College of Business AdministrationUniversity of Rhode Island 2013

2013 No. 5

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exchange of ideas. Inclusion here does notpreclude publication elsewhere.

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Office of the DeanCollege of Business AdministrationBallentine Hall7 Lippitt RoadKingston, RI 02881401-874-2337www.cba.uri.edu

Qing Cao, Dara G. Schniederjans, Jason Triche, and Marc J. Schniederjans

A Synthesis of Resource-Based View and Social Capital Theory Business Strategy, Cloud Computing, and Supply Chain Management:

Business Strategy, Cloud Computing, and Supply Chain Management: A Synthesis of Resource-Based View and Social Capital Theory

Qing Caoa

Dara G. Schniederjans*b

Jason Trichea

Marc J. Schniederjansc

a Texas Tech University, 310 Business Administration Building, P.O. Box 42101, United States Lubbock, TX 79409, qing.cao@ttu.edu,

bUniversity of Rhode Island, 226 Ballentine Hall, 7 Lippitt Road, United States, Kingston, RI 02881, Schniederjans@mail.uri.edu

c University of Nebraska-Lincoln, College of Business Administration, P.O. Box 880405, United States Lincoln, NE 68588,

mschniederjans1@unl.edu

*Corresponding Author

Abstract

Despite having various benefits associated with greater information flow in the supply chain, cloud computing technology has limited research in operations or supply chain management literature. Using a multi-method research design we conducted interviews with six individuals from four different companies in the United States, as well as conducted a survey to analyze and empirically assess our results. Our analysis found business strategy impacts the way companies use cloud computing technology and moderates how cloud computing use impacts information sharing. Additionally, we found cloud computing technology is positively associated with information sharing in the supply chain, which ultimately impacts supply chain performance. Trust is also shown to moderate the relationship between cloud computing use and information sharing among supply chain partners. This study is the first to develop a conceptual model that identifies the impact of business strategy on cloud computing use and how cloud computing impacts information sharing with trust and business strategy as a moderator.

Keywords: Cloud Computing, Information Sharing, Supply Chain Performance, Business Strategy

1. Introduction

The ever increasing geographical dispersion in supply chain networks adds to their complexity (Stock et al., 2000). To help effectively manage supply chain complexity, many firms have chosen a strategy of enhanced information technology for the purpose of increasing information flow and in turn, for enhancing their competitive advantage (Ketchen, Jr. & Hult, 2007). Beyond increasing information flow, there is also a need for supply chain partners to be willing to share information. Research has shown that integrating supply chain practice with efficient information sharing becomes crucial for improving supply chain performance (Zhou & Benton, Jr., 2007). Moreover, Thomas et al. (2011) and others have suggested research on new information technology and how this impacts information sharing between supply chain organizations is needed in the supply chain literature.

As novel information technologies emerge, there is a need to explore their potential in improving supply chain performance. One state of the art information technology currently being adopted by a variety of organizations is cloud computing. Cloud computing can be generally defined as a massively scalable computing power that offers software, infrastructure and platforms on demand using a pay-as-you-go basis through the internet (Foster et al., 2008; Rochwerger et al., 2009). While the open access flow of information to cloud computing technology comes with security concerns, it has been shown to have various benefits for information flow, including cost reduction, massively scalable service and on demand access (Rochwerger et al., 2009). Despite these information flow benefits, very little empirical research has been undertaken to examine cloud computing’s impact on information sharing in a supply chain context. Moreover, to the best of our knowledge, no study has assessed the impact of inter-organizational trust on the relationship between cloud computing use and information sharing. Further, while past research has suggested logistics strategies are essential elements of business strategy (La Londe and Masters, 1994; Chow et al., 1995; Stock et al., 1998; Stank and Traichal, 1998; Stock et al., 2000), little empirical research has identified the impact of business strategy on how cloud computing impacts information flow, and no research has identified business strategy’s impact directly on cloud computing use.

In this paper, we attempt to address the gap in the literature by using a multi- method research design using both a multiple-case study approach involving four companies and survey analysis. This study uses resource-based view (RBV), as well as social capital theory, to examine the relationships among business strategy cloud computing use, information sharing, trust and supply chain performance. We analyze qualitative data from four firms and six individuals, including a Senior Manager, Co-Owner, Vice President of International Marketing, Director of Supply Chain Management, Senior Vice President of Marketing, and Logistics and Director of

Information Technology. Our findings indicate relationships between each of the constructs that support a proposed theoretical framework. This framework addresses questions including:

1. How does business strategy impact cloud computing technology and how does its impact the relationship between cloud computing and information sharing?

2. How does cloud computing impact information sharing? 3. How does trust moderate the relationship between cloud computing and information sharing? 4. How does information sharing impact supply chain performance?

This study finds five relationships: first, the goals of an organization directly impact how cloud computing technology is used and how cloud computing impacts information sharing; next, cloud computing use is positively associated with information sharing; also, trust moderates the relationship between cloud computing use and information sharing; finally, information sharing is positively associated with supply chain performance.

This study provides a foundation for not only researchers, but also is generalizable to wider business contexts. Cloud computing use can greatly impact how information sharing is used and is of great importance to overall strategies and plans. This paper provides a practical foundation for both researchers and supply chain professionals regarding how top executives and managers at companies utilize cloud computing and how trust and business strategy maximizes goals for information sharing and ultimately impacts supply chain performance.

In the following sections we first discuss theory and model development where we analyze the relationships between our constructs and their underlying theoretical foundations related to resource-based view and social capital theory. Next, we identify past research on each construct and their potential relationships. We then discuss case study methodology, as well as our data collection. After this, we describe our survey and assess the results of our model empirically. Finally, we summarize our findings and look at the potential limitations of the study.

2. Theory/Model Development

Cloud computing technology is in its infancy in operations and supply chain literature. Given the recent emergence of cloud computing technology, this study uses theoretical foundations, including resource-based view and social capital theory, to build a conceptual model. Both resource-based view and social capital theory can provide a strong theoretical background to delineate the

relationships between resources, including cloud computing technology and the relational characteristics of a firm, as well as information sharing, trust and the impact of these constructs on supply chain performance.

In order to develop the foundation for our paper, we will synthesize concepts such as Miles & Snow (1978) typology on strategic profiles, resource-based view and social capital theory. To begin, we will present an overview of each theory. We will then present our model based on these theories, which we then will further elaborate in the propositions section.

2.1. Resource-Based View (RBV)

Past supply chain management research suggests a connection between information technology and effective supply chain management collaboration (Clemons et al., 1993; Lee & Whang, 2000; Sahin & Robinson, 2002; Rosenthal et al., 2010; Leidner & Jarvenpaa, 1995; Petersen & Ragatz, 2005; Xu & Beamon, 2006). This relationship has a strong theoretical background in resource-based view (Bharadwaj, 2000; Mata et al., 1995). Resource-based view suggests that firms compete using unique corporate resources that are valuable, rare, difficult to imitate and non-substitutable by other resources (Barney, 1991; Conner, 1991, Schulze, 1992). A firm can consist of productive resources that can be used for competitive advantage (Penrose, 1959; Rubin, 1973; Wernerfelt, 1984). The rarer the resources are the greater the advantage for the firm (Dierickx & Cool, 1989). However, while resources are important, it is more critical how the firm uses them to maximize its competitive potential (Eisenhardt & Martin, 2000).

When assessing how information technology (IT) can be deployed in supply chains to achieve performance, Fawcett et al. (2011) used Newbert’s (2007) three RBV perspectives. The resource-heterogeneity perspective looks at resources and capabilities and their relationships to sustainable competitive advantage, which is connected to sustained performance (Fawcett et al., 2011). The organizing perspective suggests that in order to achieve competitive advantage, valuable resources should be properly organized and leveraged (Fawcett et al., 2011). Finally, the dynamic-capabilities perspective suggests a need to alter resources into a capability in order to achieve superior performance in a changing environment (Fawcett et al., 2011).

In this study we consider cloud computing technology using the organizing perspective. Cloud computing can be a valuable, rare and difficult to imitate resource if the firm utilizes it based on its own business strategy in that it surpasses other information technologies commonly used in a supply chain context, such as web based electronic data interchange (EDI). EDI requires common platforms to transfer data unlike cloud computing which improves flexibility in both location and payment arrangements (Monczka et al., 1998). However, it needs to be adequately aligned with business strategy in order to provide foundations for greater information sharing in supply chains, which previous literature suggests positively impacts supply chain performance (Lee et al., 1997a,b).

2.2. Social Capital Theory

Social capital theory promulgates the benefits that relationships between entities can generate. These can be intangible and tangible benefits in a social, psychological, emotional or economic sense, both in the short-term and long-term (Lin, 1986; Lin, 1999; Lin, 2000). Narayan & Cassidy (2001) define seven dimensions of social capital. The first dimension consists of group characteristics, which involve number of memberships, participation in decision making, contribution of money, frequency of participation, etc. The second dimension is comprised of generalized norms, which refer to the helpfulness, trustworthiness and fairness of others. Third is togetherness, which represents how well people get along. Fourth is the everyday sociability of individuals. Fifth is neighborhood connections established among individuals or organizations. Sixth is volunteerism, which is kindness without the need for reciprocity. Finally, there is trust that exists among individuals or organizations.

Social capital theory can help to explain the importance of social capital in the realm of supply chain management. Two social aspects of supply chains are the focused in this study: information sharing and inter-organizational trust. Given the recency of cloud computing, security of information appears to be a main concern for potential organization adopters (Rochwerger et al., 2009). Trust is vital, for organizations to build social capital and improve the relationship for both efficient and effective information flow (Cai et al., 2010). Further greater information sharing between organizations perpetuates social capital, ultimately reducing problems in the supply chain including has been shown to improve supply chain performance (Heikkila, 2002).

Based on resource-based view and social capital theory, we propose a theoretical model as depicted in Figure 1.

3. Literature Review and Hypotheses

3.1. Business Strategy and Cloud Computing Use

Walker & Ruekert (1987) differentiated five strategic types based on Miles & Snow’s (1978) work that was rooted in strategic choice theory. These include defensiveness (emphasis on cost reduction and efficiency seeking methods), risk aversion (risk in resource allocation decisions), aggressiveness (stance on improving market positions at a faster rate than competitors), proactiveness (continuous search for market opportunities), analysis (problem solving posture), and futurity (long-term vs. short-term considerations) (Venkatraman, 1989). In this study, we analyze the relationship between business strategy using these five dimensions and its impact on cloud computing use as well as its moderating impact on the relationship between cloud computing use and information sharing. . Previous literature has found a link between business strategy and information technology use leading to greater performance. For example, Tracey et al. (1999) suggest organizations participating in strategy formulation and investing in advanced

Business Strategy

Cloud Computing Use

Information Sharing Supply Chain Performance

Trust

Figure 1. Research model

manufacturing technology will demonstrate better performance than those that do not. Kotha & Swamidass (2000) found that fits between strategy, information exchange and planning technology are associated with greater firm performance.

As stated previously, the organizing perspective of resource-based view suggests that valuable resources should be properly leveraged in order to sustain competitive advantage (Fawcett et al., 2011). Cloud computing technology can be a valuable resource if a company knows how and in what way to use it in order to maximize its value. Past literature suggests that IT applications have the potential to create differentiation across activities that will constitute a firm’s value chain (Floyd & Wooldridge, 1990). Firms will tend to align their IT resources in order to position themselves favorably relative to rivals, suppliers, etc. (Floyd & Wooldridge, 1990). While alignment between a firm’s strategy and its IT use can lead to enhanced performance, misalignment has been shown to reduce performance. Some studies have found that the misalignment between strategy and IT use caused IT to become almost a competitive burden (e.g. Warner, 1987; Vitale et al., 1986). Overall, alignment between strategy and IT use can lead to competitive advantage, avoid strategic disadvantage and enhance competitive position (Floyd & Wooldridge, 1990).

