Information And Communications Technologies Commerce Essay

Published: Last Edited:

This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.

Information and communications technologies (ICTs) have changed the way in which firms do business and create value. Many researchers focus on ICT systems and interaction with firms, such as information capability and business process re-engineering (BPR), and claim that ICTs increase firm competitiveness. For example, Sarker and Jagjit [1] and Ziaul, Faizul, and Ken [2] report that ICTs may change business practices to re-optimize business processes, which leads to increased efficiency and improved performance. Neirotti, Cantamessa, and Paolucci [3] find that ICTs help firms to improve their knowledge about customers and performance in the manufacturing industries in Italy. Rhim, Park, and Kim [4] show that adoption of ICTs may improve general financial performance, reduce functional area costs through business process outsourcing, customer relationship management (CRM), and supply chain management (SCM).

Despite the importance of ICT, most research has focused on one or two enterprise applications, such as electronic commerce or enterprise resource planning. Lee, Chu, and Tseng [5] argue that examination of one kind of technology is not a good approach to studying business reengineering. It ignores the mixed effects of various ICTs on BPR and does not offer a complete picture of the relationship between ICT adoption and BPR. In addition, ICT activities in firms are complicated, and may differ significantly across countries, but contributions of ICTs at the country level are rarely examined and compared. We agree with Limaye and Victor [6] that even as ICTs in business organizations around the world converge, the impact of their use may depend on national culture and on the specific environment in which they are embedded. Generalizations about the outcomes of ICT adoption cannot be made until research accumulates evidence of similar effects across different countries [7].

Based on the rich body of research on BPR and the adoption and diffusion of ICTs, Lee et al. [5] first propose an initial ICT-BPR model. Their survey results indicate that organizational innovation, market pressure and competitive intensity positively affect information technology adoption, which in turn trigger changes or business processes in terms of workplace, workforce, and business structure. Lee, Chu, and Tseng [8] extend the initial ICT-enabled BPR model to evaluate ICT-enabled BPR and business performance by investigating 377 senior information systems managers from top 2,000 Taiwan corporations. They find that ICT technologies facilitate firms in optimizing business processes, and business process re-engineering has significant positive impacts on internal process performance and corporate financial performance.

In this study, we further revise the ICT-BPR-Performance model and apply multiple-group structural equation modeling to test the revised model on data derived from cross-national research. The data are collected from the Business and Information Technologies (BIT) project, lead by researchers from the Anderson School of Management at UCLA. The main purpose of the BIT project is to study the impacts of ICTs on business practices in various countries over an extended period of time. Their findings would be valuable in understanding the complexity of ICT adoption and predicting outcome of business process reengineering.

The paper is organized in six sections. The second section provides an overview of past studies on ICT adoption and possible impacts on business process and profit. The third section presents an analytical framework for examining the relationship among ICT adoption, business process re-engineering, and performance, drawing from business, economics and organizational development literature. The data and methodology used in the study are discussed in section four, and the empirical results are presented in section five. The final section discusses the results, implications and limitations of the study.

2. Conceptual Background

2.1 ICT adoption and BPR

Business process reengineering is an approach that firms take to re-optimize business processes for the purpose of obtaining competitive advantage and enhancing business performance, such as cost saving, quality breakthroughs, better customer services, time reduction, and revenue increases [9]. In most BPR cases, ICTs play a critical role in reshaping business practices. For example, Morton [10] finds that ICT is an important enabler of BPR because ICTs permit the distribution of power, function, and control to wherever they are most effective, and further change the ways in which production, coordination activities, and data processing are carried out. Many experts [11-14] agree that ICTs could facilitate firm collection and analysis of information and development of strategic vision, as well as allow collaborative teamwork and determine the best approach for business process redesign. Firms sometimes need to change the organizational structure to align with the adopted ICTs to obtain positive business performance and better operational efficiency [15].

