How e-business influences on time customer delivery : An empirical investigation on insurance industry

Article history: Received June 22, 2013 Received in revised format 28 August 2013 Accepted 21 September 2013 Available online September 23 2013 During the past few years, e-business has revolutionized insurance industry and it has become as one of the most important techniques to reach global market. This paper presents an empirical investigation to find important factors influencing on time delivery to customers. The proposed study of this paper designs a questionnaire consists of 28 items in Likert scale, which was reduced to 24 and using principle component analysis, the study finds different important factors. Cronbach alpha is calculated as 0.94. In addition, Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Approx. Chi-Square are 0.882 and 2462, respectively. The study determines four important factors including dynamic organization, environment opportunities, flexible structure and customer relationship management. © 2013 Growing Science Ltd. All rights reserved.


Introduction
During the past few years, there have been substantial changes on many industries due to recent advances on technology. E-commerce has broken the borders among countries, helping people purchase different services, electronically. Many firms find that their ability to respond to unexpected changes in the market is a key factor in survival and the ability to adjust e-business processes to customer preferences has become an essential thing for online systems (Basu & Muylle, 2011;Phillips & Wright, 2009). Wu and Zhong (2009) investigated a case study of three large iron and steel manufacturing enterprises in China to identify a mechanism, which enables e-business technology to improve enterprise competitiveness. They developed the concept of application capability of e-business from a process-oriented perspective, and investigated the effect of the application capability of e-business on the relationship between e-business resources and enterprise competitiveness. They explained that e-business resources were necessary, rather than sufficient, to help enterprise competitiveness. They also reported that an enterprise could implement e-business technology to enhance its competitiveness only when its e-business resources and application capability of e-business were effectively synthesized. Hussain et al. (2011) presents a technique, determines the negative consequences of forming ebusiness associations. Unlike other methods, the proposed model captures various kinds of events and their uncertainties to detect the financial risk by implementing the convolution operator and expressing it as a probabilistic measure rather than as a crisp financial value. E-business plays essential role in modern economic networks because of its shorter cycle time and faster information transactions (Lai & Yang, 2009). Shin and Park (2009) provided a method to detect both, to create potentially competitive variants, and to evaluate them, quantitatively and used it in an e-auction case in Korea to illustrate the empirical application of the proposed method. Johnson et al. (2007) presented some findings from an exploratory study that analyzed the outcomes of e-business technology implementation in the supply chain. They examined how industry context, firm characteristics and firm-level strategic resources, such as purchasing teams, impact the exploitation of e-business technologies and the relationship between e-business technology implementation and firm performance. Wu et al. (2011) tried to understand the capabilities influence a firms' capability to build e-business success and enjoy bigger organizational performance, where firm-level e-business success was measured by e-business service ability and IT-enabled collaborative advantage. Osmonbekov (2010) investigated the impact of social enforcement, technology-relationship fit and the mediating role of reseller benefits. Lai and Chen (2009) measured e-business dependability in terms of employee perspective. Lin and Lin (2008) investigated determinants of e-business diffusion by performing a test of the technology diffusion perspective. Lai and Ong (2010) evaluated and managed employees for embracing change by performing a multiple-item scale to determine employee readiness for e-business. Katsanakis and Kossyva (2012) investigated whether firms could co-operate and compete at the same time (co-opetition), based on a C-Business system, and whether this could lead to a co-beneficial relationship. Cegarra-Navarro et al. (2007) investigated the relative importance and effect of the four learning processes introduced by Huber on different levels of ebusiness, through an empirical investigation of 130 SMEs in the Spanish telecommunications sector. They suggested that knowledge acquisition is necessary to progress from relational level to internal level. Soto-Acosta and Meroño-Cerdan (2008) analyzed e-business value creation from a resourcebased perspective by developing a conceptual model, grounded in the resource-based theory, for assessing e-business value creation. Nurmilaakso (2008) investigated adoption of e-business functions and migration from EDI-based to XML-based e-business frameworks in supply chain integration. Xirogiannis and Glykas (2007) built a reasoning mechanism as a novel supplement to ebusiness strategy formulation exercises. Voola et al. (2012) investigated the effects of market orientation, technological opportunism, and e-business adoption on performance.

The proposed method
This paper presents an empirical investigation to find important factors influencing on time delivery to customers. The proposed study of this paper designs a questionnaire consists of 28 items in Likert scale.  As we can observe from the results of Table 1, all factors maintain communalities of well above 0.50. In addition, Table 2 summarizes the results of total variance explained for different items. In addition, Fig. 1 shows Scree plot of different factors and the results indicate that we can extract four important factors.

The results
In this section, we present details of the findings of the implementation of factor analysis. The study determines four important factors including dynamic organization, environment opportunities, flexible structure and customer relationship management.

The first factor: Dynamic organization
Dynamic organization includes eight sub-factors, which are summarized in Table 3 as follows, Table 3 The summary of factors associated with dynamic organization The information of Table 3 indicates that reaction to changes plays the most important role followed by decision agility and knowledge sharing.

The second factor: Environment opportunities
Environment opportunities are considered as the second most important factors influencing ebusiness with seven sub-factors summarized in Table 4. In terms of different important factors, Internet utilization is the most influential factor followed by competitive advantage, internal teams, innovation utilization.

The third factor: Flexible structure
The third factor is associated with flexibility of organizational structure, which includes five factors presented in Table 5 as follows, As we can observe from the results of Table 5, market orientation is the most important factor followed by taking advantage of information technology, operational structure, flexibility and financial performance.

The fourth item: Customer relationship management
Customer relationship management is the last influential item, which influences on our e-business success. This item includes four factors, which are summarized in Table 6 as follows, Table 6 The summary of factors associated with customer relationship management The results of Table 6 indicate that perceived trust and reliability is the most important item followed by staff learning, customer satisfaction and rewards and promotions.

Conclusion
In this paper, we have presented a survey on detecting important factors influencing insurance industry on implementation of e-business. The survey has used principal component analysis and extracted four important factors. Dynamic structure has been the first important factor with eight subcomponents, where reaction to changes plays the most important role followed by decision agility and knowledge sharing. In our survey, environment opportunities were the second factor influencing ebusiness with seven sub-factors where internet utilization was considered as the most influential factor followed by competitive advantage, internal teams, innovation utilization. The third factor is associated with flexibility of organizational structure, which includes five factors and finally, customer relationship management is the last important factor where perceived trust and reliability has been the most important item followed by staff learning, customer satisfaction and rewards and promotions.