation-

related research employs it to investigate influencing factors that can impact innovation assimilation. This

kind of research include Furneaux and Wade’s [14] investigation of discontinuance intention of

information systems. Wang et al. [3] investigate determinants of RFID adoption in the manufacturing

industry in Taiwan drawing upon the TOE framework. Kuan and Chau [15] employ the TOE framework

to investigate EDI adoption in small businesses. Hong and Zhu [16] investigate six variables drawing

upon the TOE framework to successfully differentiate non-adopters from adopters of e-commerce. Zhu et

al. [17] explore how factors within the TOE framework influence the e-business assimilation at the

organizational level.

As indicated by Wang [3], the TOE framework has substantial consistent empirical support in the

literature; thus, it provides a foundation for the analysis and consideration of suitable factors to

understand an innovation-adoption decision. Therefore, we draw upon this framework to understand the

influence of antecedents within each sub-category.

Regarding the technological context, classic DOI (diffusion of innovation) theory proposed by

Rogers [18] identifies five innovation characteristics including: (1) relative advantage, which means “the

degree to which an innovation is perceived as being better than the idea it supersedes.”([18], p.213) (2)

compatibility, which is defined as “the degree to which an innovation is consistent with existing business

processes, practices and value systems”; ([18]) (3) complexity, the degree to which an innovation is

difficult to use; ([18], p.230) (4) observability, the degree to which the results of an innovation are visible

to others; ([18], p.232) (5) trialability, the degree to which an innovation can be experimented with ([18],

p.231). However, most studies emphasized the impact of first three attributes: relative advantage,

complexity and compatibility. Tornatky and Klein [19] conducted a meta-analysis of the relationship

between innovation attributes and innovation adoption from 75 articles. They concluded that three

attributes, i.e., relative advantage, complexity, and compatibility, enhance the likelihood of innovation

adoption. On the other hand, TAM is an established theory that explain the antecedents of IS innovation

from technology perspective. This theory considers two key drivers, namely perceived usefulness and

perceived ease of use. We can see that perceived usefulness and perceived ease of use are equivalent to

relative advantage and complexity respectively. However, recent innovation research that investigated the

Internet-based innovations such as supply chain technologies and e-commerce argue that compatibility

has become congruent with existing experiences and practices among trading partners and therefore

should be neglected from the relevant research or merged with the attributes of perceive ease of use.

Accordingly, we only include the first two technology attributes, relative advantage and complexity, into

our research model.

According to Iacovou et al. [67], organizational context describes the characteristics of an

organization, which mainly include firm size, degree of centralization, formalization, complexity of its

managerial structure, the quality of human resources, and amount of slack resources available. These

factors could help explain why some organizations are more innovative while others are less prone to

innovate. As indicated by Mishar et al. [13], the diversified performance differences of innovation

diffusion is due to the significant differences in the resources the firm possess, which include managerial

knowledge, technology infrastructure, and prior experiences with IT. Some other literatures also suggest

that the value firms obtain from IT is dependent on their skills to leverage it [20]. Firms which possess

strong managerial capability and prior IT experiences can utilize IT more efficiently than their

competitors. Therefore, we include managerial capability, IT infrastructure and absorptive capacity which

is regarded as organizational resources as antecedents.

As indicated by Tornatzky and Fleischer [21], environmental context is the area in which a firm

conducts its business-the industry, competitors, and dealing with government. DiMaggio and Powell

[22]’s institutional theory proposes that institutional environment provides rule-like social expectations

and norms for appropriate organizational structures, operations, behaviors and practices. The firm’s

perceptions of these pressures affect its interpretation of the environment in general and innovation

intentions in particular. Thus, we investigate factors within the institutional pressure that impact RFID

assimilation processes. Institutional pressures are classified into three categories: coercive pressure,

normative pressure, and mimetic pressure.

Coercive pressure is defined as the pressure originating from political influences exerted by the

powerful firms on which the focal firm depends [22]. This pressure is mainly from dominant suppliers

and customers because these dominant partners hold resources organizations need such as new business

contracts or funding.

Normative pressure refers to the perceived extent to which members of the dyadic relational

channels have adopted the innovation and the extent to which the government and industry agencies

promote the use of information technology [22]. In our model, we use regulatory support as the normative

pressure that will influence RFID’s assimilation processes.

Mimetic pressures are those which make an organization imitate others when the organizational

technologies are poorly understood, goals are ambiguous, or the environment is uncertain [22]. Because

RFID standard is still uncertain and its investment is irreversible which means the market of RFID is still

uncertain. Companies will follow others which have successfully implemented this technology.

Meanwhile, fierce competition will make companies imitate others which have already successfully

adopted this technology into their enterprises. In our research, we include market uncertainty and

competition intensity as the source of mimetic pressure.

3.0 RESEARCH MODEL AND HYPOTHESES

In this chapter, we propose an integrative model to explain and predict RFID innovation

assimilation for firms in China. As depicted in Figure 3.1, we use TOE framework to identify the

antecedents within each category. At beginning, we provide definitions of each constructs that will be

used in our hypotheses (see Table 3.1).

Table 3.1 Definitions of constructs

Construct Definition

Relative advantage “The degree to which an innovation is perceived as

being better than the idea it supersedes” [18]

Complexity “The degree to which innovation is difficult to

understand and use” [18]

IT infrastructure A shared information delivery base, the business

functionality of which has been defined in terms of

its reach and range [23]

Managerial capability Refers to the ability and willingness to mobilize

resources and change existing business processes

during innovation implementation. [17]

Absorptive capacity Is defined as the ability of an organization to

identify, assimilate and exploit knowledge from the

environment. [24].

Regulatory support Is a government’s willingness to embrace and

support regulations and standards to promote RFID

[25]

Environmental uncertainty “The degree to which the future states of the

environment cannot be accurately anticipated or

predicted due to imperfect information” [26]

Competition intensity Refers to “the degree that company is affected by

competitors in the market” [27].

3.1 Predictions Related to Technological Factors

In this section, we introduce influencing factors within the technological context. These factors include:

relative advantage and complexity. The reason to include them are discussed as below.

3.1.1 Relative advantage

Several studies have used relative advantage to predict innovation adoption and diffusion. For

example, Tsai et al. [2] investigate RFID adoption in the Taiwanese retail industry and find relative

advantage has a positive impact on RFID adoption. Besides this study, Wang et al. [3] investigate

determinants of RFID adoption in the manufacturing industry and they also find relative advantage has a

positive effect on RFID adoption.