ICT application and its influence on BPR are related to many interconnected systems, such as organizational power and cultural fit [12, 16]. Lee et al. [5] suggest that ICTs change BPR in three dimensions. The first dimension is changes in the workplace. In many cases, ICTs enhance control and coordination and permit changes of the economics and functionality of the coordination processes [10]. For example, ICTs collapse space and time constraints and allow people to work outside the office, engage in non-face-to-face coordination activities at different locations and even in different time zones [1, 2, 10, 17, 18]. ICTs enable the staff to telecommute from home or other locations, send and receive multimedia data, exchange information, and accomplish tasks by using electronic mail, teleconference and various Internet-based cooperation tools. Communication and connectivity within an organization becomes more direct and cross-unit collaboration among geographically dispersed business units is increased [1].

The second dimension of ICT impact on BPR is changes in the workforce. ICTs activates a growing spread of automation throughout the company, taking in many business practices such as supply chain management, order management, customer service management. Automation in turn leads to manpower reductions, including both office staff and production workers [1, 2, 5, 19]. Contracting out programming, network management, customer services, and market research allows firms to make alliances with organizations that are more professional or labor-intensive [18, 20]. Responding to automation and outsourcing, ICT skills or knowledge become necessary requirements for employees and are the greatest problem when firms engage in BPR [21].

The third dimension of ICT impact on BPR is changes in organizational structure. ICTs are flexible enough to handle changes in the environment and business processes, which in the end leads organizational structural reform [14, 22, 23]. By sharing and exchanging information through ICTs, employees can directly report to managers and business units, diminishing the process of mediation and increasing cross-unit collaboration [1, 2, 24]. As a result, organizational hierarchies become flatter, and the degree of centralization of decision making has been changed [25, 26]. In addition, ICTs also enhance the information-processing capacity of managers [25] as well as increase their control [27].

2.2 ICT, BPR, and performance

Many researchers believe that new ICTs create better performance [1, 12, 18, 20]. Industrial economists [1, 28-30] assume that ICTs have direct impacts on productivity. They employ the structure-conduct-performance framework, follow traditional input and output mathematical calculation and use regression to predict how much of productivity is accounted for by capital and employment of ICTs. Some researchers argue that ICT is not a driver of performance per se, saying that it should be associated with higher performance if accompanied by organizational change [31]. That is, ICTs have a moderate effect on BPR, and BPR is then expected to re-optimize business processes, improving business performance [32-35].

BPR connotes the design of workflows and processes within and between organizations [36], and such fundamental reconsideration and radical redesign may achieve drastic improvement of organizational performance in such areas as costs and services [34]. In particular, Lee et al. [8] empirically evaluate ICT-enabled BPR and business performance by adopting the balanced scorecard approach [37]. The results indicate that ICT adoption directly triggers positive changes in business processes and organizational learning and growth, and indirect improvement of customer satisfaction and financial performance.

To evaluate ICT-driven performance, it is common to use objective profit data on stock returns and accounting metrics. Santhanam and Hartono [38] find that firms with superior IT capability indeed exhibit superior performance when compared to average industry performance in financial indicators, such as return on assets or operating income to assets. Francalanci and Morabito [31] use ROE and ROI indexes to test organizational absorptive capacity and analyze its effects on the relationship between IT and business performance in small and medium enterprises. Hendricks et al. [39] document the effect of investments in ERP, SCM, and CRM systems on a firm's stock price performance and profitability measures such as return on assets and return on sales. However, the financial benefits of these implementations yields mixed results. Many firms implementing multi-year, multi-million dollar ERP projects do not reap benefits from ICTs [40, 41]. Even when gains are realized, given the high levels of expenditure and effort, the benefits for businesses from ICT investments are relatively small [42-45]. Thus, how ICTs affect business re-engineering processes, and how ICT-enabled changes impacts business performance, remains a puzzle requiring further investigation.

