Showing papers in "Interdisciplinary Journal of Information, Knowledge, and Management in 2020"

The Effect of Marketing Knowledge Management on Bank Performance Through Fintech Innovations: A Survey Study of Jordanian Commercial Banks

Abstract: Aim/Purpose: This study aimed to examine the effect of marketing knowledge management (MKM) on bank performance via the mediating role of the Fintech innovation in Jordanian commercial banks. Background: An extensive number of studies found a significant relationship between Marketing knowledge management and bank performance (e.g., Akroush & Al-Mohammad, 2010; Hou & Chien 2010; Rezaee & Jafari, 2015; Veismoradi et al., 2013). However, there remains a lack of clarity regarding the relationship between marketing knowledge management (MKM) and bank performance (BP). Furthermore, the linkage between MKM and BP is not straightforward but, instead, includes a more complicated relationship. Therefore, it is argued that managing marketing knowledge management assets and capabilities can enhance performance via the role of financial innovation as a mediating factor on commercial banks; to date, however, there is no empirical evidence. Methodology: Based on a literature review, knowledge-based theory, and financial innovation theory, an integrated conceptual framework has been developed to guide the study. A quantitative approach was used, and the data was collected from 336 managers and employees in all 13 Jordanian commercial banks using online and in hand instruments. Structural equation modeling (SEM) was used to analyze and verify the study variables. Contribution: This article contributes to theory by filling a gap in the literature regarding the role of marketing knowledge management assets and capabilities in commercial banks operating in a developing country like Jordan. It empirically examined and validated the role of Fintech innovation as mediators between marketing knowledge management and bank performance Findings: The main findings revealed that marketing knowledge management had a significant favorable influence on bank performance. Fintech innovation acted as partial mediators in this relationship. Recommendations for Practitioners: Commercial banks should be fully aware of the importance of knowledge management practices to enhance their financial innovation and bank performance. They should also consider promoting a culture of practicing knowledge management processes among their managers and employees by motivating and training to promote innovations. Recommendation for Researchers: The result endorsed Fintech innovation’s mediating effect on the relationship between the independent variable, marketing knowledge management (assets and capabilities), and the dependent variable bank performance, which was not addressed before; thus, it needs further validation. Future Research: The current designed research model can be applied and assessed further in other sectors, including banking and industrial sectors across developed and developing countries. It would also be of interest to introduce other variables in the study model that can act as consequences of MKM capabilities, such as financial and non-financial performance measures

Consumer Engagement in Online Brand Communities: Community Values, Brand Symbolism and Social Strategies