Cloud computing can be used as a resource to maximize results from current business strategies if it is valuable, rare, difficult to imitate and non-substitutable according to resource based view of a firm. Previous literature distinguishes cloud computing from other commonly used information technologies in its flexibility with analyzing a large amount of data on different platforms (Marston et al., 2011). This is dissimilar to web-based EDI which often requires common platforms (i.e. common ERP systems) (Monczka et al., 2011). Further, cloud computing has massively scalable services including software, platforms and infrastructure as well as payment arrangements (i.e. one time flat fee, pay-per-use and hybrid approach) that allows companies to scale their services based on their business strategy goals and competitive priorities (Marston et al., 2011; Benlian & Hess, 2011; Iyer & Henderson, 2010). This not only allows organizations to scale services according to their needs but also perpetuates social capital among their supply chain partners by focusing on their needs as well as their external partners. However, security concerns are rampant with the sharing of sensitive information over the cloud (Rochwerger et al., 2009). To mitigate these concerns, cloud computing allows organizations to choose between a public, private or hybrid cloud to secure information flow between partners allowing ease of access to information but reducing security concerns among partners (Marston et al., 2011). These massively scalable services allow business strategy to impact not only the use of cloud computing, but also allow a company to align their use with strategic initiatives in order to optimize information flow between supply chain partners.

Based on this past literature we formulate the following hypotheses

H1. Business strategy positively influences cloud computing use

H2. Business strategy moderates the positive relationship between cloud computing use and information sharing.

3.2. Cloud Computing Use and Information Sharing

Cloud computing builds on the research in virtualization, distributed computing, grid computing, utility computing and networking web and software services (Vouk, 2008). It enables individuals or companies to lease infrastructure resources on-demand from a virtually unlimited pool, using either a one-time payment, pay-as-you-go billing model per unit of time or hybrid method (Rochwerger et al., 2009).

Table 1. Benefits and risks of cloud computing Benefits Literature Flexibility/Convenience Ability to choose between owned infrastructure of rented from third party vendor

Marston et al. (2011); Benlian & Hess (2011)

Large amount of computing power in short amount of time (analyzing terabytes of data in a period of minutes)

Marston et al. (2011); Benlian & Hess (2011)

Ability to request more computing resource in minutes with minimal service provider interaction

Marston et al. (2011); Benlian & Hess (2011); Iyer & Henderson (2010)

IT services in countries that would traditionally lack resources for deployment of IT service

Marston et al. (2011)

Adaptive structure shared by different end users in different ways with different mediums

Marston et al. (2011); Benlian & Hess (2011); Iyer & Henderson (2010)

Offers mobile interactivity Marston et al. (2011); Iyer & Henderson (2010) Massively scalable services (SaaS, PaaS, IaaS) Marston et al. (2011); Benlian & Hess (2011); Mantena

et al. (2012); Iyer & Henderson (2010); Bardhan et al. (2010); Benlian et al. (2011); Vouk (2008); Rhoton (2011)

Ability to choose between public, private or hybrid Marston et al. (2011); Iyer & Henderson (2010); Bardhan et al. (2010)

On demand access to information Marston et al. (2011); Benlian & Hess (2011); Iyer & Henderson (2010); Bardhan et al. (2010); Benlian et al. (2011); Buyya et al. (2009); Armbrust et al. (2009)

Reduced maintenance, upgrades and development with vendor (focus on core competencies)

Marston et al. (2011); Benlian & Hess (2011)

Offers green practices Marston et al. (2011); Alford & Morton (2009); Benlian & Hess (2011); Whitten et al. (2010); Iyer & Henderson (2010)

Ability to verify history/location or application of an item through documentation

Iyer & Henderson (2010)

Payment choices (flat, pay per use, two tier) Alford & Morton (2009); Buyya et al. (2009) Cost Energy, infrastructure and maintenance cost savings Marston et al. (2011); Alford & Morton (2009); Benlian

& Hess (2011); Whitten et al. (2010); Demirkan (2010); Benlian et al. (2011)

No upfront capital investments with immediate access to hardware resources

Marston et al. (2011)

Low cost for switching service providers Iyer & Henderson (2010) Risks Literature Current Reliability Marston et al. (2011); Benlian & Hess (2011); Gewald et

al. (2009) Stability Marston et al. (2011); Benlian & Hess (2011); Kauffman

& Sougstad (2008) Security Marston et al. (2011); Benlian & Hess (2011) Expected Higher than expected cost arising from changing future requirements

Benlian & Hess (2011); Bardhan et al. (2010)

Table 2. Benefits and risks of EDI Benefits Literature Performance Business/Supply chain performance Cantor & Macdonald (2009); Machuca & Barajas

(2004); Rosenzweig & Roth (2007); Sanders (2007); Zhu & Kraemer (2005) (2002); Lee et al. (1997a,b)

Cost Cost reduction (transaction, paper, managerial) Prahinski & Benton (2004); Srinivasan et al. (1994);

Handfield (1993); Boyer & Pagell (2000); Choudhury et al. (1998); Johnson et al. (2007); Mukhopadhyay et al. (1995); Massetti & Zmud (1996); Carter & Frendall (1990); Olson & Boyer (2003); Klein (2007); Lee et al. (1997); Cantor & Macdonald (2009); Machuca & Barajas (2004)

Flexibility/Convenience Faster information delivery Hill & Scudder (2002); Sheombar (1992); Jayaram &

Vickery (1998); Narasimhan & Carter (1998); Boyer & Pagell. (2000); Sanders (2008); Ragatz et al. (1997); Gunasekaran & Ngai (2005)

Frequency of information flow Hill & Scudder (2002); Sheombar (1992); Jayaram & Vickery (1998); Narasimhan & Carter (1998); Holland et al. (1992); Barratt & Oke (2007); Rosenzweig et al. (2003); Barratt & Barratt (2011)

Ease of information flow Hill & Scudder (2002); Sheombar (1992); Jayaram & Vickery (1998); Narasimhan & Carter (1998); Boyer & Pagell. (2000); Sanders (2008); Ragatz et al. (1997); Gunasekaran & Ngai (2005)

Risks Literature Reliability Sanders (2007); Chopra et al. (2001); Menor et al.

(2002); Katsaros (94); Horback (94); Lockstrom et al. (2010)

Security Sanders (2007); Chopra et al. (2001); Menor et al. (2002); Katsaros (94); Horback (94)

Incompatibility Frohlich & Westbrook (2001) Costly Narasimhan & Das (2001) Non-internet enabled EDI is difficult to implement Boyer & Olson (2002); Zhu et al. (2006)

While cloud computing is rapidly being adopted by various organizations to facilitate supply chain relations, it has various benefits and risks in common with the more traditional web-based EDI. Tables 1 and 2 provide a summary of the benefits and risks associated with both cloud computing and EDI. However, the main difference between the two information technologies is the flexibility of service options that cloud computing provides over traditional EDI. First, cloud computing provides three types of service: Software as a Service (SAAS), Infrastructure as a Service (IAAS) and Platform as a Service (PAAS), which entail different services based on a client’s needs. Software as a Service (SaaS) provides business applications that are delivered as a service. This helps reduce software complexity and costs, enhances accessibility to services and speeds up the time to market (Rochwerger et al., 2009). SaaS also offers service providers simplified software installation and maintenance, as well as centralized control (Vouk, 2008). With SaaS end users can access service on-demand wherever they are, share data and collaborate more easily, and keep data stored in a provided infrastructure (Vouk, 2008).Infrastructure as a Service (IaaS) allows for storage and processing capacity (Vouk, 2008). Resources are split, assigned and dynamically resized to build ad-hoc systems for customers of cloud computing technology (Vaquero et al., 2009). This allows IaaS customers to rent computing resources, rather than install them in their own data centers. Likewise, it offers a fast,

easy, on-demand way of allowing customers access to computer hardware, such as servers, networking technology, and data center space. Platform as a Service (PaaS) is a set of software programs that can provide what a developer needs in order to build an application (Vouk, 2008). Instead of supplying a virtualized infrastructure, cloud computing offers a software platform on which systems can run (Vaquero et al., 2009). Further cloud computing offers the user the option to choose a payment plan that a user can choose and scale according to their needs or a supply chain partner’s needs. Along with manipulating the type and payment of the service users can also control the way in which it is received including a private, public or hybrid cloud service. Public clouds, like the amazon cloud drive allows multiple users to access the cloud infrastructure with limited security whereas a private cloud requires a user to provide a secure password and identification before accessing any type of information. The ability to privatize a cloud can ease security concerns among both users and their supply chain partners. While EDI promotes similar benefits to the supply chain field and in turn has been shown to enhance information delivery speed, frequency and ease and ultimately benefit supply chain performance (Cantor & Macdonald, 2009), cloud computing has greater potential to be accessed on a variety of mediums and locations and can analyze terabytes of data in a period of minutes (Marston et al., 2011; Benlian & Hess, 2011). This is dissimilar to web-based EDI which typically requires a common platform on either end (i.e. common ERP systems) (Monczka et al., 2011).

The impact of IT on information sharing is not new in literature (Clemons et al., 1993). Additionally previous research has suggested the various benefits associated with cloud computing that may impact information sharing (Sahin & Robinson, 2002; Rochwerger et al., 2009; Vouk, 2008; Rosenthal et al., 2010). However, no study to our knowledge has yet to empirically examine cloud computing’s impact on information sharing in the supply chain. The flexibility provided by the cloud offers three catalysts for greater information flow: greater speed at which information is processed, enhanced security through privatization options and ability to tailor the type, medium and payment of service. This flexibility allows for users to tailor the cloud according to both their and their supply chain partners needs leading to a safe and effective environment for information sharing ultimately being a useful resource to provide superior competitive advantage.

Based on this previous literature we formulate the following hypothesis

H3. Cloud computing use positively influences information sharing.

3.3. Trust

While various definitions of inter-organizational trust exist, most scholars agree that confidence in the other party’s credibility and good will are essential (Johnston et al., 2004; Gattiker et al., 2007). In this study we use Zhang et al. (2011) definition of trust as “a

trustor’s confidence and belief in credibility and goodwill of an object of trust,” where the object may be a purchasing agent or a buying organization (Zhang et al., 2011). We use this definition because credibility and goodwill are two of the most well cited and agreed upon dimensions of trust (Zhang et al., 2011), and Zhang et al. (2011)’s definition focuses specifically in the supply chain management field.

Zhang et al. (2011) argues that in interpersonal and inter-organizational trust there exist two specific dimensions: credibility and goodwill. These dimensions incorporate several other dimensions that have been looked at in past research such as honesty and benevolence.

Credibility refers to the belief that the other party is dependable or reliable (Johnston et al., 2004). This can run the gamut of meaning anything from a supplier being honest to providing adequate information. Most if not all buyer/supplier relationships that seek to be long-term will require the supplier to fulfill obligations and behave predictably (Zaheer et al., 1998). This can include behavior in which a supplier follows through on contractual agreements. Without sufficient follow through it is unlikely that trust will be fostered due to the lack of credibility.

Goodwill refers to the belief that one party will act in the best interests of another, even if there is no way of monitoring behavior (Johnston et al., 2004; Ganesan, 1994; Baker et al., 1999; Zaheer et al., 1998; Sako, 1992). This dimension includes providing adequate information without compensation or not participating in activities that may be harmful to a trusting party (Johnston et al., 2004). The goodwill dimension of trust has also been defined as a partner’s moral values measured by a willingness to protect the interests of that partner (Hosmer, 1995; Hill et al., 2009). This represents anything that the trustee organization can do in order to benefit the success of the trustor organization.

Past research suggests that strategic alliances supported by information technology have high potential for opportunistic behavior such that in order for information sharing to occur, a firm needs to have confidence in its partner’s behavior (Das & Teng, 1998). Trust has also been shown as a moderator between a firm’s adoption of e-procurement to e-marketplace participation (Chang & Wong, 2010). Although adoption and participation are separate from cloud computing use and information sharing, a connection exists through information technology (cloud computing use and e-procurement adoption) and the implementation and result of information technology (information sharing and e-marketplace participation). While there is very little research in the supply chain management area with cloud computing use, the recentness of cloud computing has caused many organizations to be concerned about storing sensitive information on the cloud (Rochwerger et al., 2009). Without adequate trust, users may be concerned about storing vital information needed for better information sharing.

Social capital theory proposes that firms are made up of individuals, and the relationships among these individuals shape activities and outcomes (Ketchen, Jr. & Hult, 2007). Trust is a vital component for organizations to become comfortable with sharing sensitive information with other organizations. Trust, therefore, between supply chain partners is used as social capital to moderate the relationship between cloud computing use and information sharing.

Based on this previous literature we formulate the following hypothesis:

H4. Trust moderates the relationship between cloud computing use and information sharing.