Based on resource-based theory, Melville, Kraemer, and Gurbaxani [46] propose an integrative model of IT business value that comprises three domains: value generation process (e.g., IT & organizational resources, process & organizational performance, etc.), competitive environment (e.g., industrial and trading partner characteristics), and macro environment (e.g. country characteristics). The conceptual model describes how phenomena resident within each domain shape the relationship between ICT and organizational performance. Only partial models are tested on empirical data and the results show no persistent evidence of performance associated with ICT investments [31, 38, 47, 48]. They further classify performance into two parts: (1) business process performance: a range of measures associated with operational efficiency enhancement, e.g., inventory turnover [49], customer satisfaction [50], and on-time shipping [51]; and (2) organizational performance: IT-enabled performance impacts across all firm activities, e.g., operations measures (cost reduction, productivity enhancement), market-based measures (stock market value, Tobin's q) [52], and perceptual measures (usage metrics, balanced scored card) [8, 53]. This resource-based theoretical approach informs understanding of the linkage between the type of ICTs and the nature of business process and organizational performance impacts. However, such approaches are rarely linked to BPR and researchers have yet to reach consensus on the performance measurement standards.

We therefore investigate the moderating effect of ICTs on performance and examine how ICTs re-engineer business processes. As firms emphasize profitability more than productivity [54], we assess the performance from the perspective of profitability.

2.3 Hypotheses and Research Questions

ICT-enabled BPR often contributes to higher performance. ICTs re-engineer the organizational structure, workplace and manpower [1, 2, 5]. By employing ICTs, the organization structure becomes flatter with efficient decision making and the staff can work and cooperate by telecommunicating with each other outside the office [1, 2, 5, 24]. ICTs also allow organizations to function efficiently with less manpower [1, 2, 19]. We thus develop the following hypotheses:

Hypotheses 1a-1c: Workplace reform (WP) (1a), workforce reform (WF) (1b), and organizational structure reform (OS) (1c) all have positive and significant impacts on business profit (profit).

Hypotheses 2a-2b: Resource planning infrastructure (RPI) (2a) and e-commerce infrastructure (ECI) (2b) both have positive and significant impacts on workplace reform (WP).

Hypotheses 3a-3c: Workplace reform (WP) (3a), resource planning infrastructure (RPI) (3b), and e-commerce infrastructure (ECI) (3c) all have positive and significant impacts on workforce reform (WF).

Hypotheses 4a-4c: Workforce reform (WF) (4a), resource planning infrastructure (RPI) (4b), and e-commerce infrastructure (ECI) (4c) all have positive and significant impacts on organizational structure (OS).

Figure 1 presents the Cross-Nation ICT-enabled BPR model proposed by this study.

[Insert Figure 1. here] The Cross-Nation ICT-enabled BPR Model

The preceding theoretical arguments and our proposed model can be formally stated by the following system of simultaneous regression models.

3. Methods

Based on the preceding theories and hypotheses, this section details the subsequent constructs and questionnaire items, and the survey settings to collect the empirical data from the senior information systems managers of organization units that make independent decisions on information technology systems.

3.1 Instrument Development

The survey instrument for this study is developed using validated items from previous research. ICT adoption refers to respondent acceptance of an ICT. We distinguish among two types of ICT, resource planning infrastructure (including enterprise resource planning, business intelligence, content management, and supply chain management) and e-commerce infrastructure (including storage area networks and network attached storage, digital receipts, collaboration & portal tools, website and e-commerce, business process modeling, and enterprise Instant messaging). Respondents are asked to indicate their acceptance of the abovementioned ICTs.

BPR refers to dramatic and distinct management reforms and redesign of workflow as a result of ICT adoption. It is assessed from three dimensions: Organizational structure, workplace, and workforce. Organizational structure reform refers to changes of organizational hierarchy. The measurement comprises a combination of the instruments used in Sarkar and Singh [1], Karmarkar and Mangal [55], asking respondents if ICT adoption decreases the number of middle level managers, makes the organization flatter, and increases managerial control [55]. Workplace reform describes changes of places where people work and engage in non-face-to-face coordination activities. A scale for workplace is developed to ask individuals to answer 2 items asking whether they telecommute and teleconference [56], asking whether their companies have reduced manpower as a result of engaging in automation, outsourcing, and automated monitoring. Respondent also rate 2 items, "The need for IT skills at lower levels is going up," and "The IT function is shifting from staff to line", for this construct. Performance in this study is evaluated from the perspective of profits. The survey instruments developed by Karmarkar and Mangal [56] are using to ask respondents to rate 2 items about how they feel about technology impacts on the organizations in terms of financial profits and margins. All scale items are measured on a five-point Likert scale, where '1' represents 'strongly disagree', and '5' represents 'strongly agree'.