Zhu et al. [6] investigate determinants of post-adoption stages of innovation diffusion, using

enterprise digital transformation as an example of innovation. Their results indicate relative advantage

positively influence e-business usage. Ramdani and Kawalek [28] predict SME’s adoption of enterprise

systems and suggest that the greater the perceived relative advantage of enterprise systems, the more

likely they will be adopted by SMEs (small and medium enterprises).

Early assimilation

stage

Technology context

Relative

advantage

Complexity

Managerial

capability

Absorptive

capacity

IT

infrastructure

Regulatory

support

Competition

intensity

Environmental

uncertainty

Environmental context

Organizational context

H1(+)

H2(-)

H3(+)

H4(+)

H5(+)

H6(+)

H8(-)

H7(+)

RFID

assimilation

Figure 3.1 Research model (Own elaboration)

Kwan and Chau [29] investigate adoption of EDI technology and suggest relative advantage is a key

factor within the technological context that can influence EDI adoption.

Drawing upon previous literature, relative advantage is an important factor that motivates

organizations to adopt an innovation. This is true because when assimilating RFID technology, decision

makers should evaluate its benefit and check whether it has relative advantage over traditional bar code

systems. Compared with traditional bar code systems, RFID can help retailers track and control stock in

real-time. If integrated with other backend systems, RFID can reduce the lead time and then improve

replenishment efficiency, and thus reduce product misplacement, stock-level, out-of-stock and labor costs

[2]. Accordingly, we propose hypothesis as follows:

H1. Organizations that perceive the relative advantage of RFID will have a high degree of assimilation.

3.1.2 Complexity

Complexity is defined as “the degree to which an innovation is perceived as relatively difficult to

understand and use” ([18], p.230). RFID is a radical innovation that is resource intensive and requires

substantial changes to existing work processes and organizational context [2], it is necessary for us to

include complexity as antecedents. In the RFID context, Wang et al. [3] operationalize RFID complexity

as immaturity of RFID technology, lack of common standards, the difficulty of integrating RFID with the

existing enterprises’ information systems and business processes. Thus, complexity of innovation should

also be analyzed to make sure that an organization has enough financial and human capital to overcome

the difficulties during implementation process.

According to Tsai et al. [2], complexity includes two components: the challenges of

customization and high costs. RFID systems should be customized for a specific working environment;

for example, RFID hardware must withstand high temperatures and humidity and operate in a variety of

work environment and product materials. There is a great need to adjust the RFID backend system and

existing IT systems for better data transmission. The second complexity involves the high

investment/maintenance costs. Costs related to RFID operations including tags, readers and IT

infrastructures are high and irreversible. Costs are further exacerbated by the absence of uniform RFID

standards. Companies that perceive high technology complexity will be very cautious of adopting RFID

and assimilate it into their enterprises. Accordingly, we predict the following:

H2: Organizations that perceive high complexity of RFID will have a low degree of

assimilation.

3.2 Predictions Related to Organizational Factors

Besides technological context, factors in the organizational context can also influence RFID

assimilation processes. We include IT infrastructure, managerial capability as well as absorptive capacity

into the organizational context and investigate their influence on RFID assimilation into Chinese logistics

companies.

3.2.1 IT infrastructure

Regarding IT infrastructure, Grant [30] classified IT-based resources into three categories: (1) the

tangible resource comprising the physical IT infrastructure components; (2) the human IT resources

comprising the technical and managerial IT skills; (3) the intangible IT-enabled resources such as

knowledge assets, customer orientation, and synergy.

According to resource-based theory, tangible resources enable firms to assimilate innovations

more quickly and improve products [31]. Compared to a less developed and non-integrated IT

infrastructure, a highly integrated IT infrastructure provides a platform to launch innovative IT

applications faster than its competitors [31]. Therefore, tangible resources are relevant factors that might

influence RFID assimilation processes.

Human resources include two components: technical IT skills and managerial skills. Since RFID

assimilation process always entails significant changes of the business processes and IT infrastructure,

managerial capability play an important role in coordinating activities related with process redesign [17].

Technical IT skills become important in the analysis, design, and implementation of changed business

processes.

Intangible resource include customer orientation, knowledge assets and synergy [31]. Previous

research suggests that customer orientation has a significant role on innovation assimilation. If a company

is more customer-oriented, it will consider improving customers’ satisfaction through introducing

innovations such as RFID technology. It is because RFID technology can shorten the lead time from

manufacturers to customers, increase the traceability of products that can make the products more visible

and therefore improve the customer services. Thus, customer orientation might be a significant sub-factor

that influences RFID assimilation processes.

Knowledge assets refers to how the knowledge, skills and experiences of the company’s

employees is embedded in its processes, policies, and information repositories [31]. Knowledge assets are

also critical for the RFID assimilation processes, because if a firm has strong repositories of knowledge

and skills in their employees, it will be easier for them to assimilation new innovations.

Synergy is defined as sharing of resources and capabilities across organizational divisions [31].

The firm that can share knowledge and information across its functional units is more flexible and can

react faster to market needs. Because RFID technology enables information sharing across warehouse

division, purchasing division and production division across a company, it provides a good way to share

resources and information. Thus, synergy of intangible resources should also relate positively with RFID

assimilation, and we include it into our research model.

Based on the above review, physical IT infrastructure, human IT resources, and synergy should

all have significant, positive relationships with RFID assimilation. As indicated by Bharadwaj [31], a

firm’s IT infrastructure is a major business resource and a key source for maintaining long-term

competitive advantage. Therefore, we include IT infrastructure as an antecedent of RFID assimilation

process.

According to Bharadwaj [31], IT as a resource can generate competitive value only when it

leverages or enables pre-existing resources and skills. Hence, IT infrastructure is critical to RFID

assimilation. This limitation should also apply to RFID technology implementation. RFID can achieve its

greatest benefits only through integrating with other backend systems such as enterprise resource

planning (ERP), customer relationship management (CRM), and decision support systems (DSS) and

sharing data and information with them [7]. Therefore, companies which have sophisticated IT

infrastructure have enough capabilities to assimilate RFID technology into their business operations and

processes. Thus, we predict the following:

H3. Increased sophistication of infrastructure leads to increased RFID assimilation.

3.2.2 Managerial capability

Asif et al. [32] suggest that the deployment of tags and readers by themselves cannot push

companies ahead of their competitors. What is more important is how an organization uses the fine-

grained and real-time data derived from RFID to change and improve its business processes. It is

leveraging this data that will determine the extent of strategic benefit the companies can obtain from

RFID technology. RFID is a radical innovation that can change the operational process of an organization

radically, but doing so requires substantial managerial capability. Fichman [33] thus suggest technologies

that enable more radical improvement require substantial complementary changes to organizational

structures, routines, and policies. Consequently, RFID assimilation requires changes regarding

organizational and process adaptations [4].