3.4. Information Sharing and Supply Chain Performance

Because information sharing is widely cited in supply chain literature, it has various definitions. Monczka et al., (1998) explain that communication behavior combines the extent to which the information exchanged affects the level of information quality and participation. Mohr & Spekman (1994) argue that information sharing is the extent to which critical information is communicated to one’s supply chain partner. Huber & Daft (1987) focus on information quality, which includes accuracy, timeliness, adequacy and credibility of information.

In this study Zhou & Benton, Jr’s (2007) definition is used, which organizes information sharing into three dimensions: information sharing support technology, information content, and information quality. We chose Zhou & Benton Jr’s (2007) definition that focuses not only on content and quality of the information, but also on a method of how it may be communicated (i.e., information sharing support technology). Since our study focuses on cloud computing technology, this definition provides a broader and more definitive context for information sharing.

Previous research suggests that the degree of relationship among organizations in a supply chain has a significant impact on supplier satisfaction (Benton & Maloni, 2005). Additionally, stronger buyer-supplier relationships enhance supply chain performance (Benton & Maloni, 2005). A relationship among supply chain members is fostered when several factors exist among the members. These include commitment, trust, cooperation, and conflict resolution when conflict exists (Benton & Maloni, 2005). Information sharing is vital to maintaining and fostering the relational factors among supply chain members. For example, information that is shared is also useful in providing a reference guideline for suppliers when initiating collaborative relationships with customers (Humphreys et al., 2001). Li et al. (2005) suggest that information sharing helps to create superior performance in supply chains, because it allows for supply chain partners to work as a single entity. In addition, it helps break down functional barriers and engenders cooperation to meet

the requirements of customers (Flynn et al., 2010). Greater cooperation and integration, thereby, leads to process efficiency and logistics service performance (Saeed et al., 2005; Germain and Iyer, 2006; Stank et al., 2001a, b).

Based on this previous literature we have formulated the following hypothesis:

H5. Information sharing positively influences supply chain performance

4. Methodology

A combination of case study methodology and survey methods was used to examine our proposed model. The multi-method (also known as mixed-method) was chosen because separate and dissimilar data sets provide a richer and more in-depth analysis (Sawyer, 2001, p. 180).

Qualitative methods including the case study were used, given the high degree of uncertainty surrounding our model (Trauth, 2001). Our conducted interviews provide a deep understanding of activities and behaviors associated with cloud computing use, as well as its impact on information sharing and ultimately performance. Additionally, using grounded theory in resource-based view and social capital theory as a basis for qualitative methods allowed us to build a conceptual model and derive propositions.

Quantitative methods were later employed to empirically examine the theoretical model derived from our qualitative data. Using structural equation modeling, we examined the relationships between each of our constructs. Using both qualitative and quantitative methods provides a deeper and richer understanding (Kaplan & Duchon, 1988). Moreover, the multi-method design strengthened the results through triangulation (Kaplan & Duchon, 1988).

4.1. Case Study

4.1.1. Case Study Selection

Case study methodology requires target organizations be chosen based on how they contribute to the ultimate research questions, as opposed to random sampling (Eisenhardt, 1989; Glaser & Strauss, 1967; Siggelkow, 2007; Staats et al., 2011). We chose our organizations based on the following criteria. First, we wanted an organization that was currently using cloud computing technology, whether through a public or private cloud. Secondly, we interviewed participants in upper management that were well aware of the basic strategies of their organizations, as well as how the cloud was used by their companies.

4.1.2. Case Study Protocol

In developing our case study protocol we used sections incorporating research and construct overview, topics, objectives, and data collection (Yin, 2009). Our case study protocol can be found in the Appendix- Table 3.Yin (2009) outlines the assessment of the quality of an empirical research design, including construct validity, internal validity, external validity and reliability. Using a panel of experts, the questions were developed and structured from broad to detailed (Lockstrom et al., 2010).

During and after coding the data, we used multiple iterations through grounded theory (Glaser & Strauss, 2006). We also used existing literature to assess the causal relationships in order to establish adequate internal validity. We discussed both consistent findings, as well as rivaling propositions with colleagues (Marshall & Rossman, 1995).

A multiple case study approach was used in order to increase external validity. Using a multiple case study approach allows researchers to consider “within-case” analyses and a “cross case” analysis using replication logic (Yin, 2009; Lockstrom et al., 2010). To maintain reliability, we developed a detailed case protocol to enable consistent data collection. Each interview was also conducted using a voice recorder and later transcribed. We also sent a case script for participants to review in accordance with Yin (2009). We also used multiple researchers to code and analyze the data and to cross validate recurring themes (Lockstrom et al., 2010).

4.1.2. Data Collection

In this study we used a representative case encompassing a holistic, multiple case study approach because the purpose was to capture the circumstances of everyday, commonplace situations (Lockstrom et al., 2010; Yin, 2009). The participants in our study included organizations that used cloud computing technology for operations and were varied in size. The sample of firms obtained is summarized in Table 4.

Table 4. Company profiles Company no. Company category Country of

origin Key informant

1 Consulting/ Technology Services USA Senior Manager

2 Tax Software USA Co-owner

3 Global Logistics/Transportation USA Vice President (VP) of International Marketing & Director of Supply Chain Management

4 Deliverer or GPS technology USA Senior Vice President (SVP) of Marketing and Logistics & Director of Information Technology

We conducted interviews over a two month period, and each interview lasted between thirty minutes and one hour. In order to ensure comparability and maintain consistency and flow, we used a semi-structured interview method (Yin, 2009). The interviewees ranged from top management to supply chain specialists who were aware of how their organizations utilized cloud computing technology and their overall company strategies.

The researchers continued to interview until theoretical saturation was accomplished (Yin, 2009). Overall, interviews with six different individuals from four companies were conducted, which is considered adequate according to Yin (2009). Since the interviews were semi-structured, we were able to gather the required information needed to seek out the relationships for our model.

5. Exploratory Analysis

After completion of each interview, the voice recordings were transcribed by two different researchers in order to ensure construct validity. After coding the data, five analytical categories and five causal relationships were found. We interviewed four companies, whose names have been changed to protect their identities. These companies are further summarized in the next section.

5.1. Overview of Companies

5.1.1. Company Retail

In Company Retail we interviewed a consultant from a consulting, technology services and outsourcing company that specifically works for a retailer. The consulting company operates in over 200 cities in 53 countries and has several operating groups, including

health and public services, communication and high tech financial services, products and resources. In recent years, Company Retail has acquired consulting, software and technology firms. It is a 4 billion dollar publicly traded company.

5.1.2. Company Truck

Company Truck provides tax services for small or individual trucking companies. Since 2007, Company Truck has prepared IFTA returns for 2500 companies and provides access to these returns, as well as to miles and fuel data that can be accessed any time from any computer. Along with preparing returns, company truck offers customers free driver qualification tracking software, hours of service calculator and a fleet maintenance program wherever and whenever a trucking company may need it.

5.1.3. Company Transport

Company Transport is a holding company that offers its customers a range of transportation services, including global, national, and regional transportation, as well as logistics, with subsidiaries in the national, regional and international markets. Company Transport is a 2.69 billion dollar publicly traded company.

5.1.4. Company GPS

Company GPS provides navigation, communication and information devices and applications using GPS technology. Its four main business segments are marine, automotive/mobile, outdoor/fitness and aviation. The company is a 4.9 billion dollar publicly traded company.

5.2. Business Strategy and Cloud Computing Technology

Interview participants were first asked about business strategy. Following the Miles & Snow (1978) typology, we found each case identified with the different strategies.

Many of our interviewees stressed the importance of cost reduction and efficiency seeking methods prevalent in the defensiveness strategy. We interviewed a Senior Manager from Company Retail, a global management consulting and technology services company. The Senior Manager described the focus on cost reduction in the organization’s operations, “We are continually looking for areas where we can reduce costs and also become more efficient from an operating perspective.”

Company Retail’s Senior Manager suggests that this strategy impacts the company’s use of cloud computing technology. In particular, Company Retail uses cloud computing technology to further the goal of not only cost reduction, but also greater efficiency through virtual services. He later explained:

We have multiple sites, distribution operations, scattered across the U.S., and in each of these we’re continually looking for opportunities where I can take different aspects, whether it be email services or file print services, and make those virtual.

Cloud computing not only provides a means of cost reduction, but also of increased efficiency through virtual services. A company, depending on its strategy, can use the cloud to obtain the benefits desired.

Like Company Retail, Company Truck, a tax software company, also considers both cost reduction and efficiency seeking as priorities for the firm. The cost reduction that cloud computing provides Company Truck is described by its Co-Owner as follows:

We are using infrastructure as a provider, called GoGrid, to replace all of our physical servers to run our applications on. We are also using other things like Google email, which is a cloud service as well. In cost reduction we replaced around 95k in hardware with $275 a month hosting charges…so our cost reduction is huge.

Originally, Company Truck invested $95,000 and was spending a large amount in upkeep of hardware. For a company focused on cost reduction, this may seem to be a large amount to invest. Yet, with cloud computing technology the firm is able to save a great deal of money in maintenance fees, as well as reduce the investment to $275 a month for hosting charges.

Company Transport, considers itself an industry leader in information technology and a very early adopter of cloud computing. They identify with a cost reduction strategy in their operations. They also suggest that their use of cloud computing technology is driven by their strategy. Company Transport uses cloud computing technology to reduce several different types of costs, as suggested by the Vice President (VP) of International Marketing below:

One way to reduce cost and enhance efficiency is to implement and use information technology and information systems. We use cloud computing technology to reduce our company’s overall costs. For instance, there is a drastic reduction in operational expenses. Hardware costs are also minimal. With a minimal maintenance cost, we can rely on the cloud computing services partner to look after our SCM related software applications, especially in overseas markets.

Company GPS, uses a slightly different strategy. Being not only a pioneer in implementation of cloud computing, but also a provider of cloud computing services, their strategic priorities are innovation and vertical integration. However, cost reduction and efficiency strategies are important operational tactics. Despite this, cloud computing provides a platform that enables a vertical integration strategy, as the Director of Information Technology describes below:

Cloud computing is very fit for our overall vertical integration business strategy in that it provides us with an efficient and cost effective platform to provide high quality services to various functional areas within our company and external partners.

Risk aversion is another strategy outlined by Miles & Snow (1978). Each company interviewed had its own risk taking propensity. Company Retail is extremely risk averse. That is, they are conservative in resource allocation decisions and product and market choices. The Senior Manager at Company Retail described their risk taking propensity as follows:

We are an extremely conservative organization…so that we have the ability to manage risk of implementation and keep the product flowing through the supply chain.

This risk averseness impacts their use of cloud computing technology to share information with their supply chain partners. Company Retail is in a private cloud, where the private cloud is devoted to a single organization’s internal use (Grossman, 2009). The use of a private cloud tends to be more secure in storing sensitive information and helps reduce potential security risks, including the ability of others to obtain sensitive information.

In terms of risk, Company Truck is very conservative. Originally, Company Truck considers the major risk associated with the IaaS service to be the reliability of the cloud. This is not an uncommon worry for cloud computing users. Many are concerned about whether the service will be available or down during critical times. However, for Company Truck the cost reduction benefits achieved from cloud computing technology far outweigh any associated risks as described below:

We are afraid of screwing up people’s taxes, so we have a bunch of disclaimers on our website about how the user is responsible for verifying the accuracy of the software return. Our biggest risk when we first went to GoGrid for our infrastructure was uptime. So I was able to sacrifice a little more risk in terms of cost benefit.

Despite this, Company Truck still monitors the information stored in the cloud, given the security risk. For example, company truck does not store customer credit card information in order to reduce the likelihood of potential fraud.

Unlike companies Truck and Retail, Company Transport considers itself risk neutral. The Director of Supply Chain Management stated:

We are risk neutral in the sense that we are actively pursuing business opportunities in emerging markets, while we have risk management strategies in place to deal with such risk effects.

Dealing with risk is a necessity for large supply chains. Complex supply chains require coordinated flows of goods, information, cash, etc. within and among different nations. Additionally, security issues and risks tend to perpetuate when dealing with large numbers of firms in different countries. Company Transport tries to maintain a balance between being opportunistic, yet verifying security and risk issues regarding information technology. With the use of cloud computing technology, there have been some troubling issues having to do with losing data as described by the Director of Supply Chain Management below:

We noticed that there have been a number of high profile incidents recently, where some of the largest cloud providers have had outages, and some even lost data.

