Grounded in the technology-organization-environment (TOE) framework, we develop a research model for assessing the value of e-business at the firm level. Based on this framework, we formulate six ...hypotheses and identify six factors (technology readiness, firm size, global scope, financial resources, competition intensity, and regulatory environment) that may affect value creation of e-business. Survey data from 612 firms across 10 countries in the financial services industry were collected and used to test the theoretical model. To examine how e-business value is influenced by economic environments, we compare two subsamples from developed and developing countries. Based on structural equation modeling, our empirical analysis demonstrates several key findings: (1) Within the TOE framework, technology readiness emerges as the strongest factor for e-business value, while financial resources, global scope, and regulatory environment also significantly contribute to e-business value. (2) Firm size is negatively related to e-business value, suggesting that structural inertia associated with large firms tends to retard e-business value. (3) Competitive pressure often drives firms to adopt e-business, but e-business value is associated more with internal organizational resources (e.g., technological readiness) than with external pressure to adopt. (4) While financial resources are an important factor in developing countries, technological capabilities become far more important in developed countries. This suggests that as firms move into deeper stages of e-business transformation, the key determinant of e-business value shifts from monetary spending to higher dimensions of organizational capabilities. (5) Government regulation plays a much more important role in developing countries than in developed countries. These findings indicate the usefulness of the proposed research model and theoretical framework for studying e-business value. They also provide insights for both business managers and policy-makers.
This study aims to design a model for measuring the level of maturity of business intelligence in electronic businesses, specifically for Internet Service Provider (ISP) companies. The study adopts a ...qualitative approach based on the phenomenological approach. A total of 10 specialists, experts, and managers from electronic businesses involved in providing Internet services are selected as participants using the maximal differentiation method. Data are collected through in-depth and semi-structured interviews and analyzed using Colaizzi's method. The findings are classified into five levels of business intelligence maturity (Level 1: Primary maturity, Level 2: Repeatable maturity, Level 3: Defined maturity, Level 4: Managed maturity, Level 5: Optimized maturity) using the Delphi technique. Subsequently, a model consisting of 33 dimensions and 232 indicators is designed based on the relevant literature and the researcher's viewpoint, with confirmation from experts. Finally, the model is validated using confirmatory factor analysis in Smart PLS software.IntroductionDue to the fact that businesses face numerous challenges, such as the need for increased responsiveness and transparency towards customers, the growing number of tasks and organizational activities, and rapid technological changes, they require mechanisms capable of real-time data analysis and integration. Business intelligence serves as one of these mechanisms. Additionally, businesses need to assess and evaluate their current performance, compare their existing processes, tools, and methods with the best practices, and measure indicators of predictability, control, and effectiveness to effectively implement business intelligence. Therefore, they require a model to gauge the maturity level of business intelligence within their organization. Consequently, the objective of this research is to present a model for measuring the maturity level of business intelligence in electronic businesses.Materials and MethodsSince the researcher aims to extract the components of business intelligence maturity based on people's mentalities and experiences, the phenomenological method, specifically Colaizzi's method, was employed. To achieve this, 10 experts from Internet service provider companies were interviewed and selected using the maximal differentiation sampling method. The analysis of these interviews resulted in the extraction of 277 significant codes. Given the research's focus on measuring the maturity level of business intelligence, 40 experts were then asked to classify the obtained concepts into five levels of business intelligence maturity (Level 1: Primary maturity, Level 2: Repeatable maturity, Level 3: Defined maturity, Level 4: Managed maturity, Level 5: Optimized maturity) using the Delphi technique and snowball sampling method. After three rounds of Delphi, 232 codes remained out of the initial total of 277 codes. These 232 indicators were then categorized into 33 dimensions based on the definitions, functions of business intelligence, and the perceived concepts of each indicator. Subsequently, the researcher designed a measurement model for the maturity level of business intelligence in electronic businesses