Robert et al. [34] note that not all firms can manage adaptation effectively because they lack

managerial skills and know-how for change management. Thus, the effect of managerial capability,

which refers to the capability of managing organizational adaptation to accommodate RFID assimilation

[17] is important to investigate.

Organizational adaptations regarding RFID assimilation include making organization changes on

structures and coordination mechanisms [4], and acquiring new expertise necessary to use the innovation

[35]. Several studies explain IT failure as a frequent result of management issues such as lack of synergy

between business and IT skills, knowledge on how to integrate the technology with the business strategy,

how to acquire skilled technical people and train them to use the RFID systems. Such broad management

failures suggest that managerial obstacles can impede RFID assimilation when organizations cannot make

organizational changes, redesign business processes, and acquire new expertise. Therefore, organizations

that have advanced managerial capability can assimilate RFID smoothly than those that do not have

enough such capabilities. According, predict the following:

H4: Managerial capability has a positive influence on companies’ RFID assimilation.

3.2.3 Absorptive Capacity

As defined by Cohen and Levinthal [24], an organization’s absorptive capacity is represented by

its ability to recognize the value of new, external information, absorb it, and apply it for commercial ends.

They also point out that effective absorptive capacity can be determined by prior relevant knowledge and

intensity of effort. Especially in an uncertain environment, absorptive capacity can affect expectations

formation and enable a firm to predict more accurately the nature and commercial potential of

technological advances. Because RFID is a radical innovation that is full of uncertainty, it requires

absorptive capacity to recognize the value of it, absorb it and apply it to their operations.

Existing literature regard absorptive capacity as a knowledge base, especially the extent of prior

knowledge the firm possess [36]. This is similar to path dependency, which is a firm’s ability and

incentive to adopt an innovation. It can be largely determined by its level of related experience with prior

relevant technologies [24]. Also indicated by Cohen and Levinthal [24], such skills and knowledge are

critical for successful adoption of new technology standards. Thus, firms which have prior experiences

and knowledge with related technology such as EDI or barcode systems may have developed technical

and managerial skills for deploying RFID technology compared with those firms without EDI or barcode

experiences.

In Zhu et al.’s [37] investigation of migration to open-standard inter-organizational systems

(IOS), they suggest that firms have fostered technical and managerial skills for IOS implementation and

developed a deeper understanding of the economic and organizational impacts of IOS. These skills and

knowledge are vital for successful implementation of new related technologies [24]. Thus, firms that have

prior experiences and knowledge with related technology such as EDI or barcode systems may have

developed more technical and managerial skills for deploying RFID technology than compared to those

firms without EDI or barcode experiences. Accordingly, we predict the following:

H5: Companies with strong absorptive capacity have a high level of RFID assimilation.

3.3 Predictions Related to Environmental Factors

In this section, we introduce environmental factors that can impact RFID assimilation processes.

In our research model, environmental factors include competition intensity, regulatory support as well as

market uncertainty. The reasons to include these factors are illustrated in the following part and based on

these, we propose three hypotheses.

3.3.1 Competition intensity

Competition intensity is “the degree that the company is affected by competitors in the market”

([27], p.24). Porter [38] indicated in his five-force competitive model that competitive pressure is an

important external driver to initiate the deployment of IOS among trading partners. Hence, competition

intensity likely plays a role in RFID assimilation in China.

According to Tsen [39], China’ economic reform towards a market economy promote more trade

and encourage more foreign direct investment (FDI) since its economic reforms in 1979. These

incremental trade and FDI contribute to China’s economic growth. As suggested by Fu [40], China has

become the second largest FDI recipient in the world—after the United States—and is the largest host

country among developing countries. These FDIs bring capital, knowledge, and new managerial skills to

China. Their participation increases competition in the domestic markets which makes challenges to

Chinese enterprises’ technology and managerial capabilities.

Moreover, China’s economy is export-oriented rather than domestic consumption oriented.

According to Wong [41], export-oriented economies are dependent on foreign demand. If there is any

slight recession in the international markets, this kind of economy will be influenced [42]. For example,

most manufacturing factories in Shenzhen are recently shut down and the production of these products is

outsourced to other countries due to the recession of international economy.

The export-oriented economy characteristics let Chinese companies face fierce competition from

local, nationwide and international market. To meet these challenges, they will try to adopt new

innovation technologies such as RFID to increase their competitive advantage. Therefore, we posit that

competition intensity will promote Chinese enterprise’ RFID assimilation process.

According to Bolloju and Turban [43], competition intensity is found to be positively associated

with the rate of adoption of new technological innovations. Benefits derived from first movers’ RFID

adoption might arouse decision makers’ awareness of this technology and make them consider adopting

it. Compared with traditional bar code systems, RFID can track the status of products in real time and

thus improve the inventory visibility as well as asset management. These improved efficiencies are

critical for companies to maintain their competitive advantage. Therefore, competition intensity is likely

to drive companies to initiate and adopt RFID technology. Accordingly, we predict the following

hypothesis:

H6: Competition intensity positively influences RFID assimilation in China.

3.3.2 Regulatory support

Regulatory support is a critical factor influencing innovation diffusion [17; 25]. Williamson [44]

suggest two ways which government could affect innovation diffusion. “One way is to take tax and other

measures to increase or decrease payoff, the other way is to alter the climate in which they are received”

[44]. Zhu et al. [17] investigate the assimilation of e-business and find that governments can encourage e-

business legislation by supportive regulations and policies.

These issues are particularly important in China. Chau et al. [8] investigate the assimilation

process of Internet technologies in China and find that Chinese companies have the highest concern for

the regulatory environment in which they and their business reside. In our research, since currently

Chinese government is proposing the twelfth five-year plan and government plans to invest in R&D of

the “Internet of Things” and cloud computing, and develop digital and virtual technologies. RFID

technology is the key enabler of the Internet of Things. Regulatory support from the government can form

an encouraging environment that will make decision makers aware of this technology and consider

adopting it in their enterprises. Therefore, we predict the following hypothesis:

H7: Government regulatory support influences assimilation of RFID technology in China

positively.

3.3.3 Environmental uncertainty

As indicated by previous research, firms facing environmental uncertainty have greater incentives

to adopt IOS (inter-organizational innovation) to improve information exchange and to reduce uncertainty

between trading partners. Sharma [45] also indicate that firms facing higher environmental uncertainty

will sense more opportunities, are proactive and innovate more than other firms. Furthermore, Bolloju and

Turban [43] indicate that market uncertainty forces organizations to adopt and implement new

technological innovations to stay competitive.