In reaction to these problems, Company Transport utilized risk management tools to assess their information technology risk on different dimensions like technology, people and processes. In particular, they use risk assessment in their use of cloud computing technology for data integrity, recovery and privacy. Company Transport tends to use a private cloud, which provides security, while occasionally using a public cloud for customers. Their strategy is a balanced approach for taking advantage of opportunities and maintaining adequate security. Their cloud computing use is also balanced through the application of a public cloud to enhance opportunities for greater exchange between themselves and their customers and a private cloud to maintain adequate security within the company. Company Transport’s Director of Supply Chain Management describes this strategy as follows:

I feel that there is a trade-off between scale (massively scalable service that cloud computing offers) and control. One extreme is that organizations run their own infrastructure and have total control. The other extreme would be a totally cloud-based infrastructure. We are avoiding both extremes. For our cloud computing architecture, we use both private and public clouds. A private cloud offers less scale and more control, while a public cloud offers maximum scale and minimal control.

On the other end of the spectrum is Company GPS, which, being an innovator and pioneer in the industry, is alert to the pursuit of any market expansion opportunity. Within the past three years, they established a joint venture with Shanghai, and currently have

subsidiaries in Taiwan and South Korea. Cloud computing has enabled them to further their goal of vertical integration as the VP of Marketing and Logistics describes below:

Cloud computing is a viable tool for us to consolidate and coordinate IT functions between headquarters and subsidiaries to achieve our vertical integration strategy.

Although in the first adoption of cloud computing technology Company GPS used the private cloud for security reasons, they have now started to adopt the public cloud for external reasons. The Director of IT describes how they view the security of the cloud below:

Security is still an issue for executives considering the cloud, but it has dropped dramatically in importance. I think this indicates it may not be as crucial a factor for companies that are considering public cloud services as it once was.

Risk averseness is a strong factor in the way companies use cloud computing technology. In interviewing our participants, we also saw aggressiveness, or the rate at which a company moves faster than its competitors for improving market share, as a key factor in the use of cloud computing technology.

Aggressiveness was relatively constant between companies. Company Retail had a focus on maintaining a close watch on its competitors. They specifically sought out ways to maintain a strategic advantage over the competition. This strong competitive and aggressive focus impacted the way they used cloud computing technology. The Senior Manager describes their strategy as follows:

…we want to be able to continually push things into the stores. (We use cloud computing) to make sure our information is updated. We also use cloud computing to keep all of the applications in sync in all of the different locations simultaneously.

Cloud computing for Company Retail serves as a way to maintain product flow in the supply chain through updated information on shipments. This retailer is in multiple locations and accesses information through a system that specifically tabulates what is in each store and what is needed.

Like Company Retail, Company Truck also has to maintain its aggressiveness when dealing with constantly changing customer needs. Being a tax software service company, each year they must deal with new regulatory issues. At the same time, customers desire more in terms of access and speed of service. Cloud computing provides a platform that allows them to maintain an aggressive stance in changing their service in relation to their competitors. Company Truck’s Co-Owner describes this strategy as follows:

We are now looking at going a lot more mobile and collecting data from GPS devices both in terms of hardware and in terms of mobile devices for the phones. Our users are constantly in motion, so we are looking at different facets to use mobile technology.

Company Truck uses cloud computing to complete computations that would normally take several hours. However, by employing several different computers and carrying out computations simultaneously, they can do so in less time. By saving time they also save energy and power by not utilizing resources that would normally be used without cloud computing technology.

Company Transport also has an aggressive approach in reacting to changing customer needs. They focus on reducing costs for customers as the VP of International Marketing describes below:

We are confronting higher customer expectations such as more intimate knowledge of, and services tailored to, the customers’ respective industries. We are further recognizing a strain on their profitability from increasing cost pressures such as government regulations and inflated fuel prices.

In response to this growing market need Company Transport uses information technology to maximize the overall efficiency of business processes. Cloud computing technology allows Company Transport to discover and adapt to regulatory changes and to lower costs, which are passed on to their customers.

Like aggressiveness pro-activeness, or flexibility in changing environmental trends, varies between companies and also impacts the use of cloud computing technology. Company Retail’s Senior Manager describes how things were before they started using cloud computing technology below:

Currently, we have a focus on sustainability, continually looking for opportunities to reduce carbon footprint. Before we had servers in every single store handling different applications…since (using cloud computing) we’ve been able to centralize a lot of our functions to reduce energy use.

From this statement it is evident that Company Retail is pro-active in sustainability and reducing their carbon footprint. This has impacted their use of cloud computing by focusing on reducing their carbon footprint via centralizing systems and reducing energy use.

Like Company Retail, Company Transport also has a pro-active stance with regard to reducing its carbon footprint as the VP of International Marketing explains below:

We participate in programs and processes for protecting and preserving the environment. These strategies have the dual goals of reducing our carbon footprint, while optimizing our corporate resources. Our industry-leading companies effectively and aggressively promote greenhouse gas reduction strategies, waste reduction and conservation across their daily operations, including green information technology.

Cloud computing is one resource that Company Transport uses as a “global logistics capability” to connect organizations throughout the world in order to improve the efficiency of the global supply chain.

Another strategy discussed in our interviews, as well as in Miles & Snow (1978), was analysis. There were several different ways our interviewees considered this in terms of problem solving strategies.

Company Transport’s representative discussed hiring external consultants that were technology experts in solving problems associated with information technology. This allows them to concentrate on their core competency, rather than having to worry about issues that are beyond their normal knowledge managing practices. This problem solving behavior also impacts the way they use their cloud computing technology. Company transport concentrates on vendor selection and risk management associated with its use. The VP of International Marketing describes this below:

We need to rely on our vendors if services provided by them are woven into business processes. So choosing a supplier for cloud computing services in our organization has to be done with the idea of a long-term relationship in mind.

Company Transport’s attention to detail in vendor selection and risk management has helped to recognize this company in Security magazine’s Top Security 500. By choosing a responsible vendor and concentrating on risk management, Company Transport is able to fix problems before they occur by having access to reputable vendors and eliminating future problems through risk management initiatives.

Futurity was the last strategy type discussed during our interviews. Company Retail describes why they focus on short- term decisions:

We have operations teams that are very much focused on short-term. The effect of what we’re doing today is trying to get the product out, making sure the stores have the information they have.

This short-term viewpoint breeds concentration on efficiency of operations. In terms of cloud computing use, it also impacts the way they view the short-term use of cloud computing technology. They change the focus from questions such as, “Will I need as many servers in the data centers?” to, “Will I be able to operate the data centers in a different manner over time in the short-run in order to run operations efficiently?”

Company Transport, on the other hand, focuses on both short-term and long-term strategies. The VP of International Marketing describes this strategy below:

We are in a very competitive environment today, and the nature of the supply chain management business is thin profit margin and cut-throat. As such, efficiency of operations is very crucial. Supply chain management is also very tech intensive. To be a leader in the industry in the long-run, we need to pursue IT innovation.

For Company Transport, cloud computing provides a platform for supply chains to become more dynamic, scalable and capable of supporting objectives in cost reducing, efficiency and in being the leader in IT innovation for both the short-term and the long-term.

Based on our interviews, we can support both hypotheses 1 and 2 that business strategy positively influences cloud computing use and that business strategy moderates the relationship between cloud computing use and information sharing.

5.3. Cloud Computing Use and Information Sharing

Interview participants were also asked about their cloud computing use. We asked them to describe the service that they use with cloud computing technology. In particular three surfaced: the massively scalable service provided by cloud computing, including the three types: SaaS, IaaS, and PaaS, the on demand service provided by cloud computing technology and the pay-as-you-go service.

Company Retail uses a private cloud, which they describe as follows, “We’re private, so with clients we actually set up vendor portals.” The vendor portals allow other individuals to access information from the cloud, but each organization has its own password and log in information for added security.

This private cloud use impacts the way they share information and the type of information they share with vendors. Company Retail’s Senior Manager explains this below:

The vendor can obtain information, whether it is purchase order information, routing information for shipments, status of orders, or status payments.

This information is shared among vendors, and they can access it at any point in time using the secured password and log in information. Cloud computing provides a platform for companies to access information at any point in time, even at different locations as described by Company Retail’s Senior Manager below:

It (Information sharing) is driven across the cloud. We have a centralized data center, and then everybody else can access that from a variety of different locations.

Company Retail’s private cloud computing offers ease of access to information without the security risks associated with public cloud computing. This also impacts Company Retail’s sense of security when sharing information with other users as described below:

We’re pretty comfortable with (sharing information) by giving each of the individual organizations their unique log on and password, so that only they can see their information and their data, even though it’s in a much larger database environment.

Company Transport also has various uses for cloud computing technology. They include facilitating process integration with the help of enterprise resources planning, enterprise application integration and greater information sharing through greater coordination of efforts between supply chain partners to respond to customer needs, and greater availability of strategic and tactical data for other members in the supply chain. In this sense cloud computing was used as a driver for both process and service, allowing Company Transport a greater competitive advantage, especially in customer relationship management as the VP of International Marketing describes below:

We have revolutionized customer relationship management via cloud computing (e.g. public cloud), allowing our customers to deploy online customer services on their corporate websites.

Company GPS, which uses both web-based cloud services and SaaS, suggests that cloud computing provides them a “clear edge” in globalization efforts by allowing for greater communication between firms in the supply chain. The director of information technology describes this benefit of cloud computing as follows:

Cloud computing facilitates and enhances information sharing processes. For example, one of our second tier suppliers and our company use the same cloud computing service for VMI applications, and it improved the information sharing between us.

Based on these interviews, we can support hypothesis 3 that cloud computing use positively influences information sharing.

5.4. Inter-Organizational Trust of Cloud Computing and Information Sharing

Interview participants were then asked to elaborate on the social relationships they have with their supply chain partners. In this study we are specifically interested in inter-organizational trust between supply chain members.

Both credibility and goodwill dimensions of trust were established in the interviews we conducted. Company Retail’s Senior Manager describes the relationship with suppliers and clients as follows:

We like to feel that all of our clients and all of our suppliers are credible, and they all desire to put forth their best foot.

Despite the strong level of trust that Company Retail has with its partners, trust at certain points in time needs to be verified. In order to do this, Company Retail researched its partner’s financial situation to discover any underlying problems as described below:

There are times, as with any business, you’ll find that when trouble does arrive they may be reluctant to put information forward. And you’ll start to see that with untimely delivery of making shipments. You’ll start to see issues from that perspective. At that point we start to take a look at their financials for a better understanding of what’s going on with their business.

When a partner is having difficulties with financial stability, Company Retail notices a decrease in the amount of information shared with them. By this we can see that trust may impact the relationship between cloud computing use and information sharing. That is, when trust is low, information sharing may be negatively impacted despite cloud computing use.

Company Transport is similar to Company Retail in their “trust but verify” mentality with supply chain partners in using cloud computing to communicate information sharing. The VP of International Marketing describes the company’s viewpoint of security with cloud computing technology below:

IT security of cloud computing is about trust. Any one of our IT partners (e.g., vendors and ISPs) can undermine our security: crash our systems, corrupt data, allow an attacker to get access to systems. The security and reliability of our platform is fundamental to our business, as is the trust and faith that our customers place in us…but we can use compliancy and standards as a solution to that issue.

Company Transport asks vendors to maintain adequate standards in terms of protocol and data formats. Further, vendors have to be certified and presented publicly to the company. While these certifications are costly, they are also critical for adoption, because they build the foundation of service level agreements between suppliers and buyers in the supply chain, thus, enhancing information flow and business. Moreover, Company Transport operates a business intelligence infrastructure to control its datacenters. This involves other companies in the supply chain having to provide operational data in order for Company Transport to react to bottlenecks or to up- or downscale the infrastructure. When this is done, adequate information sharing can be accomplished.

Company GPS also believes in the importance of trusting one’s supply chain partners. Company GPS treats its suppliers and buyers as business partners with the same goals and purposes in mind. Trust is of utmost concern when dealing with using IT such as cloud computing to facilitate information flow between partners as the VP of International Marketing and Director of IT describe below:

We believe in this day and age buyers and suppliers come together for mutually beneficial reasons, based less on the customer’s or supplier’s power and more so on a relationship based on value exchange . . . Any one of our IT partners can undermine our security…Before we can start to share information there has to be trust between the various links in the supply chain.