specifically tailored for Internet service providers. Finally, the designed model was validated through confirmatory factor analysis using SmartPLS software.Discussion and ResultsThis research has developed a model that enables companies, especially Internet service providers, to assess their current business state and their progress towards their goals. The model facilitates the decision-making process for e-business managers. With 5 levels, 33 dimensions, and 232 indicators encompassing technical, managerial, and human aspects, the model effectively enhances business capabilities and establishes a foundation for improving and advancing the level of maturity within the business. It is important to note that the model's Level 1 (Primary maturity) includes one dimension titled "reporting" with five indicators. Level 2 (Repeatable maturity) comprises five dimensions: advertising (eight indicators), management and performance evaluation (seven indicators), control (three indicators), documentation (five indicators), and automation (two indicators). Level 3 (Defined maturity) consists of six dimensions: access level (four indicators), customer orientation (16 indicators), process management (eight indicators), standardization of processes (10 indicators), improvement of information quality (five indicators), and improvement of service level (28 indicators). Level 4 (Managed maturity) encompasses 13 dimensions: assessment and analysis skills (14 indicators), business development and organizational processes (nine indicators), organizational management (12 indicators), organizational training (nine indicators), human resource management (16 indicators), organizational value (five indicators), security (two indicators), support (five indicators), business strategies (three indicators), management and development of essentials (11 indicators), business performance management (five indicators), policy making (four indicators), and cost-benefit (two indicators). Lastly, Level 5 (Optimized maturity) includes eight dimensions: predictive analysis (six indicators), dashboard (two indicators), knowledge management (six indicators), innovation (four indicators), competitive advantage (six indicators), technology development (four indicators), expansion of investment (three indicators), and data mining (three indicators).ConclusionsThis research has designed a model to facilitate the decision-making process of e-business managers, particularly those in Internet service providers. The model enables companies to assess their current business state and their progress towards their goals. The model encompasses 5 levels, 33 dimensions, and 232 different indicators, taking into account technical, managerial, and human aspects. With this comprehensive approach, the model has the potential to enhance business capabilities and establish a solid groundwork for improving and advancing the maturity level of the business. Internet service provider companies not only gain an understanding of their business intelligence maturity level and have the opportunity to elevate it through long-term planning, but they also empower themselves to navigate future changes and meet evolving customer expectations. The business intelligence maturity model introduced in this study serves as a framework for continuous improvement in their business activities. It provides a foundation and context for controlling processes and facilitates the ongoing enhancement of their operations.This study aims to design a model for measuring the level of maturity of business intelligence in electronic businesses, specifically for Internet Service Provider (ISP) companies. The study adopts a qualitative approach based on the phenomenological approach. A total of 10 specialists, experts, and managers from electronic businesses involved in providing Internet services are selected as participants using the maximal differentiation method. Data are collected through in-depth and semi-structured interviews and analyzed using Colaizzi's method. The findings are classified into five levels of business intelligence maturity (Level 1: Primary maturity, Level 2: Repeatable maturity, Level 3: Defined maturity, Level 4: Managed maturity, Level 5: Optimized maturity) using the Delphi technique. Subsequently, a model consisting of 33 dimensions and 232 indicators is designed based on the relevant literature and the researcher's viewpoint, with confirmation from experts. Finally, the model is validated using confirmatory factor analysis in Smart PLS software.IntroductionDue to the fact that businesses face numerous challenges, such as the need for increased responsiveness and transparency towards customers, the growing number of tasks and organizational activities, and rapid technological changes, they require mechanisms capable of real-time data analysis and integration. Business intelligence serves as one of these mechanisms. Additionally, businesses need to assess and evaluate their current performance, compare their existing processes, tools, and methods with the best practices, and measure indicators of predictability, control, and effectiveness to effectively implement business intelligence. Therefore, they require a model to gauge the