Abstract: Aim/Purpose This study examines the kind of community value companies should provide when strengthening the relationship between customers and brands through the establishment of an online brand community, and how this kind of community value promotes customers’ sense of community engagement and willingness to spread brand reputation. The paper also discusses how an enterprise’s brand symbolism affects the relationship between community value and customers’ engagement in online brand community. This study explored the important role of brand symbolism in the establishment of an online brand community. Background Many companies want to create online brand communities to strengthen their relationships with consumers as well as to provide better service and value to consumers, for example, Huawei’s Huafen community (club.huawei.com), Apple’s support community (support.apple.com/zh-cn), and Samsung’s Galaxy community (samsungmembers.cn). However, these brand communities may have different interests and consumer engagement about the kind of community value to offer to their customers. Methodology This study uses data collection from questionnaire surveys to design a quantitative research method. An online questionnaire survey of mobile phone users in China was conducted to collect data on social value, cognitive value, brand symbolism, customer community engagement, and brand recommendation. The brands of mobile phone include Apple, Huawei, Samsung, OPPO, VIVO, MI, and Meizu. The researcher purchased a sample service of WJX, an online survey company (www.wjx.cn), and WJX company distributed the questionnaire to research participants. The WJX company randomly selected 240 subjects from their sample database and then sent the questionnaire link to research participants’ mobile phones. Among the 240 research participants, the researcher excluded participants who lacked online brand community experience or had invalid data to qualify for data collection. After the researcher excluded particiConsumer Engagement in Online Brand Communities 66 pants who did not qualify for data collection, only 203 qualified questionnaire surveys advanced to the data collection and analysis phase, which was the questionnaire recovery rate of 84.58%. For the model analysis and hypotheses testing, the researcher used statistical software IBM SPSS Statistics and AMOS 21 and Smartpls3. Contribution This study deepens the body of literature knowledge by combining online brand community value and brand symbolic value to explore issues that companies should consider when establishing an online brand community for their products and services. This study confirms that brands with high symbolic value establish communities and strengthen social values in the online brand community rather than reducing brand symbolism. Online brand community involves a horizontal interaction (peer interaction) among peers, which can have an effect on the symbolic value of brand (social distance). Findings First, online brand community value (both cognitive and social value) has a positive impact on customer community engagement. Second, customer community engagement has a positive impact on customers’ brand recommend intention. Third, the customer community engagement is a mediator between the online brand community value and the customer brand recommend intention. Most importantly, fourth, the symbolic value of the brand controls the relationship between community value and customer community engagement. For brands with high symbolic value, the community value should emphasize cognitive value rather than social value. For brands with a low symbolic value, the community provides cognitive or social value, which is not affected by the symbolism of the brand. Recommendations for Practitioners Practitioners can share best practices with the corporate sectors. Brand owners can work with researchers to explore the characteristics of their online brand communities. On this basis, brand owners and researchers can jointly build and manage online brand communities. Recommendation for Researchers Researchers can explore different perspectives and factors of brand symbolism that involve brand owners when establishing an online brand community to advance consumer engagement, community value, and brand symbolism. Impact on Society Online brand community is relevant for brand owners to establish brand symbolism, community value, and customer engagement. Readers of this paper can gain an understanding that cognitive and social values are two important drivers of individual participation in online brand communities. The discussion of these two factors can give readers and brand owners the perception to gain more understanding on social and behavior activities in online brand communities. Future Research Practitioners and researchers could follow-up in the future with a study to provide more understanding and updated research information from different perspectives of research samples and hypotheses on online brand community.

The Effect of Rational Based Beliefs and Awareness on Employee Compliance with Information Security Procedures: A Case Study of a Financial Corporation in Israel

Abstract: Aim/Purpose This paper examines the behavior of financial firm employees with regard to information security procedures instituted within their organization. Furthermore, the effect of information security awareness and its importance within a firm is explored. Background The study focuses on employees’ attitude toward compliance with information security policies (ISP), combined with various norms and personal abilities. Methodology A self-reported questionnaire was distributed among 202 employees of a large financial Corporation Contribution As far as we know, this is the first paper to thoroughly explore employees’ awareness of information system procedures, among financial organizations in Israel, and also the first to develop operative recommendations for these organizations aimed at increasing ISP compliance behavior. The main contribution of this study is that it investigates compliance with information security practices among employees of a defined financial corporation operating under rigid regulatory governance, confidentiality and privacy of data, and stringent requirements for compliance with information security procedures. Findings Our results indicate that employees’ attitudes, normative beliefs and personal capabilities to comply with firm’s ISP, have positive effects on the firm’s ISP compliance. Also, employees’ general awareness of IS, as well as awareness to ISP within the firm, positively affect employees’ ISP compliance. Rational Based Beliefs and Awareness 110 Recommendations for Practitioners This study can help information security managers identify the motivating factors for employee behavior to maintain information security procedures, properly channel information security resources, and manage appropriate information security behavior. Recommendations for Researchers Researchers can see that corporate rewards and sanctions have significant effects on employee security behavior, but other motivational factors also reinforce the ISP’s compliance behavior. Distinguishing between types of corporations and organizations is essential to understanding employee compliance with information security procedures. Impact on Society This study offers another level of understanding of employee behavior with regard to information security in organizations and comprises a significant contribution to the growing knowledge in this area. The research results form an important basis for IS policymakers, culture designers, managers, and those directly responsible for IS in the organization. Future Research Future work should sample employees from another type of corporation from other fields and should apply qualitative analysis to explore other aspects of behavioral patterns related to the subject matter.