Given the security risk that often comes with cloud computing technology, including vendors that crash systems, corrupt data or allow an attacker to get access to the system, it is vital for Company GPS to maintain a trusting relationship before using cloud computing to communicate with firms. The VP of International Marketing describes this below:

Almost everything we will talk about in supply chain management is predicated on being able to share information openly with the appropriate members of the chain. In other words trust is then a key foundation of supply chain management.

Based on these interviews, we can support hypothesis 4 that trust moderates the relationship between cloud computing use and information sharing.

5.6. Information Sharing and Supply Chain Performance

Another aspect asked of our participants concerns information sharing between them and their partners. We inquired about three aspects: information sharing support technology, information content and information quality.

Company Retail describes information sharing support technology as consisting of vendor portals in the private cloud. Vendor portals are gateways that can be accessed by the partners, each using their own specific user names and passwords for added security. In these vendor portals individuals can access information, including shipping information and status of orders. Using these vendor portals seems to enhance Company Retail’s relationship with vendors and individual partners as described below:

That (vendor portals) seems to be spreading quite well and is very well received both within our organization and within our individual partners.

The vendor portals have been successful in sharing information between Company Retail and individual partners. In this sense the information sharing support technology, or vendor portals that Company Retail uses, strongly impacts their relationships with partners.

Company Transport also suggests sharing important information like sales forecasts, marketing strategies and inventory levels with supply chain partners using cloud computing technology. The Director of Supply Chain Management describes the importance of information sharing as follows:

Since building up new capacities in large quantities takes up to years, forecasting demand is vital for providers of computing power, and they (supply chain partners) invest great efforts in this.

Accurate forecasts in demand can also help alleviate the bullwhip effect in supply chains (Lee et al., 1997a, b). Through the use of cloud computing technology, Company Transport can help alleviate problems in the supply chains that result from inaccurate forecasts in demand.

Company Transport also suggests there are two types of information sharing: sequential information sharing and reciprocal information sharing structures. In sequential information sharing the output of one partner’s activity flows to the next partner as an input, and this continues as a sequential process along the supply chain. In this case they rely on electronic data interchange. However, reciprocal information sharing is more complex, considering that information flow is bi-directional and partners communicate with several others, which may cause inconsistencies regarding the information of different partners. In this case cloud computing is more useful as a tool to prevent inconsistencies as described below:

To reduce uncertainty and conflict in collaboration, the best coordination mechanism for partners is to synchronize and integrate the interactive processes using cloud computing architecture.

In this case inconsistencies are eliminated via centralized data points. Multiple partners through a public cloud can gather accurate information and increase performance by using information sharing support technology or cloud computing.

Information content is another facet of information sharing. It is defined as the content exchanged between firms in the supply chain (Zhou & Benton, Jr., 2007). In the interviews conducted we found a broad variety of content was exchanged between partners through the use of cloud computing technology. Company Retail describes sharing future demand, shipping information, status of orders and other content as stated below:

We are continually polling our suppliers for what they think they might have coming available and then adjust our forecast accordingly. Likewise, we’re also polling our demand forecast and we’re looking at what we might have for storage from last season or 2-3 seasons ago and forecasting what we might think will sell the best.

Information sharing has impacted demand forecast accuracy. This directly may impact the bullwhip effect, which Lee et al. (1997a, b) describes as oscillating demand amplification upstream in the supply chain. This can also be considered a measure of supply chain performance.

Along with appropriate information content, another aspect important for reduction of bullwhip effect, and improved supply chain performance, is information quality. Information quality refers to the quality of the information exchanged between firms (Zhou & Benton, Jr., 2007). This is more specifically defined using several aspects, including, but not limited to, accuracy, availability, timeliness, internal connectivity, external connectivity, completeness, relevance, accessibility and frequently updated information (Zhou & Benton, Jr., 2007).

Information sharing as a whole, and information quality as a part, was described by Company Transport as helping to achieve an effective way to reduce uncertainties in the supply chain and counter problems like the bullwhip effect. The Director of Supply Chain Management describes how information sharing the right way allowed for greater efficiency:

Information sharing ensures that the right information is available for the right trading partner in the right place and at the right time. We use information sharing to prevent, detect and resolve exceptions spontaneously and create unprecedented levels of efficiency in collaborative supply chains.

Company GPS assesses the value of suppliers in terms of quality, timeliness, ease of access to information and commitment. Greater information quality and flow between each supplier and Company GPS gives the supplier a higher rating. Greater information sharing,

content and quality have helped with problems associated with the bullwhip effect. During the last two years Company GPS carried out two initiatives. The first initiative was to integrate the company’s internal information repositories and centralize relevant forecast and transactional information through customer relationship management. The second initiative was to foster greater information integration among external partners in the supply chain with cloud computing technology. The VP of International Marketing and Director of IT suggests not only has greater information flow reduced price variations and rationing game strategy, which are two main causes of the bullwhip effect, greater information flow has also improved overall accuracy of information, thereby reducing the bullwhip effect as described below:

In Garmin we use collaborative forecasting, that is, a process for collecting and reconciling information from within and outside the organization to come up with a single projection of demand. It is done through information sharing. Evidence from our company shows that collaboration between customers and suppliers improves the accuracy of the forecast. Cloud computing encourages information sharing, and as such, we can alleviate the bullwhip effect and render more accurate demand…improve the accuracy of supply forecasts.

One of the main categories in this study is overall supply chain performance. Along with the elimination of bullwhip effect there were several other dimensions of supply chain performance that were discussed during our interviews with the participants.

Communication is the first dimension of supply chain performance and involves “frequent, genuine and involving personal contacts between buying and selling personnel” (Chen & Paulraj, 2004, p. 126). Use of information technology does not in itself represent communication. It can be used to facilitate communication, but only active involvement and contact between supply chain partners can impact communication on an inter-organizational level.

Communication improves supply chain performance through active information sharing between partners. As mentioned previously, cloud computing technology helped to facilitate active information sharing with Company Retail and its partners that have vendor portals, where information can be accessed from any place at any time.

Along with the importance of communication is the importance of involvement, which refers to the amount of supplier/buyer participation in the decision processes of certain firms. Some suppliers go so far as to be involved in new product development, ranging from giving minor design suggestions to being the main source of responsibility for overall development (Chen & Paulraj, 2004; Wynstra & Ten Pierick, 2000). We also refer to the overall role suppliers play in the decision making of the buyer.

Company Retail has a strong reliance on its supply chain partners as evidenced by its communications with them. By continually polling supply chain partners both downstream and upstream they are able to maintain accurate demand forecasts, as well as remain alert to constantly changing market trends. In return Company Retail makes decisions based on buyer feedback. Similarly, they poll suppliers on what is in storage and can make adjustments in demand through information received. This involvement helps reduce problems in the supply chain, including bullwhip effect (Lee et al., 1997 a,b).

Integration of logistics calls for organizations in the supply chain to maintain integration so that the necessary quantity of goods is in the right place at the right time (Chen & Paulraj, 2004; La Londe, 1983). This requires an intensive and coordinated exchange between supply chain partners (Chen & Paulraj, 2004; Caputo, 1996; Vollman et al., 1997). Company Retail focuses on the importance of adequate information sharing provided by vendor portals in on time delivery performance, which the senior manager describes as being “typically very favorable” with regard to the company:

Our suppliers are looking to get the product out the door, and we’re looking to buy it as quickly as possible. We do have processes in place where the supplier and transportation companies do call for appointments. And it’s one area that we continually look for opportunities to create that vendor portal. That private cloud allows those carriers to come in and schedule their times as opposed to having to answer a phone call or work off an excel spreadsheet.

Company Retail uses information sharing from cloud computing technology to schedule appointments with suppliers and transportation companies. Cloud computing enhances speed and efficiency in information sharing between Company Retail and its suppliers, and this helps to increase not only relationship, but also operational aspects in the supply chain. Along with the relationship aspects of supply chain performance operational measurements were discussed during our interviews.

Company Transport considers several aspects of supply chain performance, including revenue, market value, return on assets and return on stockholder investment, all of which is benchmarked through the use of cloud computing that impacts information sharing. The VP of International Marketing describes the company’s success and how cloud computing has helped achieve this as follows:

We enable firms to achieve reduced operating costs and increase revenues in new and existing markets. We also provide firms an opportunity to enhance their market value by reducing ownership of assets, which translates to a higher return on remaining assets and greater return on stockholder investment. We also bring to the relationship our specialized expertise in managing logistics with contemporary technology and systems, including cloud computing.

This ability to improve value through decreased costs and increased revenues with greater information flow between supply chain partners has also allowed Company Transport to benchmark in two other areas of supply chain performance, outlined by the Director of Supply Chain Management below:

Our firm is the industry benchmark in both areas (short delivery cycle time and responsiveness to customers’ changing needs).

Based on these interviews we can support hypothesis 5 that information sharing positively influences supply chain performance.

While the case study provided an exploratory analysis and helped derive qualitative support for related to the relationships summarized in Table 5 in the Appendix, we will further empirically examine these relationships using survey methodology.

6. Confirmatory Analysis

The research model in Figure 1 depicts the various relationships between business strategy, cloud computing, inter-organizational trust, information sharing and supply chain performance. This model is used to test the validity of the hypotheses that have so far been supported by our case analysis and to provide triangulation of results (Lee, 1991; Mingers, 2001).

6.1. Survey Development

The development of the survey was carried out in three steps: (1) item generation, (2) analysis by experts in the field and (3) large scale analysis. In order to ensure content validity, an extensive literature review was conducted to define each construct. We then gave the survey to a panel of experts in supply chain management to ensure reliability and validity of the scale. Finally, we conducted a large-scale survey to validate the instruments.

According to Churchill (1979) and Segars & Grover (1998) the measurement items should cover the content domain of a construct. To generate measurement items we reviewed past literature and a list of potential items was created. These are depicted in Table 6. A total of 59 items were created using a 7-point Likert scale.

6.2. Sampling design

The sample respondents in this study were individuals from a variety of randomly selected transportation and delivery industries (NAICS codes: 481112, 482111, 483111, 484110, and 484121). Mail-surveys were used and collected over a three month period. The

total number of surveys sent out was 780. We collected 153, out of which 136 were usable with a 17.4% response rate. Characteristics of the respondents appear in Table 7.

Table 7. Firm sample statistics Profiles Number of

respondents Percentage (%)

Type of industry Scheduled freight air transportation (NAICS 481112) 23 17% Line-haul railroads (NAICS 482111) 31 23% Deep sea freight transportation (NAICS 483111) 18 13% General freight trucking, local (NAICS 484110) 25 18% General freight trucking, long-distance, truckload (NAICS 484121) 27 20% Couriers and express delivery services (NAICS 484121) 12 9% Number of employees Less than 500 7 5% >500-1000 39 29% >1000-2000 42 31% >2000-5000 33 24% More than 5000 15 11% Annual sales (in millions) Less than 50 4 3% >50-100 26 19% >100-300 35 26% >300-500 24 18% >500-1 billion 30 22% More than 1 billion 17 12%

6.3. Normality of Data

Structural equation modeling has estimation procedures that require normal distributions for continuous variables (Kline, 1998). After mean-centering the data, we tested for non-normality using the common measurement of skewness and kurtosis. West et al. (1995) suggest that skewness index values ranging from 2.0 to 3.0 and kurtosis values ranging from 7.0 to 21.0 represent moderately non-normal values. Skewness values greater than 3.0 and kurtosis values greater than 21.0 represent extreme non-normality (West et al., 1995).

As seen in Table 9 the majority of our skewness and kurtosis are within the acceptable range with exception to T5, SCP2, SCP3, SCP 12 (skewness just above 3.0), IS1 (Skewness 6.624, Kurtosis 49.307), and CC2 (kurtosis 30.058), SCP4 (skewness 5.633, kurtosis 30.172), and SCP 13 (skewness 4.745, kurtosis 38.636).