maturity level of business intelligence within their organization. Consequently, the objective of this research is to present a model for measuring the maturity level of business intelligence in electronic businesses.Materials and MethodsSince the researcher aims to extract the components of business intelligence maturity based on people's mentalities and experiences, the phenomenological method, specifically Colaizzi's method, was employed. To achieve this, 10 experts from Internet service provider companies were interviewed and selected using the maximal differentiation sampling method. The analysis of these interviews resulted in the extraction of 277 significant codes. Given the research's focus on measuring the maturity level of business intelligence, 40 experts were then asked to classify the obtained concepts into five levels of business intelligence maturity (Level 1: Primary maturity, Level 2: Repeatable maturity, Level 3: Defined maturity, Level 4: Managed maturity, Level 5: Optimized maturity) using the Delphi technique and snowball sampling method. After three rounds of Delphi, 232 codes remained out of the initial total of 277 codes. These 232 indicators were then categorized into 33 dimensions based on the definitions, functions of business intelligence, and the perceived concepts of each indicator. Subsequently, the researcher designed a measurement model for the maturity level of business intelligence in electronic businesses specifically tailored for Internet service
Online retail platforms significantly impact consumers' purchasing decisions. Satisfaction, purchase intent, and repeat online shopping drive the platform's purchasing decisions. In contrast, ...individuals do not purchase products due to dissatisfaction and lack of purchasing intent. It will cause hesitation and spread negative feedback to influence online consumer behaviors. This research proposes a conceptual model incorporating the Status Quo Bias (SQB) and the Negative Online Purchase Decision-Making Process (NOPDMP) to suggest a new framework for evaluating the maintained consumer behavior of online shopping platforms. The questionnaires following the proposed conceptual model were collected from the sample data from participants of 384 experienced respondents using online shopping platforms. Data were analyzed for the causal relationship using Structural Equation Model. The implications of the assessment framework that incorporates the influence of negative factors can weigh the decision to purchase products and improve and reduce shopping cart abandonment on e-commerce platforms. This framework can also describe instances of negative perspectives regarding incentive alignments with actual behaviors.
Electronic business ventures (EBVs), startups on Internet platforms, have recently attracted research attention. This study attempts to understand the encompassing mechanism for the superior market ...performance of EBVs entering China's electronic market with a focus on the effects of two important drivers. The first is Guanxi orientation, which is a strategic factor rooted in Chinese culture. The second is the order of entry or the chosen time of entering a market to gain advantages. We test six hypotheses based on data collected from 155 EBVs established over the past 10 years in China. The results show that EBVs' Guanxi orientation positively influences their market performance and that this effect is mediated by political ties built through Guanxi activities. Although the order of entry effect is not evident for EBVs, Guanxi orientation contributes to market performance to a higher degree for late entrant EBVs than for early follower EBVs. The study's findings offer new insights into the implementation of Guanxi orientation in the fast-growing electronic market in China, an emerging country with a culture distinct from that of the West.
•The market performance of Electronic Business Ventures (EBVs) is studied in a Chinese cultural context, taken into consideration order of entry decisions.•Order of entry does not appear a determinant factor for EBVs’ superior performance, but it has a moderating effect on the relationship between Guanxi orientation and market performance.•EBVs’ Guanxi orientation leads to stronger political ties, which in turn positively influence market performance.
This paper aims to fill research gaps in the existing literature on the effect of electronic business on financial firm performance within the specific context of manufacturing Small and Medium ...Enterprises (SMEs). More specifically, this research analyzes not only the direct effects of e-business on firm performance but also the mediating effect of organizational innovation the relationship. Building on the knowledge and resource-based views, the proposed research model and its associated hypotheses are tested by using partial least squares (PLS) structural equation modeling on a dataset of Spanish manufacturing SMEs. Results suggest that electronic business has a direct effect on financial performance and is positively associated to organizational innovation. In addition, results show that the relationship between electronic business and financial performance is mediated by organizational innovation.