However, this situation might be different in China. As indicated by Chau et al. [8]’s

investigation of Internet assimilation status in China, market uncertainty has a negative influence on a

Chinese firm’s proactive and innovative strategies and behaviors. The reason for this phenomenon is that

Chinese firms are more risk averse than Western firms. Consequently, without external support from their

business partners in the industry, they are less likely to take initiative to adopt Internet technologies.

Moreover, adopting RFID technology requires considerable irreversible investment costs which

mean risk to Chinese enterprises. Thus they are less likely to run the risk and be pioneer to adopt RFID

technology. Compared to bar code system, the cost of an RFID tag is still much higher especially for

those low-profit product [9]. According to Lai and Hutchinson [7], the costs may decrease to US $ 0.20

only when the amount of demand can increase to 5 billion. This problem is even more serious for the low-

end product industry such as toys and clothes but not so serious in higher-end consumer products, such as

smart phones and computers.

Aside from these obvious costs, the bigger costs for RFID can be the cost incurred for the

necessary IT infrastructure (including servers, databases, middleware and applications). As Konsynski

and Smith [46] suggest, deployment and development is likely to add significant cost to the tight

implementation of RFID technology. Walker [47] also believes that optimizing processes, analyzing data,

and training workers would cost companies more than the purchase of RFID technology. Moreover, the

investment cost is irreversible due to the tight coupling between the technology and organization. And

whether the benefits derived from RFID can cover the irreversible costs is still uncertain to most of the

companies.

Regarding standards uncertainty, the Chinese government has decided not to use either EPC or

UID, but instead to develop their own RFID standard, which adds unique uncertainty to the Chinese

market. Additionally, according to Lai [7], there is still challenge about who is responsible for drafting the

RFID standards. Companies who are at assimilation stage might find it is hard to share information and

integrate with trading partners in the same industry if they use different RFID standards. These situations

will no doubt inhibit their RFID assimilation process. Taking these factors into consideration, we have the

following hypothesis:

H8. Environmental uncertainty influences RFID assimilation in China negatively

4 METHODOLOGY AND DATA COLLECTION

In this section, we introduce the research methodology and data collection method.

Operationalization of constructs is also introduced in this section. The measures of the constructs are

based on extant literature and are revised to fit the RFID context. Finally, we report on efforts to establish

the factorial validity and reliability of our measures.

4.1 Sample Frame

We use questionnaire surveys to collect data from various supply chain participants including

manufacturers, retailers and logistics providers. Data was collected through two non-profit organizations,

namely: GS1 HK, LSCM (Hong Kong R&D center for logistics and supply chain management enabling

technologies). The two non-profit organizations are dedicated to helping business community foster the

adoption of international supply chain standards, technologies and practices that form the backbone of

supply chain efficiency, visibility and collaboration. They helped us distribute the questionnaires to their

member companies. CEOs, IT managers or CIOs who are familiar with the deployment process of RFID

technology were mainly respondents. 900 questionnaires were distributed in total and we received 102

valid responses, achieving a response rate of 11%. The profile of sampled companies is listed in Table 4.1

and demographic characteristics of respondents are listed in Table 4.2.

Before surveying, we conducted three pilot interview studies to check if there are any content

validity problems with our questionnaires. To reduce the common-method bias, we collected data through

both online survey and offline paper surveys.

Table 4.1: Profiles of the sampled companies

Firm Characteristics N=102 %

Industry type

Manufacturing 79 82.3%

Retailing 23 17.7%

Firm size (No. of employees)

<10 10 9.8%

Between 10 and 50 34 33.3%

Between 50 and 100 21 20.6%

Between 100 and 500 13 12.7%

>500 24 23.5%

Table 4.2: Demographic characteristics of respondents

Respondent Characteristics N %

Gender

Female 13 12.7%

Male 89 87.3%

Age (in years)

18-25 12 11.8%

26-35 41 40.2%

36-45 29 28.4%

46-55 18 17.6%

56+ 2 2.0%

Working experience (in years)

<10 80 78.4%

10-20 19 18.6%

>20 3 3.0%

Job position

Director 47 46.1%

Manager 49 48.0%

Chief Information Officer 6 5.9%

4.2 Measures

Measurement items are developed based on a comprehensive review of the literature and expert

opinions and revised according to the RFID context. Seven-point Likert-like scales ranging from “(1)

strongly disagree” to (7) strongly agree” are used for all items. In Appendix 1, we list all the measures of

the construct and the sources of these measures.

5 DATA ANALYSIS

In this section, we introduce the final results of data analysis including the results of measurement

model, structural model and hypotheses testing. R2’s and the significance of the path coefficients are also

reported.

5.1 Justification of using structural equation modeling

Currently two SEM approaches are available for analysis: the covariance-based approach (such as

LISREL, EQS, and AMOS) and the partial least squares (PLS) approach (such as PLS-Graph or Smart-

PLS). The reason we used PLS was that a strong theoretical foundation is required for the covariance

based approach whereas the PLS approach does not require such a strong theoretical foundation [2; 48].

The reason for these differences is that the aim of covariance-based SEM approach is to determine

whether the covariance matrix of the theoretical model fits the empirical covariance matrix whereas the

aim of PLS is to predict and tries to maximize the explained variance of the manifest variables [49]. Our

study tries to explore factors that influence organizational assimilation of RFID within the TOE

framework and thus is exploratory in nature. Thus, the model does not have a strong enough theoretical

foundation to apply covariance-based SEM. We specifically used SmartPLS 2.0 [50] to analyze our

measurement model and conduct hypotheses testing.

5.2 Factorial Validity and Reliability

Before we tested our hypotheses with PLS, we first conducted extensive pre-analysis and data

validation according to the latest standards for three purposes [51-53]: (1) to establish the factorial

validity of the measures through convergent and discriminant validity; (2) to check for common-method

bias (despite careful design to prevent it); and (3) to establish strong reliabilities.

We first established factorial validity and reliability of our latent constructs. Factorial validity

includes convergent validity and discriminant validity. According to Fornell and Larcker [54], convergent

validity for a construct is evaluated by three criteria: (1) item loadings (λ) larger than 0.70; (2) composite

construct reliability larger than 0.80; (3) average variance extracted (AVE) larger than 0.50. Appendix 3

depicts the item loadings of each construct, which indicates all of the constructs have item loadings large

than 0.70. Moreover, Appendix 2 indicates that all constructs have composite reliability larger than 0.80

and AVE value larger than 0.50. Therefore, we can conclude that all of the constructs have high

convergent validity.