Table 9. Sample statistics

N Min Max Mean Std. Dev. Skewness Kurtosis

Variable Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error

BS1 136 .4191 1.5809 .590830 .2935773 2.460 .208 4.900 .413

BS2 136 .2941 2.2941 .621972 .4356668 1.428 .208 1.522 .413

BS3 136 .2353 2.2353 .624567 .4668182 1.185 .208 1.167 .413

BS4 136 .1103 1.1103 .457937 .4288274 .473 .208 -1.689 .413

BS5 136 .1618 1.1618 .493080 .3979190 .500 .208 -1.491 .413

BS6 136 .1029 1.1029 .422145 .4244623 .620 .208 -1.544 .413

BS7 136 .0588 1.9412 .418685 .5141623 1.047 .208 .068 .413

BS8 136 .0662 1.0662 .384516 .4413490 .681 .208 -1.524 .413

BS9 136 .0809 2.0809 .391977 .4489864 .962 .208 -.243 .413

BS10 136 .1176 1.8824 .483564 .4579843 .704 .208 -.723 .413

BS11 136 .1838 1.1838 .492106 .3797608 .601 .208 -1.270 .413

BS12 136 .0368 1.9632 .440744 .5192407 .765 .208 -.570 .413

BS13 136 .1765 2.1765 .673875 .4869102 .728 .208 .457 .413

BS14 136 .2794 1.7206 .622189 .4280379 1.117 .208 .278 .413

BS15 136 .1765 1.8235 .536332 .4764374 1.028 .208 .121 .413

CC1 136 .3603 1.6397 .680904 .3876986 1.266 .208 .323 .413

CC2 136 .4926 1.5074 .529304 .1697617 5.617 .208 30.058 .413

CC3 136 .0956 1.9044 .493512 .4605470 .438 .208 -1.343 .413

CC4 136 .2721 1.7279 .527141 .3957409 1.625 .208 1.975 .413

CC5 136 .3088 1.6912 .533088 .3028325 1.509 .208 2.126 .413

CC6 136 .0294 1.0294 .442474 .4811701 .306 .208 -1.928 .413

T1 136 .0221 2.0221 .273248 .4453832 1.384 .208 .641 .413

T2 136 .2941 1.2941 .508651 .2860801 1.274 .208 1.170 .413

T3 136 .3382 1.3382 .544983 .2728226 1.652 .208 2.660 .413

T4 136 .2794 1.2794 .487457 .2863155 1.223 .208 .892 .413

T5 136 .3529 1.6471 .472318 .2230980 3.340 .208 14.972 .413

6.4. Confirmatory Factor Analysis

Using confirmatory factor analysis we assessed (1) reliability (2) uni-dimensionality and convergent validity, and (3) discriminant validity on a system level.

Reliability is most widely measured using Cronbach’s alpha (α) (Davis, 1995). Cronbach’s α is based on the correlations among the predictors of the measure (Pedhazure & Schmelkin, 1991). The higher the correlations, the higher the alpha coefficient.

Uni-dimensionality is assessed by the fit indices, and convergent validity is assessed by the significance of t-value in the indicators. In addition, the model fit is tested using a variety of indices, including comparative fit index (CFI), normed fit index (NFI), root mean square error of approximation (RMSEA), and normed chi-square (Byrne, 1989; Bentler, 1990; Chau, 1997; Hair et al., 2006). Values of CFI, NFI, NNI, GFI and AGFI higher than 0.9 represent a good fit (Byrne, 1989; Joreskog & Sorbom, 1986; Papke-Shields et al., 2002). However values above 0.8 and close to 0.90 are also considered to be acceptable fit (Cao & Dowlatshahi, 2005). Typically values of RMSEA below 0.06 are deemed good (Hair et al., 2006). However a RMSEA value below 0.07 is also deemed to be acceptable fit (Steiger, 2007). A value of less than 3.0 for χ2/ d.f. represents reasonable fit (Segars & Grover, 1998; Papke-shields et al., 2002). Finally, critical N allows researchers to assess the fit of a model relative to other models with different sample sizes (Hoelter, 1983). A critical N lower than the actual sample size shows that CFA has sufficient power to detect problems causing poor fit (Joreskog & Sorbom, 1993).

To check for discriminant validity, a pairwise comparison was performed. A difference between χ2 values comparing a constrained with an unconstrained model that is significant at p <0/05 would indicate support for discriminant validity criterion (Joreskog & Sorbom, 1996).

7. Results

7.1. CFA Results

Table 8 in the appendix presents the correlation matrix. The confirmatory factor analysis was conducted for the measurement model. The final model indices fit the recommended criteria and demonstrated good uni-dimensionality (see Table 11). Similarly, the item loadings for each factor were significant for their corresponding t-values. Cronbach’s α coefficients were also all above 0.70, which provides evidence for good reliability as presented in Table 10.

Table 10. Reliability, confirmatory factor Analysis (CFA) factor loadings, t-statistics, and p-values Construct (Reliability: Cronbach’s α) Items CFA Loadings t-value p-value

Business strategy (0.813) BS1 0.745 3.994 0.000 BS2 0.763 4.504 0.000 BS3 0.724 3.274 0.000 BS4 0.79 5.198 0.000 BS5 0.666 2.200 0.033 BS6 0.685 2.490 0.026 BS7 0.67 2.231 0.031 BS8 0.753 4.107 0.000 BS9 0.738 3.845 0.000 BS10 0.708 2.943 0.007 BS11 0.702 2.843 0.008 BS12 0.669 2.203 0.031 BS13 0.779 4.868 0.000 BS14 0.846 5.427 0.000 BS15 0.742 3.900 0.000

Cloud computing (0.796) CC1 0.656 2.137 0.035 CC2 0.783 4.904 0.000 CC3 0.759 4.394 0.000 CC4 0.787 5.013 0.000 CC5 0.732 3.578 0.000 CC6 0.76 4.469 0.000

Trust (0.801) T1 0.773 4.827 0.000 T2 0.685 2.420 0.027 T3 0.731 3.346 0.000 T4 0.78 4.894 0.000 T5 0.717 3.136 0.000

Table 11. Summary of model fit indices

N=136

λ2

df λ2/df GFI AGFI NNI CFI NFI RMSEA Critical N (p<0.001) Recommended

values <3 >0.90 >0.90 >0.90 >0.90 >0.90 <0.08 < N

Fit indices values

(Model 1) 203 111 1.83 0.88 0.87 0.90 0.92 0.90 0.074 104

Fit indices values

(Model 2) 169 97 1.74 0.89 0.90 0.92 0.94 0.92 0.062 99

Table 11 provides fit indices for both model 1 and model 2 which incorporate moderating variables. NNI, CFI, and NFI are all well within the good fit range of greater than 0.90. Further the λ2/d.f. is well below the 3.0 and critical N is below our sample size of 136 suggesting good fit.. Finally GFI and AGFI also have acceptable fit very close to the 0.90 threshold and RMSEA is below 0.08 indicating acceptable fit as well.

7.2. Hypotheses Testing Results

To test hypotheses 1-5 in the proposed framework, structural equation modeling was used to assess model fit and path coefficients, as well as corresponding t-values. Table 11’s indices suggest an overall good fit to the baseline model, not taking into account inter-organizational trust’s and business strategy’s moderating role in the relationship between cloud computing use and information sharing.

Table 12. Standardized SEM results for PATH list (Maximum Likelihood Estimation)

Hypothesis Path Estimate t-value p-value H1 Business strategy -> cloud computing 0.375 3.613 0.00035 H2 Business strategy x Cloud

computing use -> Information

sharing 0.279 2.993 0.00214

H3 Cloud computing use -> Information sharing

0.412 4.375 0.00003

H4 Trust x Cloud computing use

-> Information sharing

0.248 2.541 0.00710

H5 Information sharing -> Supply chain performance

0.503 4.679 0.00002

Table 13. Summary of Hypotheses Tests Hypothesis Supported? Significance level H1: Business strategy positively influences cloud computing use. Supported 0.001

H2: Business strategy moderates the relationship between cloud computing use and information sharing.

Supported 0.01

H3: Cloud computing use positively influences information sharing. Supported 0.001 H4: Trust moderates the relationship between cloud computing use

and information sharing. Supported 0.01

H5: Information sharing positively influences supply chain performance.

Supported 0.001

The results of Tables 12 and 13 provide support for hypothesis 1-5. Hypothesis 1suggesting business strategy positively influences cloud computing use is supported at the α= 0.001 significance level (β= 0.375, t-value= 3.613). We also found support for hypothesis 2 examining the moderating role of business strategy on the relationship between cloud computing use and information sharing at the α=0.01 significance level (β=0.279, t-value=2.993). Hypothesis 3 examines the relationship between cloud computing use and information sharing which was found significant at the α=0.001 significance level (β=0.412, t-value =4.375). Hypothesis 4 examines the moderating role of trust on the relationship between cloud computing use and information sharing and is supported at the α=0.01 significance level (β=0.248, t-value=2.541). Finally we found support for hypothesis 5 suggesting information sharing positively influences supply chain performance at the α=0.001 level (β=0.503, t-value=4.679).

8. Discussion

Identifying information technology that is useful in increasing information sharing among supply chain members is crucial in an increasingly complex global context. Thomas et al. (2011) interviewed a variety of supply chain management professionals and asked them, “If we gave you a magic wand and granted you just one wish, what would you wish for to improve your supply chain?” Many supply chain management professionals suggested that while they believed supply chain partners were willing to share critical information, system limitations prevented effective collaboration (Thomas et al., 2011). The end result of these sub-optimal systems was poorly informed decision making, which led to poor supply chain performance (Thomas et al., 2011). Thus, supply chain

professionals are in need of more research incorporating effective information technology that can perpetuate the relational aspects of supply chain management, including information sharing.

Along with this, supply chain professionals have called for research to focus on improving communication and information exchange among supply chain partners (Thomas et al., 2011). Both inter-firm and intra-firm struggles were identified and described as supply chain problems (Thomas et al., 2011). Many of the participants in the study suggested seamless flow of information was essential in an efficient and effective supply chain (Thomas et al., 2011).

In answering these calls for research, this paper sought to answer several questions: How does business strategy impact cloud computing use and does it moderate the relationship between cloud computing use and information sharing? How does cloud computing use impact information sharing among supply chain partners? Does trust have an impact on the relationship between cloud computing use and information sharing? And how does information sharing via cloud computing technology impact supply chain performance in an operational and relational sense?

In examining the first couple of questions, we found that each strategy had an impact on the way cloud computing was used and also impacted the way cloud computing was used to increase information sharing. All four companies placed an emphasis on cost reduction and efficiency seeking methods in the defensiveness strategy type. Additionally, the vast cost savings benefits provided by cloud computing technology were stressed during each of the interviews. While some companies were conservative in decision making, others were more prone to taking greater risks. The conservative organizations opted for private cloud computing for security measures, while the more risk taking companies gradually became involved in public cloud use thereby impacting the way information was shared among supply chain entities. Cloud computing was also used as a tool for increasing market territory and information flow between new subsidiaries. Firms higher in pro-activeness noted the pro-environmental impact that cloud computing provides through reduction of the carbon footprint via reduced energy use. Additionally, cloud computing provided a platform for problem solving strategies, particularly through communication and mirroring of a company’s strategy with regard to short-term versus long-term focus.

We also found all the cases implied that cloud computing greatly enhanced information sharing among supply chain partners. Cloud computing provided firms the ability to share information internally and externally throughout their companies and supply chains. That being said it was only through the alignment with the business strategy that cloud computing provided a basis for secure, efficient and effective information sharing.

Further we found several of our cases indicated security issues were prevalent with the use of cloud computing technology, especially through public cloud use. While this may be the case for some of the respondents, other respondents did not indicate trust as a consequential facet in cloud computing use. Various research has outlined that although security is important in the use of cloud computing technology, measures to address these issues are being taken, including private cloud use. A growing number of younger individuals are becoming aware of cloud computing and its potential benefits, mitigating some of the trust concerns with the cloud.

Lastly, there were several topics discussed regarding information sharing, including information sharing support technology, content and quality. These elements are crucial to information flow throughout the supply chain (Zhou & Benton, Jr., 2007) and ultimately supply chain performance (Zhou & Benton, Jr., 2007).

Along with our case study analysis we also found empirical support for each hypothesis using a survey of 136 firms. It was found that business strategy has both a positive impact on business strategy as well as a moderating role on cloud computing use and information sharing. Further, trust was also found to moderate the relationship between cloud computing use and information sharing. Moreover, the positive impact that cloud computing has on information sharing ultimately leads to greater supply chain performance. Using both case study analysis and survey analysis provide triangulation of results in order to provide researchers and managers a practical model for optimizing information sharing and supply chain performance via cloud computing use, alignment with business strategy and adequate inter-organizational trust.

This study provides a foundation not only for how strategy impacts cloud computing use, but how cloud computing use impacts relational aspects of supply chain management, and in turn how this impacts supply chain performance. Thereby providing both researchers and managers an empirically validated model, rigorously tested through both case study analysis and survey analysis, focused on optimizing information sharing and supply chain performance.