IDCUP Algorithm to Classifying Arbitrary Shapes and Densities for Center-based Clustering Performance Analysis

Abstract: Aim/Purpose The clustering techniques are normally considered to determine the significant and meaningful subclasses purposed in datasets. It is an unsupervised type of Machine Learning (ML) where the objective is to form groups from objects based on their similarity and used to determine the implicit relationships between the different features of the data. Cluster Analysis is considered a significant problem area in data exploration when dealing with arbitrary shape problems in different datasets. Clustering on large data sets has the following challenges: (1) clusters with arbitrary shapes; (2) less knowledge discovery process to decide the possible input features; (3) scalability for large data sizes. Density-based clustering has been known as a dominant method for determining the arbitrary-shape clusters. Background Existing density-based clustering methods commonly cited in the literature have been examined in terms of their behavior with data sets that contain nested clusters of varying density. The existing methods are not enough or ideal for such data sets, because they typically partition the data into clusters that cannot be nested.

The Longitudinal Empirical Study of Organizational Socialization and Knowledge Sharing – From the Perspective of Job Embeddedness

Abstract: Aim/Purpose Based on the social exchange theory, this study aimed to explore the underlying mechanisms and boundary conditions between organizational socialization and knowledge sharing. Background With the advent of the era of the knowledge economy, knowledge has been replacing traditional resources such as capital, labor, and land to become the critical resources of enterprises. The competitiveness of an organization depends much on the effectiveness of its knowledge management; the success of its knowledge management largely relies upon employees’ motivation and willingness to engage in knowledge sharing. Methodology This study is a longitudinal analysis of data collected from 281 newcomers in Chinese enterprises at two-time points with a one-month interval. Structural equation modeling (SEM) was conducted to test hypotheses by calculating standardized path coefficients and their significance levels. Contribution The study examined models linking organizational socialization and knowledge sharing that included organizational links and sacrifice as mediators and trust as a moderator. Organizational socialization and knowledge sharing 2 Findings Results show that the influences of organizational socialization on knowledge sharing change regularly over time. In the role management stage, coworker support and prospects for the future impact the practices of knowledge sharing through links and sacrifice. Moreover, the findings show that trust moderates the effect of links and sacrifice on employees’ knowledge sharing. Recommendations for Practitioners This study can help enterprises develop targeted human resource management strategies, improve the degree of job embeddedness within the organization, and thus encourage more knowledge sharing among employees. Recommendations for Researchers First, researchers could pay attention to more underlying mechanisms and boundary conditions in the relationship between organizational socialization and knowledge sharing. Second, focusing on specific cultural context and dimension of concepts may provide a new insight for the future study and help add greater theoretical precision to knowledge sharing. Impact on Society First, this study suggests that coworker support and prospects for the future improve knowledge sharing within the organization. Second, understanding how job embeddedness (organizational links and organizational sacrifice) acts as a mediator enhancing knowledge sharing, managers should consider raising their attachment relationship to organizations from two aspects: links and sacrifice. Third, knowledge sharing takes place in a team-oriented context, where the success of the team requires highquality relationships among individual team members within the team as a whole. Future Research Researchers in the future should employ experimental research design or utilize longitudinal data to ensure that the findings reveal causation. In addition, future research can investigate how the initial level and later changes of organizational socialization are associated with knowledge sharing beyond the observational scope of traditional cross-sectional and lagged research designs.