Discriminant validity is examined by comparing the relationship between shared variances among

the constructs and the value of AVEs (average variance extracted). If a construct’s AVE is larger than the

squared correlations with other constructs, we can conclude that it has discriminant validity. The

threshold value of AVE is .5. That is to say, if the AVE value is larger than .5, then we can say that the

construct meet discriminant validity. As summarized in Appendix 2 and Appendix 4, all of the constructs

have AVE scores larger than 0.50 and the squared root of AVE for each construct is much larger than the

construct’s correlation with every other construct [49], indicating that our model has sufficient

discriminant validity.

Reliability measures the degree to which items are free from random error, and therefore yield

consistent results. It is evaluated by composite reliability Cronbach’s α. If a construct has a composite

reliability above 0.80 and Cronbach’s α value larger than 0.70, we can conclude the construct has an

acceptable level of reliability [54]. Again, see Appendix 2.

5.3 Hypothesis Testing

Two steps were conducted to evaluate the research model: First, standardized path efficient and

statistical significance for the path significance is estimated. Bootstrapping analysis is conducted with 400

subsamples to estimate path coefficients and statistical significance. Second, coefficient of determination

(R2) for endogenous variables to assess the predictive power of the structural model is calculated.

Through these two steps, we can test the path significance and coefficient of each variable.

In figure 2, we list the path coefficient and significance level of each path. The results indicate

that IT infrastructure, managerial capability, absorptive capacity and environmental uncertainty play

significant influence on RFID assimilation in China. Among these significant paths, environmental

uncertainty negatively influences RFID assimilation while IT infrastructure, managerial capability and

absorptive capacity play positive influence on RFID assimilation. Managerial capability are significant at

the p=0.01 level and the other paths are significant at the p=0.05 level.

5.4 Non-response Bias

To test non-response bias, we performed a t-test to compare the demographic characteristics

between early and late respondent. Results indicate that there is no significant difference between the two

groups. Therefore, we conclude that there is no non-response bias in our survey.

5.5 Common Method Bias

Self-report surveys in which the same rater responds to items in single questionnaires at the same

point in time are likely to be susceptible to CMV (common method variance). It is one of main sources of

measurement error that can threaten the validity of conclusions of relationships between measures. To

detect or assess the common method variance, we first employed the widely used method of the

Harmon’s single-factor test. According to Harmon’s single-factor test, a common method is assumed to

exist if (1) a single factor emerges from non-rotated factor solutions; (2) a first factor explains the

majority of the variance in the variables. We used principal component analysis as extraction method. The

results indicate only one factor is present and the most covariance explained by one factor is 23.48%.

However, this test is criticized by Podsakoff et al. [55] as not rigorous enough, and proposed the

method of using a single-common-method-factor approach. Their approach was later implemented for

PLS by Liang et al. [56], and was considered a promising approach until it was debunked as invalid and

ineffectual by Chin et al. [57]. Hence, to further augment our approach of assessing CMV, we used a

more useful and simple approach advocated by Pavlou et al. [58]. They note that all one has to do is

simply examine a correlation matrix of the constructs and to determine if any of the correlations are above

0.90, which is evidence that CMV may exist. Their fundamental reasoning is that if CMV exists in any

data set there will be extremely high correlations amongst the self-reported constructs. That is, if there are

no high correlations, then the threat of any meaningful CMV is remote. Examining our measurement

model statistics, we do not have inflated correlations, there is no reason to believe CMV is negatively

impacting our data.

Thus, we can conclude that the likelihood of common method bias is low in our research.

6.0 DISCUSSION

In this section, we introduce the final results of our research model. We also explain the non-

supported hypotheses based on existing literature. Implications for research and theory are illustrated

followed by the implications for practice and industry. Limitations and future research opportunities for

scholars are also introduced at the end of this section.

6.1 Summary of Final Results

We first hypothesize that relative advantage plays a significant positive influence on RFID

assimilation process in China. However, the results indicate that the influence is not significant (H1

rejected). According to Seymour et al. [59], most organizations invest a new technology with the short-

term view to obtain a competitive advantage over competitors. However, the relative advantage might be

offset by the high costs and implementation complexity of RFID technology and cannot be achieved

quickly in a short time. Indeed, some research investigating innovation adoption also supported the

similar findings. According to Tornatzky and Klein’s [19] meta-analysis of innovation adoption, not all of

the studies revealed that relative advantage can significantly influence innovation adoption. Wamba et al.

[60]’s research find firms were all interested in RFID’s benefits including greater data accuracy, track and

trace capabilities and improved inventory management, no matter whether they had adopted it or not.

Another reason may be that RFID indeed play important roles in the adoption stage, during which

decision makers should make either purchasing or non-purchasing decisions based on the relative

advantage of this technology. But after adoption, relative advantage can play little influence on the

adaptation and assimilation process.

Early assimilation

stage

Technology context

Relative

advantage

Complexity

Managerial

capability

Absorptive

capacity

IT

infrastructure

Regulatory

support

Competition

intensity

Environmental

uncertainty

Environmental context

Organizational context

H1(+0.011)

H2(+0.099)

H3(+0.223*)

H4(+0.322**)

H5(+0.220*)

H6(+0.055)

H8(-0.258**)

H7(-0.130)

RFID

assimilation

Figure 2: Path coefficient and R square of each assimilation stage

In Hypothesis 2, we posit that complexity plays significant negative influence on the RFID

assimilation. However, the empirical result does not support our original hypothesis. This may be because

technology complexity and implementation complexity are different concepts [59]. In Seymour et al.’s

qualitative study of RFID adoption in South Africa, three organizations reported that it is complexity of

the technology implementation rather than the technology itself (configuring business rules) inhibits their

RFID adoption. Thus, complexity that refers to the technology complexity in our research does not play

significant influence on the assimilation process.

Regarding Hypothesis 3, we hypothesized that IT infrastructure has a significant positive

influence on RFID assimilation. The empirical results support this hypothesis. That is to say, firms with

mature and sophisticated IT infrastructure can assimilate RFID to a higher level than those with immature

IT infrastructure. RFID can achieve its greatest benefits only through integrating with other backend

systems such as enterprise resource planning (ERP), customer relationship management (CRM), and

decision support systems (DSS) and sharing data and information with them [7]. Thus, physical IT assets

play important roles in the integration and assimilation process. Companies with sophisticated IT

infrastructure have mature backend enterprise applications with which RFID can be integrated with.