9. Conclusions and directions for future research

This study provides an in-depth look at how four companies of varying sizes and purposes use cloud computing technology and how it impacts relational factors like information sharing among supply chain members. We used case study methodology, given the recentness of cloud computing technology and a lack of empirical background on how it impacts relational aspects of supply chain management, including information sharing and trust. We also used survey methodology to empirically examine our proposed model. Like all studies this analysis is not without specific limitations.

First, our case study analysis is composed of four organizations. Additionally, we survey specific companies in the transportation industries. Although this provides needed empirical support, the breadth of organizations does not allow for generalizability of results to a larger scope of organizations. Further, our case study and survey results were based on individuals from the U.S.. Future research is encouraged to look at a larger number of industries as well as countries in order to assess the impact of cloud computing on information sharing and how business strategy and inter-organizational trust moderates this relationship.

Further, we provide evidence of cloud computing use impact on information sharing in a broad sense. Future research should analyze how different services provided by cloud computing can help impact information sharing. Questions such as “does public vs. private cloud computing lead to greater information sharing” and “Does different payment arrangements impact the use of cloud computing to optimize information sharing?” might provide interesting insights to both researchers and managers alike.

Despite these limitations, this paper does provide a first step in the direction of understanding the state of the art information technology and how it ultimately optimizes information sharing and supply chain performance. More future research is encouraged to adequately assess this growing paradigm that is progressively being adopted by a variety of industries.

10. Appendix

Table 3. Protocol

Questions Reference Business Strategy Adapted

using information from: Miles & Snow (1978), Cao et al. (2011); Ellram et al. (2007)

1. Is cost reduction or efficiency seeking methods a priority for you firm? 2. How does this method impact your use of cloud computing technology? 3. How would you assess the way your company handles risk in the decisions that you make? 4. How has this impacted your overall usage of cloud computing technology? 5. What is your perception of risk associated with cloud computing technology? 6. How does your firm react to changing market positions in comparison to your competition 7. How does your reaction to changing market positions impact your overall cloud computing usage? 8. How does your company respond to changing environmental trends? 9. How does this response impact your overall cloud computing usage? 10. Does your company actively seek out market opportunities available to you? 11. How would you assess the problem solving behavior of your firm dealing with supply chain management issues? 12. How does this behavior impact your use of cloud computing usage? 13. In strategic decisions, does your firm focus on effectiveness (long term) or efficiency (short term)? 14. How does this impact your use of cloud computing technology? Cloud Computing Adapted

using information from: Foster et al. (2008), Mell & Grance (2009), Ellram et al. (2007)

15. How has cloud computing technology impact your overall performance in terms of overall competitive advantage? 16. How has on demand information provided by cloud computing impact information sharing and the relationship among you and your supply chain partners? How has it impacted your firm in terms of overall competitive advantage? 17. How has having pay as you go service provided by cloud computing impacted information sharing and the relationship among you and your supply chain partners? How has it impacted your firm in terms of overall competitive advantage? 18. How has having massively scalable information services provided by cloud computing impacted information sharing and the relationship among you and your supply chain partners? How has it impacted your firm in terms of overall competitive advantage?

Information Sharing Adapted using information from: Zhou & Benton, Jr. (2007)

19. Are there any concerns about the cloud that affects your information sharing among you and your supply chain partners? 20. How would you assess the overall information sharing capability that your firm has with supply chain partners? Including quality, content of the information 21. How has cloud computing impacted information sharing in your organization?

Trust Adapted using 22.How would you assess the relationship you have with your supplier in terms of your belief of their credibility, dependability and desire to do

good? How has this relationship impacted information sharing between you and your supply chain partners? How has cloud computing impacted this relationship?

information from: Zhang et al. (2011), Mayer & Gavin (2005)

Supply Chain Performance Adapted using information from: Kroes & Ghosh (2010), Chen & Paulraj (2004), Lee et al. (1997a,b)

23. How would you assess the performance of your supply chain? 24. How would you assess your company’s relationship with your suppliers? 25. How would you assess the accuracy of demand forecasts in your firm? 26. How has the following impacted the accuracy of your demand forecasts: relationship and information sharing with you suppliers?

Table 5. Case study evidence Companies Business strategy → Cloud

computing use Business strategy x Cloud computing use

Cloud computing → Information sharing

Trust x Cloud computing use Information sharing → Supply chain performance

Company Transport

Company Transport mitigates risk associated with cloud computing by running risk assessment and using private as opposed to public cloud computing. Company Transport focuses on an aggressive approach due to increasing cost pressures, government regulations and inflated fuel prices. In response they use cloud computing in order to lower costs to pass onto their customers. Company transport has a strong proactive stance on protecting

Company transport uses cloud computing to facilitate the following: enterprise application integration, greater availability of strategic and tactical data and ease of access to information allowing greater response to customer needs.

Company transport believes security, trust and reliability of the platform is fundamental to maintaining service level agreements that ultimately impact information flow and business

For company transport information flow is sequential and reciprocal, they use cloud computing as a way to reduce uncertainty and collaboration. This improves information flow and indirectly impacts supply chain performance. Likewise, information sharing helps to prevent, detect and resolve problems in the supply chain creating efficiency in collaboration.

and preserving the environmental and uses cloud computing as a means of reducing their carbon footprint and optimizing corporate resources. Cloud computing also provides a platform for company transport to support their objectives in the short term as well as the long term by using cloud computing to run several operations simultaneously saving time and money.

Company GPS

Company GPS focuses their strategic priorities on innovation and vertical integration. They use cloud computing as an efficient and cost effective platform to provide high quality services to various functional areas and external partners.

Company GPS uses cloud computing which provides a platform for facilitation in globalization efforts.

Company GPS fundamental belief is that buyers and suppliers come together for mutually beneficial reasons based on relationship and value exchange. Moreover, before sharing information trust has to be established between supply chain partners.

Company GPS suggests that through collaboration between customer and suppliers forecast accuracy is improved which alleviates the bullwhip effect.

Company Retail

Company retail has a strategy involving a reduction of costs and efficiency and uses cloud computing’s virtual services. Company retail has a strong aggressiveness approach and uses cloud computing to keep applications in sync with different locations simultaneously in order to keep track on the constantly changing market. Company retail also has a focus on sustainability and reducing their carbon footprint, cloud computing has provided a means of reducing energy usage.

Company retail considers themselves conservative. They use a private cloud to share private information with only those needing access. This reduces potential security breaches in their information sharing.

Company retail shares information via cloud computing by allowing a vendor to obtain information including purchase order, routing and status of orders and payments through the cloud. It also centralizes information for vendors to gain information easily no matter where they are geographically.

Company retail feels a need to trust their partners before sharing information. When problems occur, information sharing ultimately reduces.

Company retail uses vendor portals in the cloud as gateways to information flow between supply chain partners. This provides a foundation for building and enhancing the relationship between themselves and their vendors.

Company Company truck focuses on Company truck considers

Truck cost reduction and efficiency and uses infrastructure as a provider to replace physical servicers to run applications on. This has led to a cost reduction of 95, 000. As for risk, company truck feels that the cost benefits of cloud computing far outweigh the risk. To mitigate risk they don’t store secure data in the cloud. Company truck has a high aggressiveness strategy due to constantly changing regulatory issues. They use cloud computing to conduct computations in minutes that would normally take hours and likewise can maintain an adequate service level by using cloud computing through greater flow of information

themselves conservative. Likewise they limit the amount of information shared on the cloud. For example, customer credit card information is not provided in order to reduce the likelihood of potential fraudulent activity.

Table 6 Questions from survey & supporting literature Construct Variables Items Citations Business Strategy Defensiveness I believe my company should use

cost control systems for monitoring performance. (agree or disagree)

Adopted from Venkatraman (1989)

I believe my company should use production management techniques. (agree or disagree)

Risk Aversion I believe my company would be one that maintains conservative decision making. (agree or disagree)

I believe my company should approve projects on a “stage-by-stage basis” rather than with “blanket” approval. (agree or disagree)

I believe my company should support projects where the expected returns are certain. (agree or disagree)

Aggressiveness I would rather my company sacrifice profitability to gain market share. (agree or disagree)

I would rather my company gain market share at the expense of sacrificing profitability. (agree or disagree)

I would rather my company seek a market share position at the expense of cash flow and profitability. (agree or disagree)

Proactiveness I believe my company should constantly seek new opportunities related to present operations. (agree or disagree)

I believe my company should be the first one to introduce new brands or products in the market. (agree or disagree)

Analysis I believe that information systems provide support for decision making. (agree or disagree)

I believe that my company should use planning techniques. (agree or disagree)

I believe that my company should use management information and control systems. (agree or disagree)

Futurity I would emphasize basic research to provide my company with future competitive edge. (agree or disagree)

I believe my company should use formal tracking of significant general trends. (agree or disagree)

Cloud Computing Pay as you go (Indicate the importance to you of) pay-as-you go service

Adapted from Froehle & Roth

provided by cloud computing technology

(2004); Based on information provided by Rochwerger et al. (2009); Armbrust et al. (2009)

I believe the pay-as-you-go service provided by cloud computing is useful to companies. (agree or disagree)

Massively Scalable (Indicate the importance to you of) massively scalable service provided by cloud computing technology

I believe the massively scalable service provided by cloud computing technology is useful to companies. (agree or disagree)

On Demand Access (Indicate the importance to you of) on demand access provided by cloud computing technology

I believe the On demand access provided by cloud computing technology is useful to companies. (agree or disagree)

Information Sharing Information Sharing Support Technology

(Indicate the importance of) The use of information sharing support technology between you and your supply chain partner

Adapted from from Zhou & Benton, Jr. (2007)

(Indicate the importance of) The use of technology for communication between your company and supply chain partners.

Information quality (Indicate the importance of) information accuracy between you and your supply chain partner

(Indicate the importance of) information completeness between you and your supply

chain partner. (Indicate the importance of)

updating information frequently between you and your supply chain partner.

Assess how important information accessibility between you and your supply chain partner.

Information Content (Indicate the importance of) the appropriate information shared at the right time

(Indicate the importance of) necessary information content being shared between supply chain partners

Inter organizational Trust

Credibility (Indicate the importance of) your supply chain partner has high integrity

Adapted from Zhang et al. (2011)

(Indicate the importance of) your supply chain partner is reliable in making negotiation-related promises with your firm.

Goodwill (Indicate the importance of) your supply chain partner is respectful of you and others in your firm.

(Indicate the importance of) your supply chain partner is overall trustworthy

(Indicate the importance of) your supply chain partner treats your firm as a valued partner

Supply Chain performance

Delivery Cycle Time (Indicate the importance of) short delivery cycle times

Adapted from: Kroes & Ghosh (2010); Based I would prefer my company to

have short delivery cycle times (agree or disagree)

on information from Chen & Paulraj (2004) Manufacturing Cycle

Time (Indicate the importance of) short manufacturing cycle times

I would prefer my company to have short manufacturing cycle times (agree or disagree)

Product Shipped (Indicate the importance of) not having missing/wrong/ damaged/ defective products shipped

I would prefer my company to not have missing/wrong/damaged/defective products shipped (agree or disagree)

On time delivery performance

(Indicate the important of) on time delivery performance

I would prefer my company to have on time delivery performance. (agree or disagree)

Warranty/Returns Processing Costs

(Indicate the importance of) low warranty/returns processing costs

I would prefer my company to have low warranty/return costs. (agree or disagree)

Communication (Indicate the importance of) communication with other supply chain partners.

