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The technological innovation of Software as a Service-Enterprise Resource Planning (SaaS-ERP) opens several relative advantages, which may be realized by choosing the proper operation mode. Thus a company looking for a new ERP system faces the question: When and under what conditions does it make sense to choose a SaaS-ERP system? The paper aims to discuss these issues.

The relative advantage criterion of the diffusion of innovation theory, derived as operation mode differences, determine the conditions under which SaaS- or On-Premise-ERP is preferable: a classification of all main systemic operation mode differences between SaaS and On-Premise for the more complex ERP systems is presented. The systemic differences were identified by analytic generalization using triangulation between a literature review and a multiple case study with four ERP producers.

The most significant decision factors between ERP operation modes are flexibility, customization, cost, and operation and maintenance. General strategies have been derived by bringing the theoretical reasons together with the operation mode difference criteria. Typical criteria for selecting SaaS-ERP are a lack of IT-capacity or capabilities, as well as high need for flexibility, due to business development, seasonality, growth, collaboration and/or expansion. On-Premise-ERPs should be selected if specific or strategic resources would be outsourced or when major customization is a need.

Case research is limited in that it reveals only ERP producers’ view and omits outlying cases.

The findings implicate that ERP selecting customers should consider and expand their criteria for ERP selection by operation mode criteria.

The classification of the most essential operation mode differences allows, for the first time, ERP selecting customers to design selection strategies. ERP selecting companies should strategically favor the operation mode that best suits their respective organizational characteristics so as to obtain the best possible support from the ERP operation modes.

The purpose of this paper is to explain how enterprise resource planning (ERP) implementation evolves by cloud computing in different industries with different delivery models of cloud ERP. This paper also investigates infrastructure as a service (IaaS) as a delivery approach for cloud ERP. Case research on IaaS is rarely found in the literature. In addition, this paper intends to reveal how this transformation from on-premises to the cloud would influence the ERP implementation process.

A multiple-case study is conducted to identify the different deployed models of cloud ERP systems in the implementation projects. The influences of emerging cloud computing technology on ERP implementation are investigated by interviewing consultants related to the projects.

The findings illustrate that not only software as a service (SaaS) but also IaaS and platform as a service cloud computing services are widely applied in cloud ERP implementation. This study also indicates that certain technical limitations of cloud ERP might have a positive effect on the outcome of ERP implementation.

This study investigates how cloud computing influences ERP implementation from different aspects. The result identifies both SaaS and IaaS as two different approaches widely adopted in cloud ERP implementation. Besides, this study has discussed in-depth and analyzed these two cloud ERP paradigms in five factors, including functionality, performance, portability, security, cost and customization. The classification and suggestions are original to the literature.

After reading and discussing this case, students will learn to identify the content and context of enterprise resource planning (ERP) implementation that is important from an operations standpoint. Through this case, student will discuss and evaluate the scenarios of ERP implementation arising from different deployment alternatives. Students will also learn to comprehend the case organization’s unique operational context and explore the challenges of introducing change into workplace environment and stakeholders’ overall expectations.

This case introduces students to the dilemmas of managerial decision-making that large companies face while implementing organization-wide technological upgrades, such as ERP. The case is set at a time point where ABC Mining Company – a large public-sector mining company – was trying to identify the most optimal ERP option based on its organizational structure and organizational processes. The information related to ABC’s organizational context included their business, structural and operational scenarios at the time. The information related to ABC’s stakeholders’ expectations reflected their perception about ERP and future implications. The information related to managerial conflicts reflected the understandings of the managers, in terms of need for ERP, needed skill to handle ERP and different types of ERP implementations that others have adopted. The case calls students for extensive analysis of the gathered information to identify and evaluate impacts and risks of all possible ERP alternates, and finally pick upon the most optimal ERP alternate. The case assumes a live 90-min class session conducted by an instructor. The instructor is recommended to assign the case to students for mandatory pre-reading before coming to class. The instructor is provided with a teaching plan to navigate the case.

The case is designed as an introductory case for an undergraduate or a graduate course pertaining strategic decision-making of ERP systems implementation.

Teaching notes are available for educators only.

CSS 11: Strategy.

Switching to public cloud enterprise resource planning (ERP) systems not only provides financial and functional benefits to organizations, but also results in sunk costs of incumbent systems and uncertainty costs of cloud systems. The purpose of this study is to investigate the enablers and inhibitors concerning switching to cloud ERP systems at the organizational level.

Data were collected from 212 top managers and owners of the enterprises in Taiwan, and 10 hypotheses were examined using structural equation modeling.

Technological (system quality), organizational (financial advantage), and environmental contexts (industry pressure) are found to be the antecedents of switching benefits. Perceived risk of cloud ERP systems and satisfaction with and breadth of use of incumbent ERP systems are found to be the predictors of switching costs. Switching benefits positively affect switching intention, but switching costs negatively affect switching intention.

This study develops a theoretical model grounded in a set of theoretical foundations, including two-factor theory, technology-organization-environment (TOE) framework, information systems (IS) success model, and expectation confirmation theory (ECT). Two-factor theory is used to characterize switching benefits and costs that affect switching intention. Technological factors come from IS success model, and the factors affecting benefits are organized based on TOE framework. Sunk costs of incumbent ERP systems are developed based on ECT.