Moreover, when assimilating RFID technology, companies might meet knowledge barriers and obstacles

that require internal IT staff to solve. Companies with mature IT infrastructure also have skilled IT staff to

overcome the knowledge barriers during the implementation process. Therefore, IT infrastructure plays

significant positive roles on the assimilation process of RFID technology.

In Hypothesis 4, we posit that managerial capability positively influence RFID assimilation

process in China. The results supported our hypothesis. Because RFID is a radical innovation that is

resource intensive and requires substantial changes to existing work processes and organizational

structure [2] organizations that have advanced managerial capabilities can overcome the managerial

obstacles successfully than those that do not have enough managerial capabilities.

Regarding Hypothesis 5, absorptive capacity is found to significantly influence RFID

assimilation. Again, absorptive capacity refers to “a firm’s ability to recognize the value of new

information, assimilate it and apply it to commercial ends” ([24], p.128). It is regarded as a knowledge

base, especially the extent of prior knowledge the firm possess [36]. Thus, firms that have strong

absorptive capacity with prior experiences of using related knowledge have great capability to recognize

the value of RFID technology and try to assimilate it and apply it to commercial ends.

In Hypothesis 6, we posit that competition intensity positively influences RFID assimilation

process while it is not supported by the empirical results. A possible explanation for this finding could be

that fierce competition drives firms to leap rapidly from one technology to another [61]. In such

situations, it is difficult for firms to undergo a gradual, careful, and sustained learning-by-doing process to

assimilate existing technologies [20].

In Hypothesis 7, we proposed that regulatory support has a positive influence on the RFID

assimilation process for Chinese firms, with was not statistically significant (H7 not supported). As

indicated by David [62], normalization and standardization procedures brought by regulations can reduce

uncertainty and will create network effects. These network effects can make companies aware of the new

innovation and motivate them to adopt it. However, these companies’ enthusiasm will wane over time

when they meet obstacles during the further assimilation process.

The different influence of regulatory support across stage can also be found in Zhu and

Kraemer’s [25] investigation of E-business post-adoption. They indicate that the influence of supportive

business laws is particularly important at early stages of e-business development than at later assimilation

stage of e-business in an economy. Thus, it might be the case that regulatory support for RFID is more

important for adoption rather than for assimilation.

Regarding Hypothesis 8, we proposed that environmental uncertainty negatively influences RFID

assimilation. Empirical results supported this hypothesis. As we mentioned in the previous chapter, there

are two major uncertainties with RFID assimilation: irreversible investment costs and uncertain standards.

Thus, if companies that have already entered into assimilation stages want to cancel or change their RFID

implementation, they might undergo the risk of incurring irreversible costs. Moreover, companies who are

at assimilation stage might find it is hard to share information and integrate with trading partners in the

same industry since they use different RFID standards. These situations will no doubt inhibit their RFID

assimilation process.

In conclusion, the empirical results indicate that innovation characteristics such as relative

advantage and complexity do not play significant roles on RFID assimilation process. All factors within

the organizational context play significant positive influence on RFID assimilation. Under the

environmental category, environmental uncertainty plays significant negative influence on China’s RFID

assimilation.

6.2 Theoretical Contributions and Practical Implications

While RFID has been adopted by more and more Chinese companies in recent years, many of

them have failed to achieve deep usage beyond initial adoption [4]. However, innovation can only

generate significant business value when it is integrated into the corporate value chain [63]. Moreover,

most IS innovation research just focus on the one-shot adoption decisions, and little is known about the

post-adoption stage. As indicated by Fichman [35] and Zhu et al. [17], post-adoption stages of

assimilation are especially worthy of a focused study. Thus, this research contributes to the post-adoption

research which has been studied to a much less extent than the one-shot adoption research.

Second, different cultural contexts and environmental settings may generate different results. We

conducted this research in a new context, i.e., Chinese manufacturing industries. Results indicate the same

antecedents can have reverse influences on RFID assimilation. For example, as indicated by our research,

environmental uncertainty plays significant negative roles on Chinese companies’ RFID assimilation

because of these companies’ risk-averse characteristics. This finding is consistent with Chau et al. [8]’s

research of internet technologies assimilation in China. They revealed that “Chinese firms are risk averse

and are less likely to be bellwethers for Internet technology.” [8] However, this research finding is also

contrary to the popular argument that in Western countries, environmental uncertainty, rather than

maturity, positively influences a firm’s proactive and innovative strategies and behaviors. Since the

Chinese government still has maintained powerful political influence and control in the transition process,

regulatory environment has also become one of these companies’ biggest concerns. However, previous

research findings based on developed economy cannot empirically support developing countries’

assimilation practices. Thus, it is necessary for us to investigate RFID assimilation in transitional

economy such as China.

Third, this research investigates one significant determinants of RFID assimilation (absorptive

capacity), which were seldom investigated in prior RFID adoption/assimilation literature. Based on

existing literature, absorptive capacity is an important construct to investigate innovation adoption and

assimilations, especially disruptive technologies such as RFID technology.

From empirical implications perspective, managers can promote their RFID assimilation level

through improving their managerial capability, organization’s IT infrastructure and absorptive capacity.

As indicated by the CEO of LEO Company in Hong Kong, the biggest challenge faced by RFID

implementation is business process reengineering. This emphasizes the need of improving IT managerial

skills for the efficient usage and assimilation of innovations. This kind of skills can be obtained from

RFID vendors whose interests in expanding markets are served by such transfer in China and other

developing countries [64]. Another way is to work with foreign multinational corporations who can

benefit from transferring such skills either as a means of extending their markets or upgrading the

capabilities of local suppliers in developing countries [65].

As illustrated, IT infrastructure contains three components: (1) physical assets such as wireless

network, enterprise applications including ERP (enterprise resources planning), MRP (material resource

planning), DSS (decision support systems), and so on; (2) human IT resources including technical and

management skills; (3) IT-enabled intangibles such as customer orientation, knowledge asset and synergy.

Thus, managers can improve their IT infrastructure through improving related enterprise

applications and training their IT staffs on both RFID related technical skills and management skills. They

should also make their business strategy customer-oriented, and try to embed the knowledge, skills and

experiences of the employees into its business processes, policies and information repositories to better

assimilate RFID technology. Moreover, Leung et al. [66] evaluate the use of IT by the third party logistics

in South East Asia (including Singapore and Malaysia) and indicate that the barriers of their IT adoption

is lack of software integration and logistics professionals. Accordingly, IT infrastructure can also be

improved through integrating various enterprises applications and training IT staffs and equipping them

with strong technical and management skills.