The final questionnaire, developed partially in accordance with the BIT project, includes two major parts. The first part is composed of twenty two questions as shown in Table 1. The second part contains information about the surveyed company, including size, industry type. The twenty two items in Table 1 stand for the variables that measure the theoretical constructs serving as predictors of the Cross-Nation ICT-enabled BPR Model in Figure 1.

[Insert Table 1 here]: Detailed Constructs and Questionnaire Items

3.2 Survey Settings

The research is conducted by obtaining responses from Chief Information Officers or senior information systems managers that make independent decisions on information and communications technologies systems in firms from Taiwan, the United States, Korea, and Chile. [1] Table 2 summarizes the sample sizes and demographics of each country. We selected these four countries for three reasons: (1) generalizability: that is, the countries broadly represent the international clusters; (2) construct equivalence: that is, the adoption of ICTs provides relatively similar experiences in terms of basic want / need fulfillment, for the business organizations in the four countries (and arguably many others); and (3) data availability: that is, the available BIT network that provides quality data for the four countries.

[Insert Table 2 here]: The sample sizes and demographics of each country

In Taiwan, questionnaires are mailed to 2,000 companies by systematically sampling the database of The Largest 5,000 Corporations. In Korea, the survey is sent by fax or delivered by interviewers depending on the location of the respondents. The collection process is managed by a reliable market research company. More than 50% of the respondents were at the managerial level. In Chile, the data has a weighting factor because 300 case samples were split equally among large, medium, and small firms (100 cases each, randomly selected in each category). To ensure proper representativeness of these 300 cases, they are weighted up/down according to the real distribution of these three sizes, since there are fewer small than large companies. In the United States, the survey was sent to a database of over 25,000 individuals across all industry sectors in the United States. The data is acquired from an independent entity that collects corporate data. The CIO are requested to complete the survey either by mail or on-line, where the survey questionnaire was also made available.

The sample consists of 382 respondents from Taiwan, 248 from the United States, 262 from Korea, and 301 from Chile. We exclude 40 samples from the public and media sectors from Taiwan, in which ICT adoption is low due to industry characteristics. It is worth noting that this low response rate is common in research that attempts to obtain data from top management [57].

Among these organizations, the largest industry in Taiwan is "Manufacturing (38.3%)", followed by "Service (28.1%)". Among these organizations, those with fewer than 100 employees are categorized as small organizations (35.5%), while organizations with more than 1,000 employees are considered large (18.7%). In the United States, the largest industry is "Service (56.5%)", followed by "Manufacturing (31.5%)", employing from fewer than 50 to more than 1,000 workers. Among the manufacturing organizations, organizations with fewer than 100 employees are categorized as small organizations (7.2%), while organizations with more than 1,000 employees are considered large (39.7%). In Korea "Service (63.7%)" firms are followed by "Manufacturing (27.5%)", employing from fewer than 50 to more than 1,000 workers. Among these organizations, organizations with fewer than 100 employees are categorized as small organizations (27.7%), while organizations with more than 1,000 employees are considered large (26.2%). In Chile, the largest industry is "Manufacturing (39.3%)", followed by "Service (28.7%)". Among these organizations, those with fewer than 100 employees are categorized as small organizations (78.4%), while organizations with more than 200 employees are considered large (8.6%).

4. Results

A more rigorous approach to modeling relationships between constructs, structural equation modeling (SEM) may offer a more holistic picture of ICT adoption, as relationships between business process reform and business profit can be examined simultaneously in one unified model. In addition to descriptive statistical summaries, multiple-group structural equation modeling was used to test the model. The SPSS 12.0 and AMOS 16.0 software packages were used for the statistical analysis.

4.1 Evaluations of the Measurements

Among the four countries, enterprise resource planning is the most popular information system in the resource planning infrastructure, while supply chain management systems are the least popular (Table 1). Website and e-Commerce are the most widely adopted ICTs in the e-commerce Infrastructure. Digital receipts are the least adopted ICTs in Taiwan, Korea, and the United States. Business process modeling is the least used in Chile.