I would prefer my company have communication with the other supply chain partners. (agree or disagree)

Interdependence (Indicate the importance of) involvement of key supply chain partners in decisions you make

I would prefer my supply chain partners have involvement in the key decisions that we make. (agree or disagree)

Long term relationship (Indicate the importance of) long term relationships with supply chain partners

I would prefer my company to have long term relationships with our supply chain partners. (agree or disagree)

Integration of Logistics (Indicate the importance of) logistics integration with supply chain partners

I would prefer my company have adequate logistics integration with our supply chain partners. (agree or disagree)

Table 8. Correlation matrix T1 T2 T3 T4 T5 IS1 IS2 IS3 IS4 IS5 IS6 IS7 BS1 BS2 BS3 BS4 T1 1.00 T2 .268** 1.00 T3 .135 -.027 1.00 T4 .188 .263** .032 1.00 T5 .041 .131 .044 .150 1.00 IS1 -.029 -.089 -.056 -.088 -.075 1.00 IS2 .113 .236** .220** .271** .159 .182* 1.00 IS3 .051 -.058 .089 .193* .178* .145 .394** 1.00 IS4 .145 .052 .182* .095 .161 .010 .202* .248** 1.00 IS5 .126 .060 .064 .070 -.059 -.075 .069* .093 .201* 1.00 IS6 .249** .118 .210* .133 .175* -.088 .293** .221** .064 .060 1.00 IS7 .259** .151 .140 .072 -.077 .065 .199* .201* .141 .062 .259* 1.00 BS1 -.064 -.082 -.012 -.027 -.113 .179* -.022 -.094 -.043 -.186* -.039 -.082 1.00 BS2 .029 -.107 .055 .081 .039 .054 .076 .101 .093 -.179 .004 .002 .490* 1.00 BS3 .141 -.021 .140 .039 -.117 .004 .130 .116 -.001 .013 .165 .062 .293* .410** 1.00 BS4 -.005 .003 -.149 -.062 -.017 .014 .027 .048 -.073 .043 -.031 .085 .021 .058 -.031 1.00 BS5 .146 .117 -.014 .351** .046 -.099 .306** .162 .107 -.110 .321** .291** .000 .104 .057 .066 BS6 .076 .099 -.190* .219* -.075 -.089 -.016 -.023 -.133 -.024 .069 .038 -.182 -.078 -.156 .334**

BS7 .084 -.020 .196* .127 .326** .009 .266** .264** .089 -.090 .310** .105 -.039 .228** .121 .119 BS8 .252** .053 -.019* .123 .038 -.048 .128 .213* .100 .030 .162 .089 -.013 .128 .111 .051 BS9 .121 .098 .023 .169* .009 .215* .117 .145 -.013 -.089 .079 .173* .125 .037 .039 .120 BS10 .190* .086 .173* .001 .054 .027 .366** .267** .185* .026 .225** .269** .035 .096 .031 -.008 BS11 .062 -.008 -.028 .179* .066 -.081 .113 .214* .183* .007 .101 .182* -.051 .046 -.003 .175* BS12 .045 -.030 -.021 .089 -.090 -.089 .068 .083 .097 .084 .009 .136 -.015 -.012 .124 -.031 BS13 .402** -.047 .008 .015 -.134 -.134 -.003 .195* -.007 .068 .178* .167 -.041 -.045 .254** .054 BS14 -.037 -.031 -.084 -.232** .128 -.063 -.138 -.069 -.074 -.170* .238** -.054 -.065 -.079 -.133 .080 BS15 .112 .023 -.157 .016 .097 .007 .013 .088 .104 .032 .161 .104 -.151 .047 -.107 -.095 SCP1 .145 .064 -.013 .003 -.059 .060 -.030 .050 .213* .029 .051 .102 .001 .102 .008 .008 SCP2 .204* .079 -.028 .115 .115 .019 -.092 .055 -.089 -.027 -.001 .286** -.014 .033 -.013 -.007 SCP3 -.060 .035 -.087 .164 .298** -.082 .010 .084 .013 -.082 .064 .062 -.033 .268** .100 .086 SCP4 -.099 -.131 -.132 -.060 .022 .336** .055 .147 .015 -.014 .052 -.084 -.078 .051 .003 -.062 SCP5 .075 .037 .070 .267** -.028 .183* .266** .087 .111 .181* .109 .224** -.002 .120 .156 -.072 SCP6 .018 .031 .063 .267** -.024 -.105 .152 -.032 .207* -.011 -.006 .009 -.132 .052 -.062 -.094 SCP7 .192* .012 -.058 .081 .064 -.040 .206* .135 .103 .001 .052 .142 -.035 .131 .153 -.015 SCP8 .284** .167 -.130 .178* .021 -.099 .165 .194* -.010 .067 .167 .271** -.113 .068 .018 .147 SCP9 .083 .152 .016 .289** .070 -.070 .172* .081 .120 .088 .110 .139 .032 .054 -.076 -.144 SCP10 .232** .056 -.105 .197* -.034 .151 .025 .024 -.040 -.049 .077 -.065 .003 .042 .063 .155 SCP11 .228** .174* -.039 .128 -.154 -.007 .065 -.154 -.021 .224** .153 .348** .007 -.053 -.062 -.091 SCP12 -.007 .081 -.084 .114 .471** -.076 .036 .101 -.018 .038 .105 .088 -.099 .064 -.093 .064 SCP13 -.033 .068 -.091 -.047 .155 .015 -.035 -.102 -.029 .084 -.128 .034 .001 .004 .046 -.125 SCP14 .260** .098 -.009 -.006 .026 .027 -.059 -.131 .134 .212* .199* .093 -.115 .002 .043 -.083 SCP15 -.034 -.050 -.003 .262** -.022 -.071 .106 .023 -.042 -.106 .029 .112 .082 .064 -.061 .107 SCP16 .048 .047 .078 .080 .108 -.012 .230** .020 .129 -.108 .206* .210* -.053 .062 .083 .123 SCP17 .121 .012 .078 .166 .156 -.067 .093 .128 .018 .036 .018 .271** -.057 .061 -.043 .052 SCP18 .061 -.009 .083 .297** .034 -.068 .202* .187* .257** .124 .101 .161 -.085 -.043 -.043 -.128 CC1 -.004 -.100 .077 -.089 -.140 -.074 .019 -.032 .148 -.059 .063 -.025 .012 .067 .039 -.083 CC2 .001 -.129 .128 .009 -.040 -.010 .142 .009 -.062 -.017 -.069 .079 -.052 .011 -.088 -.044 CC3 -.089 -.009 .027 -.079 -.048 .076 .020 .065 -.038 .040 -.069 .026 .011 -.073 .037 -.063 CC4 .015 -.123 -.030 -.094 -.084 .019 -.171* -.129 .003 -.024 .064 -.013 .139 .080 .110 .059 CC5 -.091 -.072 .117 -.062 -.024 .078 -.065 -.148 .028 .043 .002 .025 -.095 -.054 -.032 -.175* CC6 -.068 -.062 .063 .015 .075 .079 -.059 .023 -.123 .013 .093 .007 .023 .036 .139 -.052

Table 8 cont. Correlation matrix BS5 BS6 BS7 BS8 BS9 BS10 BS11 BS12 BS13 BS14 BS15 SCP1 SCP2 SCP3 SCP4 SCP5 BS5 1.00 BS6 .168 1.00 BS7 .297** .058 1.00 BS8 .174* .216* .177* 1.00 BS9 .123 .316** .114 .124 1.00 BS10 .181* -.046 .144 .170* .150 1.00 BS11 .184* .204* .217* .337** .227** .156 1.00 BS12 .056 -.110 .014 .085 -.040 .027 .081 1.00 BS13 .054 .058 -.005 .123 .054 .097 .134 .157 1.00 BS14 -.017 .115 .048 -.127 -.008 .061 .050 -.181* .192* 1.00 BS15 .242** .059 .083 .106 -.056 .240** .173* .061 .086 .286** 1.00 SCP1 -.020 -.074 .066 -.001 -.130 -.047 -.016 .178* .063 -.011 .063 1.00 SCP2 .116 .099 .119 -.044 .218* .070 .099 .046 -.010 -.016 .059 .094 1.00 SCP3 .134 .003 .276** .016 -.012 .135 .150 .010 -.042 .037 .079 -.029 .111 1.00 SCP4 -.036 -.050 .103 -.126 -.024 .079 -.142 .026 -.031 .040 .170 .218* .116 .163 1.00 SCP5 .213* .018 .208* .078 .243** .119 -.034 .179* -.023 -.027 -.025 .051 .008 .135 .198* 1.00 SCP6 .067 .117 .203* -.094 .012 -.010 .208* .215* .057 .021 -.104 .004 -.080 .103 -.130 .266** SCP7 .112 .130 .176* .244** -.003 .235** .159 .084 .026 -.064 .022 .068 .087 .060 -.033 .116 SCP8 .282** .193* .289** .140 .071 .203 .161 .132 .103 -.045 .059 -.093 .254** .156 -.008 .120 SCP9 .191* .162 .211* .089 .119 .211* .167 -.006 .009 .124 -.063 .004 .150 .116 -.110 .264** SCP10 .156 .158 .234** .118 .016 .025 -.011 .105 .042 .016 .101 .242** .038 .073 .113 .093 SCP11 .131 .153 .051 .090 .150 .094 .073 .105 .005 -.162 .065 -.025 .183* -.053 -.110 .258** SCP12 .020 .016 .321** .096 .080 .082 .196* .139 -.114 .139 .061 .028 .034 .451** .060 .268** SCP13 -.145 -.129 .060 -.162 -.004 .121 -.002 .053 -.079 -.042 .007 -.097 -.060 .273** .013 .173* SCP14 -.012 -.021 .085 -.001 -.014 .072 -.090 .067 -.013 .040 -.018 .066 .112 .184* .119 .251** SCP15 .269** .081 .181* .155 -.022 .048 .065 .102 -.104 -.022 .041 -.009 .040 -.032 -.029 .097 SCP16 .168 .114 .138 .047 .132 .197* .107 -.016 .053 .192* .015 .067 .080 .221** .077 .178* SCP17 .156 .079 .234** .168* -.031 .131 .067 .071 -.045 .031 -.051 .006 .135 .213* -.013 .193* SCP18 .200* .075 .196* .147 .080 .098 .296** -.047 -.025 -.068 .031 .002 .170* .096 .041 .202* CC1 .025 -.079 -.044 .042 -.251** -.062 -.124 .110 .049 .035 -.007 .035 -.031 -.094 -.032 -.135 CC2 .046 -.048 .041 .148 -.038 .173* -.002 .018 .062 .055 .020 -.047 -.043 -.007 -.034 .203* CC3 .004 -.169 .003 -.014 .013 .173* -.001 .158 -.043 -.032 -.004 .100 .096 -.073 .002 -.009 CC4 -.060 .023 .200* .028 .158 -.131 .013 .023 .156 -.010 -.120 .062 .129 -.062 .038 .064 CC5 -.135 -.014 .064 -.105 .067 -.051 -.029 .046 -.071 .020 -.093 .076 .102 .050 .235** .121 CC6 -.133 -.037 .084 -.033 .118 .033 .002 .101 -.086 .076 -.039 .018 .123 .244** -.065 .095

Table 8 cont. Correlation matrix SCP6 SCP7 SCP8 SCP9 SCP10 SCP11 SCP12 SCP13 SCP14 SCP15 SCP16 SCP17 SCP18 CC1 CC2 CC3 CC4 CC5 SCP6 1.00 SCP7 .212* 1.00 SCP8 .284** .231** 1.00 SCP9 .368** .247** .242** 1.00 SCP10 .105 .140 .262** .160 1.00 SCP11 .099 .095 .189* .251** .153 1.00 SCP12 .078 .023 .228** .234** .140 .088 1.00 SCP13 .067 -.005 .019 .099 -.139 .099 .480** 1.00 SCP14 .170* .209* .287** .118 .124 .119 .264** .226** 1.00 SCP15 .176* .146 .154 .167 .040 .013 -.035 -.095 -.059 1.00 SCP16 .177* .360** .098 .106 .132 .035 .090 -.049 .126 .139 1.00 SCP17 .196* .177* .372** .344** .128 .051 .368** .166 .240** .352** .191* 1.00 SCP18 .281** .199* .105 .473** -.021 .167 -.009 -.112 .058 .192* .266** .358** 1.00 CC1 .065 .060 -.072 -.009 -.073 -.122 -

.257** -.285**

.116 .182* -.032 .059 .054 1.00

CC2 .037 .058 -.009 -.019 -.110 -.026 .119 -.051 .082 .051 .063 .228** .117 .032 1.00 CC3 .129 .073 .023 -.071 .069 -.022 -.047 -.191* .066 .063 .000 .144 .082 .228** .115 1.00 CC4 .033 -.029 -.032 .114 -.063 .113 -.002 -.022 .151 .182* .072 .023 .049 .288** -.022 .137 1.00 CC5 .125 -.066 -.006 .192* .001 .152 .057 -.027 .107 -.153 -.007 .042 .216* .099 -.022 .229** .199* 1.00 CC6 .007 -.033 -.026 .138 .013 .078 .257** .046 .158 -.041 -.034 .079 .035 .041 -.062 .390 .229** .252**

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