As indicated by Fu [40], lack of absorptive capacity and complementary assets is a bottleneck that

inhibits the innovation assimilation. This study provides important implications for firms in developing

countries that are carrying out knowledge transfer. According to Lin et al. [67], developing countries lack

human resources and financial resources to become the R&D centers which means technology transfer is

a key issue for these countries. To effectively transfer external technology, firms should improve their

interaction mechanism including both intra-and inter-organizational interactions to promote learning from

outside environment. Communications between employees from different divisions and background

should be encouraged to improve the intra-organizational interactions. Moreover, management of R&D

activities, and the construction of information collection mechanisms inside and outside organizations are

also essential.

Regarding the uncertain standards, EPCglobal only specifies an RFID standard at layer one and layer

two of OSI model and leave the top layers to be defined by industry themselves [68]. Thus, developing

countries may face difficulties to harmonize their standards at application and top layers. To deal with this

problem, government can make some legislation to confirm the top layer RFID standards to harmonize it

with that of other countries.

At the company level, managers should also predict the uncertainty caused by the high irreversible

investment costs and unconfirmed standards during the assimilation process. They should evaluate their

organization’s capabilities to accept sunk costs brought by the failure of RFID project and make rationale

adoption decisions. Managers should also have knowledge of the RFID standards that their trading

partners use and try to use the same standards to avoid standard conflict during information and data

sharing process. Only by this can they share information and data smoothly with their trading partners and

assimilate RFID technology in a high level.

6.3 Limitations and Future Research Opportunities

Because RFID technology is still at its infancy and is not widely used in China, we were not able to

achieve a large sample size. In total, we had 102 data points for the assimilation. Therefore, it is possible

that some of the insignificant paths were caused by the small sample size, rather than the incorrect

hypothesis. As more Chinese companies begin to use RFID technology and assimilate it into their

organizations, future research involving larger sample sizes can be conducted.

When collecting data, we used a single respondent from each target company without collecting

more responses from other informants in the same organization. According to Ranganathan et al. [69],

random measurement error can be increased by relying on one respondent to make complicated social

judgments about organizational characteristics. However, due to the costs and possibility of lower

response rate, we did not collect multiple respondents from one organization. Future research can mitigate

this problem through collecting data from multiple respondents per company to reduce the measurement

errors. Further research could collect longitudinal data from multiple respondents to investigate the causal

relationships between predictive variables and dependent variables.

Moreover, because RFID is an IOS (inter-organizational information systems) innovation that

requires cross-organizational cooperation to share information and business data, inter-organizational

factors become more important when RFID is more deeply assimilated. Importantly, our study did not

generally involve organizations that had assimilated RFID this deeply. Such assimilation should be the

ultimate goal in automating any supply chain with RFID. Future research should thus study the influence

of inter-organizational factors such as supply chain integration and collaboration on the inter-

organizational innovation assimilation processes.

Finally, we did not include top management support in our model. Other research has shown this

to influence technology assimilation. Hence, the next version of this model and research should further

consider this construct. Importantly, other related organizational context variables may also be important,

such as organizational commitment, or such recent findings on the importance of extra-role behaviors

performed by IT employees [e.g., 70], all of which could have significant influence on how well RFID

assimilation occurs. Key differences in assimilation approaches may also be seen in different industries

and national cultures, and should also be considered because key differences in culture have been

exhibited in multiple IT use and deployment contexts [e.g., 71; 72-74]

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http://dx.doi.org/10.1287/isre.2015.0569)

Appendix 1 Construct Measurement

Construct Source items Measurement items Source

Relative

advantage

The same as right column RFID may increase cost efficiency, e.g. through improved

asset visibility that reduces stock loss and saves human assets.

RFID may improve inventory replenishment, e.g. through

better tracking of products.

RFID may consolidate competitive marketing strategy, e.g.

through gaining the capability to formulate more competitive

marketing strategy and increase customer service.

RFID may increase product security, e.g., through increasing

the accuracy of the information on the movements of the

physical goods that are visibly recorded.

Wang [3]

Complexity The same as right column A lack of customized solutions for RFID system and their

incompatibility with existing IT systems;

Little or no harmonization of interfaces due to lack of unified

standards for RFID;

Large investment or maintenance costs of establishing RFID

and related IS;

Poor tracking reliability due to poor reception of radio waves

absorbed or distorted by moisture or metals;

Reduced business security because company supply chain

flows can be tracked by monitoring the RFID equipment;

Wang [3]

Managerial

capability

The same as right column The capability to make organizational changes necessary to

assimilate RFID;

The capability of integrate RFID into the overall strategy and

business process;

The capability of acquiring expertise for RFID

implementation.

Chatterjee

[4]

Barua [75]

IT

infrastructure Resources comprising the physical IT

infrastructure components;

Human IT resources comprising the technical

We have necessary tangible resources comprising the physical

IT infrastructure components for RFID such as wireless

internet, intranet, enterprise applications including

Grant [30]


and managerial IT skills;

The intangible IT-enable resources such as

knowledge-assets, customer orientation, and

synergy.

ERP,MRP,DSS, etc.;

We have the human IT resources comprising the technical and

managerial IT skills for RFID;

We can track and predict changing customer preferences in the

volatile markets (customer orientation);

We have skills and experience of our employees embedded in

the process, policies and information repositories (knowledge

assets).

We can share resources and capabilities across organizational

divisions about RFID (Synergy).

Absorptive

capacity

The same as right column Acquisition:

The search for relevant information concerning our industry is

every-day business in our company;

Our management motivates the employees to use information

sources within our industry;

Our management expects that the employees deal with

information beyond our industry.

Assimilation:

In our company ideas and concepts are communicated cross-

departmental.

Our management emphasizes cross-departmental support to

solve problems;

In our company there is a quick information flow, e.g., if a

business unit obtains important information it communicates

this information promptly to all other business units or

departments;

Our management demands periodical cross-departmental

meeting to interchange new developments, problems, and

achievements;

Flatten

[76]


Exploitation:

Our management supports the development of prototypes;

Our company regularly reconsider technologies and adapts

them accordant to new knowledge;

Our company has the ability to work more effective by

adopting new technologies.

Competition

intensity

The degree of rivalry to which a firm is affected by

competitors in local markets, nationwide and

worldwide. [77]

The degree that our company is affected by competitors in the

local market;

The degree that our company is affected by competitors

nationwide;

The degree that our company is affected by competitors

worldwide.

Porter [77]

Market

uncertainty

The market for their company’s products;

The competition for their company’s products;

The demand of their major customers;

The degree of loyalty of their major customers;

The frequency of price-cutting in their industry.

The investment cost of RFID is irreversible.

The evolution of RFID technology is unpredictable (e.g.

standards haven’t been confirmed).

