![Sample our Information Science journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5940/TOC-Subject-Sample-2021-Communication-Studies.jpg"})
Abstract
Enterprise resource planning (ERP) software is a platform for innovation with high failure rates due to its complexity. In China, failure rates of ERP are also high, with key differences between China and Western countries in terms of development, cultural, and organizational structure. Even when Chinese firms successfully adopt ERP, many fail to assimilate ERP and consequently never experience the full benefits of the innovation. The purpose of this study is to examine the predictors of adoption versus assimilation in Chinese firms. The existing literature largely assumes a dichotomy of choices when implementing organizational innovations in business: technological evaluation and imitation. We argue that this dichotomy does not apply well to a Chinese ERP context. China has achieved tremendous success in manufacturing and industrial processes through technological leapfrogging offered by imitation. At the same time, Chinese firms are under increasing pressure to innovate. Therefore, we argue that forces of imitation and evaluation are likely both at play when Chinese firms adopt and assimilate innovations—including ERP. Accordingly, we examined how two behaviors, interorganizational social technology imitation and rational technology evaluation, influence Chinese organizations in adopting and assimilating ERP systems. Our findings suggest that both social technology imitation and rational technology evaluation are determinants of Chinese ERP adoption and assimilation. Hence, this study offers new ways for IT and innovation researchers to explore social behavior (i.e., imitation) in IT diffusion processes and to consider the merits or risks of such behavior alongside the conventional rational approach (i.e., evaluation).
Acknowledgment
The work described in this study was financially supported by the Research Grants Council of the Hong Kong Special Administration Region, China (Project no, CUHK4725/05H) and the National Natural Science Foundation of China (Project no. 71471125).
Supplemental File
Supplemental data for this article can be accessed on the publisher’s website at http://dx.doi.org/10.1080/07421222.2016.1267534
Notes
1. Chinese people also dislike certain characters that symbolize something undesirable. Typical examples are numbers such as “4” and “24,” which are synonymous with “dead” and “easy to die.” Not many Chinese people like their phone numbers, employee identification numbers, or residence numbers to be associated with these numbers. Such factors are not considered in Western ERP design.
2. Similarly, Rice et al. [Citation68] argued that the dichotomy between the rational and the social is artificial and perhaps unnecessary. Webster and Trevino [Citation87] even suggested bringing the two approaches together by incorporating factors from both theories.
3. In the field of management, for example, imitation research has developed several theories to explain organizational and individual imitation. Organizational theorists have attempted to explain the unique behavior patterns associated with imitation by referring to the “bandwagon effect” [Citation29], which is a diffusion process in which an organization’s leaders feel pressured to adopt an innovation due to the sheer number of other organizations that have already adopted it in earlier stages [Citation70].
4. In addition, many DOI studies (e.g., [Citation1, Citation50]) have used only these three variables.
5. In situations where clarification was required, the interviewers contacted committee members for confirmation after they had had a chance to review the relevant archives. In this way, we minimized the risks associated with response inaccuracy due to memory lapses.
6. The first completed survey instrument from each interviewer was carefully reviewed to assess the quality and reliability of the data collection. Any issue identified in this review process was discussed with the interviewer before he or she resumed the interviews. Then, 56 surveys were randomly chosen for validation. The interviewees were contacted by the project supervisor, who randomly selected a few items from the questionnaire for the interviewees to reanswer. This validation process ensured not only data reliability but also that the interviewees to whom responses were attributed had actually been interviewed. Although this measure was implemented on a small scale, we found little deviation between interviewees’ first and second responses and no fault associated with the interviewers.
7. First, all student interviewers were briefed on the potential side effects of cross-sectional data. Thus, they were asked to mark on the questionnaire if an informant had been unsure or hesitant in their responses. These marked questionnaires, although limited, were followed up for validation. Second, the interviewees had to be senior executives, key ERP decision makers, or educated ERP professionals serving on an ERP steering committee to enhance response quality and minimize response bias [Citation47, Citation75]. Third, the interviewees were asked to provide documentation of ERP adoption and assimilation, if possible, as a secondary data source. These documents were used in validating their survey responses. Last, we performed statistical analyses on CMV, and compared early and late adopters to ensure the validity of our cross-sectional data.
8. Although there are other potential aspects of DOI, these three dimensions are the most widely used. DOI research in the past few decades validated that a large number of innovation characteristics were critical to adoption and diffusion of innovations [Citation71]. However, it generalized the relationship between 25 innovation characteristics and adoption and diffusion from their meta-analysis of seventy-five research articles. They identified ten characteristics that were most frequently studied by researchers: compatibility, relative advantage, complexity, cost, communicability, divisibility, profitability, social approval, trialability, and observability. Of these ten characteristics, compatibility, relative advantage, and complexity were consistently found to be significant. Since this time, many DOI research studies in the information systems field have employed these three variables in their innovation adoption and diffusion studies [Citation9, Citation32, Citation48]. Therefore, in our study, only these three aspects were used to represent DOI. It is clear that these three aspects are distinct and can move in different directions theoretically; thus, based on leading guidelines on formative construct specification and measurement, we specified DOI as a formative construct with compatibility, relative advantage, and complexity as its subdimensions.
9. This is particularly true not just for SOEs but for firms that are shielded from international competition such as in oil and gas, technology, steel production, and the like. In fact, collective and locally government-owned enterprises are shown to be even less efficient and less competitive than SOEs [Citation40].
Additional information
Notes on contributors
Vincent Siuking Lai
Vincent Siuking Lai ([email protected]) is a professor of management information systems (MIS) at the Faculty of Business Administration of the Chinese University of Hong Kong. He received his Ph.D. in MIS from the University of Texas at Arlington. His research focuses on innovation assimilation, online auctions, technology herding, virtual collaboration, and global IS strategy. He has published in Journal of Management Information Systems, Communications of the ACM, Decision Sciences, Decision Support Systems, and many others.
Fujun Lai
Fujun Lai ([email protected]; corresponding author) is an honorary professor at Soochow University, China and the McCarty Distinguished Professor of MIS at the College of Business at the University of Southern Mississippi. He received his Ph.D. from the City University of Hong Kong. His research interests include e-commerce, enterprise information systems, supply chain and logistics management. He has published in Journal of Operations Management, Decision Sciences, Communications of the ACM, and Decision Support Systems, and others.
Paul Benjamin Lowry
Paul Benjamin Lowry ([email protected]) is a professor of information systems at the Faculty of Business and Economics at the University of Hong Kong. He received his Ph.D. in management information systems from the University of Arizona. His research interests include organizational and behavioral security/privacy issues; HCI and decision sciences; e-commerce and supply chains; and scientometrics. He has published in Information Systems Research, Journal of Management Information Systems, MIS Quarterly, Journal of the AIS, Information Systems Journal, and many others. He is the coeditor in chief of AIS Transactions on HCI, and has served on various editorial boards and as the track chair in various leading conferences.