Different from previous studies on cloud computing adoption, this study provides insights into switching intention to cloud computing. The study also proposes an integrated model grounded in multiple perspectives to explain organizations' decisions to switch to cloud ERP systems. These findings help cloud service providers better understand how to promote cloud ERP adoption from technical, organizational, and environmental perspectives.

As social networking services are popular, the need for recognizing reliable people has become the main concern. Quantifying the relationships between the users of social networks is also one of the important challenges with the increasing number of users. So, trust plays an important role in social networks in order to recognize trustworthy people. The purpose of this paper is to propose an approach to recognize trustworthy users and protect users from abuse by untrustable users.

In this paper, the authors suggest a method to measure the trust value between users of social networks based on call log histories such as abundance, novelty, and sincerity and quality of service (QoS) requirements such as accessibility, response ability, tend to respond, and agility. After that, the authors calculate error-hit, precision, and recall to evaluate the trust value.

The results indicate that the proposed approach has better performance in terms of error-hit, precision, and recall than FIFO, combined, QoS-based, and call log-based method.

In this paper, the trust issue in social networks is pointed out and a new approach to evaluate the trust value is proposed based on call log histories and QoS requirements.

This study aims to empirically validate the determinants of cloud adoption in small and medium enterprises (SMEs) in India and examine its impact on their economic performance.

An integrated theoretical model interplaying technological, organizational and environmental aspects were applied for analyzing the variation in factors. Using data from 317 Indian SMEs, we have applied confirmatory factor analysis and structural equation modeling to test the hypotheses.

The results demonstrated that perceived usefulness, perceived ease of use, technology readiness, top management support and trust were the influencing drivers of cloud adoption in SMEs in India. Compared to previous studies, we did not find compatibility and competitive pressure as significant, suggesting that there was no single set of factors influencing technology adoption. Economic performance achieved by reduced transaction costs formed the basis of favorable adoption.

The integrated model can provide space for new dimensions based on the category and geography of the SMEs. The paper does not address the supply-chain perspective of cloud adoption.

The study directs the firm owners to visualize business logic by creating a digital ecosystem. Further, the model guides the stakeholders, including cloud service providers, to contribute to the economic proficiency of the SMEs.

The paper empirically validates a model integrating both the drivers and consequences of cloud computing adoption as a unique study. Findings indicate that the usage of metrics such as return on investment and system efficiency form a part of the technology system approach.

The purpose of this paper is to evaluate the suitability of cloud computing for small and medium-sized enterprises (SMEs) in India.

Literature review is used to identify benefits, challenges, and factors concerning usage and adoption of cloud computing by SMEs. A conceptual framework was developed based on the existing theoretical models and factors identified from the literature. A survey based on questionnaire method was followed to collect data from 121 manufacturing SMEs in India. The conceptual framework was refined by using factor analysis, and multiple regression analysis was used to test the hypotheses.

Major benefits of cloud computing for SMEs include cost advantage, easy deployment process, easier access to latest information and communication technologies, automatic updates and upgrades, scalability, flexibility, and improved disaster recovery and back-up capabilities. The concern area includes perceived loss of control, vendor lock-in, security issues, reliability and availability issues, and internet connectivity and speed. The factors that are found significant include perceived benefits, top management support, competitive pressure, and perceived concerns. The model explained 73 percent of cloud computing adoption.

The study is expected to make significant contribution toward body of knowledge pertaining to information technology adoption in SMEs.

The study is expected to provide SMEs an insight into real benefits and challenges associated with adopting cloud computing. The model can help SMEs in evaluating their readiness for adopting cloud computing and can ensure successful outcome of cloud computing adoption in SMEs. Providers are also going to be benefited through their enhanced understanding of SMEs’ requirements.

The proposed framework incorporates all the relevant factors including perceived benefits, perceived concerns, and other organizational and environmental factors to improve model’s predictive power.

Centralization, which indicates distribution of decision-making power in organizations, is well-discussed in innovation literature as one of the influencing factors of innovation implementation. Motivated by a gap in enterprise resource planning (ERP) research, the purpose of this paper is to investigate the influence of centralization on the success of ERP implementation.

Centralization is characterized twofold: policy-related centralization (PRC) and work-related centralization (WRC). ERP implementation success is captured in terms of user acceptance and the use of the ERP system. Using organizational innovation theory, six hypotheses relating centralization, ERP implementation success, and organization size are built and tested using data gathered from 51 Indian organizations that implemented ERP. The data are analyzed using partial least squares-structural equation modeling.

User acceptance is significantly inhibited by PRC. WRC has a negative influence on use. The negative influence of PRC on acceptance is more pronounced in the case of larger organizations. On the whole, a decentralized set-up is favorable to ERP implementation success.

The study highlights the impact of a centralized management structure on success of ERP implementation and in doing so, it demarcates the varied influence of two types of centralization. It contributes to the scarce research on ERP implementation using the strong theoretical basis of organizational innovation. The findings highlight the implications of centralization to the implementation outcomes, for organizations embarking upon ERP.