The net payoffs of using RFID are still uncertain.

Fichman

[33]

Lai [7]

Regulatory

support The extent that business laws support e-business

transactions among firms;

The legal protection of consumers’ purchases

on the Internet;

The degree to which the use of e-business at

firms was driven by incentives provided by the

government and required by government

procurement.

The extent that business laws support RFID technology;

The extent that government provides protection of RFID use;

The degree to which the use of RFID is driven by incentives

provided by the government and is required by government

procurement.

Zhu [17]

Assimilation According to Chau and Tam’s operationalization of

open systems adoption, organizations are regarded as

adopters if they meet three criteria:

(1) an open system migration plan had been

developed;

(2) the plan had already been endorsed by top

management; (3) a financial budget and a migration

The RFID system adoption plan has already been

endorsed by top management;

An RFID financial budget and an adoption schedule have

been approved.

RFID related organizational procedures and processes

have been revised and developed.


schedule had been approved.

According to Premkumar et al. [78], adaptation stage

is the one where the organization learns and adapts to

the technology by trying it out in its first application.

Acceptance means organizational members are

committed to IT application usage and the

organizational structure and process changes brought

by the IT technology [79].

According to Zhu et al.[17], routinization is defined

as the stage in which e-business is widely used as an

integral part in a firm’s value chain activities.

Organizational members are trained both in the new

procedures and in the corresponding RFID application(s)

[79]

Organizational members are willing to accept the changes

of organizational structures and procedures caused by

RFID usage [79]

Usage of RFID and its applications is encouraged by

employees in related department as a normal work. [79].

Appendix 2 Composite reliability, Cronbach’s alpha and AVE scores of major constructs

Construct Composite reliability AVE Cronbach’s alpha

Relative advantage 0.884 0.719 0.809

Complexity 0.835 0.631 0.769

IT infrastructure 0.897 0.745 0.828

Managerial capability 0.939 0.885 0.874

Absorptive capacity 0.797 0.652 0.780

Competition intensity 0.823 0.632 0.776

Regulatory support 0.940 0.886 0.873

Environment uncertainty 0.796 0.674 0.903

Assimilation 0.946 0.747 0.931

Appendix 3 Loadings and Cross-loadings of Main Construct

Construct Absorptive

capacity

Assimilation Competition

intensity

Complexity Environmental

uncertainty

IT infra-

structure

Regulatory

support

Managerial

capability

Relative

advantage

AC 0.636 0.183 0.180 -0.151 0.012 0.231 0.128 0.318 0.176

AS 0.811 0.288 0.218 -0.442 -0.228 0.294 0.139 0.284 0.318

EX 0.805 0.330 0.025 -0.342 -0.136 0.542 0.185 0.208 0.169

Assimilation_1 0.296 0.894 0.125 -0.135 -0.320 0.434 0.468 0.044 0.239

Assimilation_2 0.283 0.885 0.129 -0.105 -0.303 0.409 0.466 -0.030 0.248

Assimilation_3 0.277 0.926 0.146 -0.132 -0.398 0.419 0.488 -0.081 0.256

Assimilation_4 0.335 0.861 0.069 -0.199 -0.340 0.400 0.356 -0.094 0.137

Assimilation_5 0.412 0.839 0.200 -0.286 -0.407 0.464 0.453 0.064 0.285

Assimilation_6 0.291 0.772 0.260 -0.282 -0.365 0.305 0.463 -0.084 0.184

CI_1 -0.296 0.286 0.877 0.346 0.148 -0.163 0.237 -0.326 -0.222

CI_2 0.134 0.146 0.916 0.011 -0.147 0.070 0.087 0.039 0.193

CI_3 0.177 0.186 0.949 -0.069 -0.129 0.080 0.093 -0.059 0.259

CO_1 -0.237 -0.107 0.066 0.734 0.174 -0.209 -0.079 -0.040 0.002

CO_2 -0.261 -0.073 0.008 0.725 0.120 -0.257 -0.142 0.041 -0.140

Construct Absorptive

capacity

Assimilation Competition

intensity

Complexity Environmental

uncertainty

IT infra-

structure

Regulatory

support

Managerial

capability

Relative

advantage

CO_3 -0.446 -0.249 -0.082 0.909 0.437 -0.254 -0.194 -0.048 -0.315

UC1 -0.015 0.086 0.296 0.170 0.873 -0.151 -0.191 -0.354 -0.070

UC2 0.120 -0.077 -0.034 0.226 0.606 -0.112 -0.258 0.046 -0.189

UC3 -0.214 -0.439 -0.154 0.378 0.990 -0.231 -0.253 0.033 -0.284

IT_1 0.403 0.414 0.112 -0.313 -0.219 0.834 0.306 0.268 0.222

IT_2 0.434 0.405 -0.002 -0.197 -0.222 0.864 0.338 0.166 0.235

IT_3 0.449 0.399 0.099 -0.241 -0.148 0.890 0.399 0.136 0.242

MC_1 0.091 0.380 0.062 -0.156 -0.206 0.299 0.917 -0.111 0.196

MC_2 0.257 0.568 0.111 -0.192 -0.291 0.435 0.964 0.003 0.292

RA1 0.293 0.275 0.254 -0.271 -0.261 0.256 0.265 0.155 0.898

RA2 0.222 0.212 0.134 -0.170 -0.253 0.217 0.190 0.161 0.872

RA3 0.213 0.157 0.241 -0.166 -0.218 0.209 0.225 0.103 0.767

RS_1 0.287 -0.034 0.010 0.037 0.073 0.184 -0.033 0.952 0.115

RS_2 0.358 -0.028 -0.047 -0.121 -0.010 0.237 -0.054 0.930 0.212

Appendix 4 Measurement model statistics

Construct

Means

SD (1) (2) (3) (4) (5) (6) (7) (8)

Absorptive capacity (1) 5.28 0.78

Assimilation (2) 3.37 1.37 0.366

Competition intensity (3) 4.15 1.65 0.173 0.187

Complexity (4) 4.53 1.48 -0.435 -0.220 -0.046

Environmental uncertainty(5) 4.98 1.38 -0.176 -0.413 -0.160 0.381

IT infrastructure (6) 4.62 1.53 0.497 0.471 0.084 -0.291 -0.228

Managerial capability (7) 4.50 1.31 0.202 0.521 0.102 -0.188 -0.272 0.402

Regulatory support (8) 4.53 1.12 0.338 -0.033 -0.016 -0.037 0.038 0.221 -0.045

Relative advantage (9) 5.08 1.43 0.292 0.263 0.256 -0.247 -0.289 0.270 0.269 0.168

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