A Cognitive Knowledge-based Model for an Academic Adaptive e-Advising System

Abstract: Aim/Purpose This study describes a conceptual model, based on the principles of concept algebra that can provide intelligent academic advice using adaptive, knowledge-based feedback. The proposed model advises students based on their traits and academic history. The system aims to deliver adaptive advice to students using historical data from previous and current students. This data-driven approach utilizes a cognitive knowledge-based (CKB) model to update the weights (values that indicate the strength of relationships between concepts) that exist between student’s performances and recommended courses. Background A research study conducted at the Public Authority for Applied Education and Training (PAAET), a higher education institution in Kuwait, indicates that students’ have positive perceptions of the e-Advising system. Most students believe that PAAET’s e-Advising system is effective because it allows them to check their academic status, provides a clear vision of their academic timeline, and is a convenient, user-friendly, and attractive online service. Student advising can be a tedious element of academic life but is necessary to fill Adaptive e-Advising System 248 the gap between student performance and degree requirements. Higher education institutions have prioritized assisting undecided students with career decisions for decades. An important feature of e-Advising systems is personalized feedback, where tailored advice is provided based on students' characteristics and other external parameters. Previous e-Advising systems provide students with advice without taking into consideration their different attributes and goals. Methodology This research describes a model for an e-Advising system that enables students to select courses recommended based on their personalities and academic performance. Three algorithms are used to provide students with adaptive course selection advice: the knowledge elicitation algorithm that represents students' personalities and academic information, the knowledge bonding algorithm that combines related concepts or ideas within the knowledge base, and the adaptive e-Advising model that recommends relevant courses. The knowledge elicitation algorithm acquires student and academic characteristics from data provided, while the knowledge bonding algorithm fuses the newly acquired features with existing information in the database. The adaptive e-Advising algorithm provides recommended courses to students based on existing cognitive knowledge to overcome the issues associated with traditional knowledge representation methods. Contribution The design and implementation of an adaptive e-Advising system are challenging because it relies on both academic and student traits. A model that incorporates the conceptual interaction between the various academic and student-specific components is needed to manage these challenges. While other e-Advising systems provide students with general advice, these earlier models are too rudimentary to take student characteristics (e.g., knowledge level, learning style, performance, demographics) into consideration. For the online systems that have replaced face-to-face academic advising to be effective, they need to take into consideration the dynamic nature of contemporary students and academic settings. Findings The proposed algorithms can accommodate a highly diverse student body by providing information tailored to each student. The academic and student elements are represented as an Object-Attribute-Relationship (OAR) model. Recommendations for Practitioners The model proposed here provides insight into the potential relationships between students’ characteristics and their academic standing. Furthermore, this novel e-Advising system provides large quantities of data and a platform through which to query students, which should enable developing more effective, knowledge-based approaches to academic advising. Recommendation for Researchers The proposed model provides researches with a framework to incorporate various academic and student characteristics to determine the optimal advisory factors that affect a student’s performance. Impact on Society The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advice to students. The proposed approach can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to learning. Al-Hunaiyyan, Bimba, & Al-Sharhan 249 Future Research In future studies, the proposed algorithms will be implemented, and the adaptive e-Advising model will be tested on real-world data and then further improved to cater to specific academic settings. The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advisory to students. The approach proposed can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to course recommendation.

A Multicluster Approach to Selecting Initial Sets for Clustering of Categorical Data

Abstract: Aim/Purpose This article proposes a methodology for selecting the initial sets for clustering categorical data. The main idea is to combine all the different values of every single criterion or attribute, to form the first proposal of the so-called multiclusters, obtaining in this way the maximum number of clusters for the whole dataset. The multiclusters thus obtained, are themselves clustered in a second step, according to the desired final number of clusters. Background Popular cluster methods for categorical data, such as the well-known K-Modes, usually select the initial sets by means of some random process. This fact introduces some randomness in the final results of the algorithms. We explore a different application of the clustering methodology for categorical data that overcomes the instability problems and ultimately provides a greater clustering efficiency. Methodology For assessing the performance of the proposed algorithm and its comparison with K-Modes, we apply both of them to categorical databases where the response variable is known but not used in the analysis. In our examples, that response variable can be identified to the real clusters or classes to which the observations belong. With every data set, we perform a two-step analysis. In the first step we perform the clustering analysis on data where the response variable (the real clusters) has been omitted, and in the second step we use that omitted information to check the efficiency of the clustering algorithm (by comparing the real clusters to those given by the algorithm). Contribution Simplicity, efficiency and stability are the main advantages of the multicluster method. A Multicluster Approach to Selecting Initial Sets for Clustering of Categorical Data 228 Findings The experimental results attained with real databases show that the multicluster algorithm has greater precision and a better grouping effect than the classical Kmodes algorithm. Recommendations for Practitioners The method can be useful for those researchers working with small and medium size datasets, allowing them to detect the underlying structure of the data in an intuitive and reasonable way. Recommendations for Researchers The proposed algorithm is slower than K-Modes, since it devotes a lot of time to the calculation of the initial combinations of attributes. The reduction of the computing time is therefore an important research topic. Future Research We are concerned with the scalability of the algorithm to large and complex data sets, as well as the application to mixed data sets with both quantitative and qualitative attributes.