The paper assesses the ways in which digital transformation in Montenegro influences the use of digital marketing in business, determining the impact of this concept on promotion and brand ...positioning, i.e. electronic business development through electronic services. This facilitates the integrated analysis of the context of electronic business, thus providing innovative and value-creating insights for Montenegro – a transition country. This research was conducted using a survey on a stratified random sample and the data was subsequently analyzed using the Structural Equation Model (SEM), Analysis of Variance (ANOVA) test, and eta-coefficient. Multivariate analysis was applied to data obtained from 172 companies. The results showed that a number of factors determine the ways in which companies apply digital marketing and use differing levels of influence, amongst which the period of implementation, the abilities of people in charge for its usage, perception of digital marketing cost-effectiveness, measurability of its effects and sufficiency of traditional marketing have a key role. The period in which digital marketing is used was especially significant and notably affects the choice of digital marketing instruments, the way its performances are measured and the managers’ perception of its cost-effectiveness. Social networks were the most commonly used form of digital marketing in the market under analysis, and Google analytics was the most common way to measure the effects of digital marketing. Furthermore, the results showed that the more a company relies on the use of digital marketing in its business, the more significant its impact on promotion and brand positioning.
•Multivariate analysis was applied to data obtained from 172 companies in transition country Montenegro.•a survey on a stratified random sample and the data was subsequently analyzed using the Structural Equation Model (SEM), Analysis of Variance (ANOVA) test, and eta-coefficient.•The use of digital marketing has a slightly bigger impact on the formation of respondents' attitudes regarding its influence on the development of e-business (η2 = 0.563), followed by its impact on brand promotion and positioning (η2 = 0.509). Based on the results obtained, we accept hypotheses H2 and H3.•Research has shown that social networks are the form of digital marketing that companies use most often. This is especially evident in companies that use digital marketing for more than 5 or more than 10 years. The most common ways to measure the effects of digital marketing are Google Analytics, followed by the Social Network User Engagement Rate and the Degree of Interaction.
E-business (electronic business) is the conduct of business processes on the internet. These e-business processes include buying and selling products, supplies and services; servicing customers; ...processing payments; managing production control; collaborating with business partners; sharing information; running automated employee services; recruiting; and more
Purpose The author aims to study and predict the sustainability governance performances of firms using an advanced grey prediction model. The case implication of the prediction model is also studied ...considering select firms in the Indian context. Design/methodology/approach The author has proposed an advanced grey prediction model, the first-entry grey prediction model (FGM (1, 1)) for forecasting the sustainability governance performances of firms. The proposed model is tested using the periodic data of sustainability governance performances of 10 Indian firms. Findings The author observes that the majority of firms (6 out of 10) show dipping performances for sustainability governance for the future predicted period. This throws insights into the direction of improving good governance practices for Indian firms. Practical implications The idea and motivation for sustainability-focussed governance need a bi-directional focus from the side of managers that act as the agents and from the side of shareholders that act as the principals, as seen from an agency theory perspective for sustainability governance. Social implications Sustainability governance culture can be inculcated to a firm at the strategic level by having a bi-directional focus from managers and shareholders, so as to enhance the social and environmental sustainability performances. Originality/value The governance performance evaluations for firms particularly in developing countries were not dated back more than a decade or two. Hence, the author implements a prediction model that can be best suited, when there are small periodic data sets available for prediction.
It does not need to be mentioned that Business cards are essential for businesses and consumers alike across all industries irrespective of size of the business. Today, these cards not only help in ...giving contact details but building a brand. In digital era the business card is also going through the journey of digital transformation. While some of the expectation from such electronic business card can be articulated as - Easy to share, cost-effective, Eco-friendly, Easy to customize, store the information conveniently and contact management .While taking a closer look at these expectation the authors were convinced that such system should be based on a cloud architecture .The authors with their experience on the 2P-cloud Architecture realized that the concept can be extended for cloud services 4-tier architectures and an Electronic Business card system can be built on it. In this study, we proposal an instance of the cloud electronic business card (EBC) generation framework which is according to the Key point of view of Business models, Operational processes and User experiences of Digital transformation studied by Abhijit et al. and the five skills and competencies of CDO studied by Anna et al. and the 2P-Cloud architecture studied by Chuang et al as main. In this study, we focused on the system availability of cloud EBC system in the development processes, which is to attend the smooth process of Human-Computer Interaction when we design an IT system.
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