4.2 Quality of the Proposed Model

Scale reliability and construct validity are tested with confirmatory factor analysis (CFA) [58] before assessing the hypothesized relationships shown in Figure 1. It is also necessary to identify equivalent phenomena when conducting cross-national research [59]. A separate CFA that involves raw data as input is performed for each of the four countries [60]. All constructs in the four samples are composed of identical items. Based on CFA results, we eliminate items that load on multiple constructs or have low item-to-construct loadings [60]. Then, the fit of the measurement model for each of the four countries is assessed [61]. As Table 3 shows, the loadings of items on their respective factors are highly significant (p < 0.01). The goodness of fit index (GFI), comparative fit index (CFI), and Bollen's fit index (IFI) range between 0.82 and 0.91 for each of the four countries. The root mean square of error approximation (RMSEA) values is 0.061, 0.067, 0.064, and 0.061 for Taiwan, US, Korea, and Chile, respectively. The results suggest that the data converge and the CFA model for all four countries fits the data adequately [58, 62].

[Insert Table 3 here]: Summary of reliability and validity index

To test if there are true cross-national differences in structural relationships between scale scores for further comparison, measurement invariance is conducted to rule out differences caused by systematic response biases or problems with scale artifacts, reliability, or nonequivalence [63, 64]. Following Mullen [62] and Steenkamp and Baumgartner [64], we perform a test of unconstrained model (Model 1). It produces χ2 =1,768.62 with 788 degrees of freedom (df) (Table 4). CFI is found to be 0.86 and RMSEA is 0.033. These fit indices indicate that the six-factor model is supported in all groups, meaning that the four countries exhibit the same simple factor structure. Each sample population can therefore use the same baseline model. The second model (Model 2) assesses whether the factor covariance are equal across the four countries by constraining the λ to be equal across groups. The results (Table 4) demonstrate that the chi-square difference between the simple structure model (Model 1) and the equal variance model (Model 2) is 135 with 48 df (p < 0.05). Although the chi-square test is significant (an indication of a poor fit), research relying exclusively on chi-square difference tests may suffer "from the same well-known problems as the chi-square test for evaluating overall model fit" [60, 64, 65]. Researchers should also examine the root mean square error of approximation (RMSEA); the consistent Akaike information criterion (CAIC), the Comparative Fit Index (CFI); and the Tucker-Lewis Index (TLI) or nonnormed fit index (NNFI) for model fit indication [64]. The results of this study show that the increase in chi-square between model 2 and model 3 is significant, Δχ2 = 239.05 with Δdf = 57. However, the remaining goodness-of-fit indices (TLI = 0.82, CFI = 0.82, and RMSEA = 0.035), which are less sensitive to sample size, show a less marked decrease in fit. Overall, the factor loadings, factor correlations, and factor variance are invariant across countries. Although the error variances are not invariant across the four countries, they are usually regarded as the least important and therefore the variances do not exert a constraint on our analysis [66].

[Insert Table 4 here]: Measurement invariance tests through a CFA constrained at several levels

4.4 Results for Hypotheses Testing

Table 5 shows path coefficients of the four countries. In Taiwan, resource planning infrastructure has significant and positive impacts on workforce reform, with a standardized path coefficient of 0.15. e-commerce infrastructure has significant and positive impacts on workplace reform and workforce reform, with standardized path coefficients of 0.31 and 0.17, respectively. Workplace reform positively affects workforce reform; and workforce reform positively influences organizational structure reform, with standardized path coefficients of 0.38 and 0.94, respectively. Workforce reform strongly influences company profits with a standardized path coefficient of 0.05. These results support Hypotheses 1b, 2b, 3a, 3b, 3c, and 4a.

In the United States, the RPI has significant and positive impacts WP and WF, with standardized path coefficients of 0.19 and 0.34, respectively. The ECI has significant and positive impact on WP and OS, with standardized path coefficients of 0.39 and 0.24, respectively. WP affects WF; WF influences OS, with standardized path coefficients of 0.37 and 0.63, respectively. Profit is influenced by WP and WF, with standardized path coefficients of 0.16 and 0.13, respectively. These results support Hypotheses 1a, 1b, 2a, 2b, 3a, 3b, 3c, 4a, and 4c.

In Korea, the RPI significantly and positively impacts WP and OS, with standardized path coefficients of 0.10 and 0.19, respectively. The ECI has significant and positive impacts on WF, with a standardized path coefficient of 0.17. WP affects WF, which influences OS, with standardized path coefficients of 0.56 and 0.75, respectively. Profit is influenced by both WP and WF, with standardized path coefficients of 0.27 and 0.12, respectively. These results support Hypotheses 1a, 1c, 2a, 3a, 3c, 4a, and 4b.

In Chile, RPI has significant and positive impacts on WP, with standardized path coefficients of 0.09. The ECI has significant and positive impacts on WP, with standardized path coefficients of 0.26. WP affects WF, and WF influences OS, with standardized path coefficients of 0.34 and 0.43, respectively. WP positively affects the profit, with a standardized path coefficient of 0.10. These results support Hypotheses 1a, 2a, 2b, 3a, and 4a. In sum, the path from WP to WF and from WF to OS is significant in all countries.

[Insert Table 5 here]: Results of structural equation model analysis of individual country models

However, we also found several notable and unanticipated results. In the United States, there are two negative significant path coefficients: one from RPI to OS, and, the other from OS to Profit, with standardized path coefficients of -0.19 and -0.09, respectively. In Korea, there are two negative significant path coefficients. The standardized path coefficient is -0.15 from RPI to WF, and -0.28 from WF to Profit. An explanation for why RPI does not have a positive impact on OS in the US might be that firm size in the US is much bigger than in the other countries in our survey. From the perspective of employee size, the United States has the largest firm scale, followed by Korea. Twenty-five percent of US firms have more than 2,000 employees. In Korea, firms with more than 1237 employees comprise 25% of the sample. Taiwan and Chile have smaller firm scales. In Taiwan and Chile companies with over 1000 employees account for 18.7% and 8.6% of all companies in the sample, respectively, much lower than in the United States and Korea. Further, large firms having proportionally greater spending on human resources may impact profits.

5. Conclusion and discussion

ICTs play an important role in business activity. Previous research has shown that ICTs contribute to performance improvements [67, 68]. However, research on the mixed effects of ICTs on BPR is lacking and cross-country comparisons of these effects have not been explored. Therefore, our research applies multiple-group structural equation modeling to test the Cross-Nation ICT-enabled BPR Model. The results are consistent with previous research that ICT adoption affects BPR, and, BPR influences business performance. There are differences in ICT adoption impact on BPR and differences of BPR influence on profit among countries.

For Chile, the resource planning infrastructure and e-commerce infrastructure positively affect workplace reform, which leads to profit improvement. For Taiwan, the e-commerce infrastructure has significant positive impacts on workplace reform and workforce reform. Workforce reform directly generates better profits. Though workplace reform does not directly affect profits, it indirectly improves profits. For the United States, both infrastructures positively cause workplace reform. The resource planning infrastructure, though making firms improve their workforce, negatively affects organizational structure reforms. e-commerce infrastructure positively impacts organizational structure. However, the mixed effects of these two infrastructures do not improve profits. Profits are positively influenced by workplace and workforce reform. For Korea, the resource planning infrastructure positively enables workplace reform and organizational structure reform. e-commerce infrastructure leads to positive workforce change. However, when mixed with negative effects of adoption of resource planning infrastructure, this impact does not create profits for firms directly, but indirectly through organizational structure reform.

Cultural differences probably exist for the discovered differences among these four countries. In addition, the ICT adoption - BPR - Performance paths of the firms in Taiwan and Chile are quite similar while firms in the USA and Korea show greater similarity. It might be because that the majority of the sample in the USA and Korea are service firms (USA: 56.5%; Korea: 63.7%) and larger enterprises (more employees hired). The sector distribution in the Taiwan and Chile samples is nearly equal. For example, the service sector sample proportion in Taiwan is 28.1%, in Chile, 28.7%, while the manufacturing sector comprises 38.3% in the Taiwan sector and 39.3% in Chile. Most firms in these two countries have fewer than 100 employees. In Taiwan and Chile, firms seem to be conservative in dramatically reforming workforces and organizational structures. However, they are willing to take advantage of new communication and information exchange tools to accomplish tasks without space constraints. It may be that workplace reforms are more peripheral to business operations and structural reforms contribute most of the results from optimization of business processes [2, 14, 22, 23]. This proposition is also confirmed in the results showing that profits are indirectly influenced by workplace reforms and workforce reforms. Reforms of workplace allow workers to accomplish tasks in difference time zones or locations. It is the easiest way to start to change the management processes and reduce travel and communication costs. The requirement of ICT usage to telecommunicate and teleconference to engage in interrelated work activities [34, 69] forces firms to demand that their employees have IT skills and to automate business processes. Such reform of the workforce renders management processes simpler and more efficient [32]. As processes become simpler, more efficient, and automatic, the organizational structure flattens, and involvement of employees in empowerment activities increases.

This research also finds that ICTs do not always result in better BPR, and ICT-enabled BPR does not always lead to good performance, in the sense of higher profits. In particular, the adoption of the resource planning infrastructure does not improve performance of organizational structure or workforce. This may be because ERP implementation easily encounters adoption difficulties and the pay-off takes time to appear [1, 2]. The long-term impact of infrastructure on BPR and performance is worth further investigation.

This paper contributes to IS research by offering insights and exploring BPR generalization using a cross national comparison. First, it provides empirical evidence to refine impacts of ICT contribution to business process reengineering and performance from the firm-level to the country-level. Prior research on this topic has usually focused on BPR theoretical discussion and implementation strategies based on case studies. The development of empirical evidence for generalization has largely been lacking. Second, research usually focuses on one or two ICT applications, such as KM or ERP. A more robust picture of the relationships between ICT adoption and BPR is lacking. The findings of this study will be valuable in understanding the complexity of ICT adoption and predicting outcomes of BPR. Finally, we explore the national differences in ICT adoption and its impacts on financial performance. It should be noted that ICT-enabled BPR does not always lead to profits. This inconsistency with prior literature may be because ICT investment may have time delay effects, and because the financial index is not the only indicator for performance estimation. For example, Santhanam and Hartono [36] note that the prior financial performance of firms must be taken into consideration in future tests of ICT capability.

Despite all the care given to this study, we acknowledge several limitations of our research. First, internationally comparative studies are subject to common methodological errors [70]. For example, we encounter the difficulty of obtaining equivalent indicators across the four countries for the constructs [30]. We do have Europe data from BIT research. However due to model converge and some missing value problems, we trimmed the original set of scale items and eliminated European countries from this paper. Another example of this problem is that sample structures may not be consistent across the four countries. The USA sample and Korea sample have more responses from service firms than from manufacturing firms. Second, we use a five-point Likert-type response format to explore the change of financial performance in firms instead of using ROA or ROI data, because it is difficult to obtain a financial index for each sample in every country. Third, there might be survey biases related to the subjective nature of the data. The CIO is our only informant about ICT adoption and performance evaluation may cause cognitive biases. However, James and Hatten [71] have demonstrated that this type of measurement is valid.

Notwithstanding these limitations, this study has demonstrated that integrating the ICT impact and business process re-engineering could provide further understanding of ICT contribution to firm performance. One avenue available to future researchers is to analyze industry sector differences, manufacturing firms vs. service firms, for example. Further research can explore additional facets of adoption intention and relationships among ICT adoption, BPR, and performance. Another avenue would be observing more country-level differences by adding more countries, or using economic regions (Asia, the Americas, or Europe) as categories. Other possibilities include narrowing down the samples to listed and OTC companies to obtain actual ROA and ROI data for analysis, incorporating psychological aspects of ICT adoption at firm level in different country contexts, and examining the effects of mediators and moderators on performance.