Critical Success Factors for Implementing Business Intelligence Projects (A BI Implementation Methodology Perspective)

Abstract: Aim/Purpose: The purpose of this paper is to identify Critical Success Factors (CSFs) for Business Intelligence (BI) implementation projects by studying the existing BI project implementation methodologies and to compare these methodologies based on the identified CSFs. Background: The implementation of BI project has become one of the most important technological and organizational innovations in modern organizations. The BI project implementation methodology provides a framework for demonstrating knowledge, ideas and structural techniques. It is defined as a set of instructions and rules for implementing BI projects. Identifying CSFs of BI implementation project can help the project team to concentrate on solving prior issues and needed resources. Methodology: Firstly, the literature review was conducted to find the existing BI project implementation methodologies. Secondly, the content of the 13 BI project implementation methodologies was analyzed by using thematic analysis method. Thirdly, for examining the validation of the 20 identified CSFs, two questionnaires were distributed among BI experts. The gathered data of the first questionnaire was analyzed by content validity ratio (CVR) and 11 of 20 CSFs were accepted as a result. The gathered data of the second questionnaire was analyzed by fuzzy Delphi method and the results were the same as CVR. Finally, 13 raised BI project implementation methodologies were compared based on the 11 validated CSFs. Contribution: This paper contributes to the current theory and practice by identifying a complete list of CSFs for BI projects implementation; comparison of existing BI project implementation methodologies; determining the completeness degree of existing BI project implementation methodologies and introducing more complete ones; and finding the new CSF “Expert assessment of business readiness for successful implementation of BI project” that was not expressed in previous studies. Findings: The CSFs that should be considered in a BI project implementation include: “Obvious BI strategy and vision”, “Business requirements definition”, “Business readiness assessment”, “BI performance assessment”, “Establishing BI alignment with business goals”, “Management support”, “IT support for BI”, “Creating data resources and source data quality”, “Installation and integration BI programs”, “BI system testing”, and “BI system support and maintenance”. Also, all the 13 BI project implementation methodologies can be divided into four groups based on their completeness degree. Recommendations for Practitioners: The results can be used to plan BI project implementation and help improve the way of BI project implementation in the organizations. It can be used to reduce the failure rate of BI implementation projects. Furthermore, the 11 identified CSFs can give a better understanding of the BI project implementation methodologies. Recommendation for Researchers: The results of this research helped researchers and practitioners in the field of business intelligence to better understand the methodology and approaches available for the implementation and deployment of BI systems and thus use them. Some methodologies are more complete than other studied methodologies. Therefore, organizations that intend to implement BI in their organization can select these methodologies according to their goals. Thus, Findings of the study can lead to reduce the failure rate of implementation projects. Future Research: Future researchers may add other BI project implementation methodologies and repeat this research. Also, they can divide CSFs into three categories including required before BI project implementation, required during BI project implementation and required after BI project implementation. Moreover, researchers can rank the BI project implementation CSFs. As well, Critical Failure Factors (CFFs) need to be explored by studying the failed implementations of BI projects. The identified CSFs probably affect each other. So, studying the relationship between them can be a topic for future research.

The Challenge of Evaluating Virtual Communities of Practice: A Systematic Mapping Study

Abstract: Aim/Purpose: This paper presents a study of Virtual Communities of Practice (VCoP) evaluation methods that aims to identify their current status and impact on knowledge sharing. The purposes of the study are as follows: (i) to identify trends and research gaps in VCoP evaluation methods; and, (ii) to assist researchers to position new research activities in this domain. Background: VCoP have become a popular knowledge sharing mechanism for both individuals and organizations. Their evaluation process is complex; however, it is recognized as an essential means to provide evidences of community effectiveness. Moreover, VCoP have introduced additional features to face to face Communities of Practice (CoP) that need to be taken into account in evaluation processes, such as geographical dispersion. The fact that VCoP rely on Information and Communication Technologies (ICT) to execute their practices as well as storing artifacts virtually makes more consistent data analysis possible; thus, the evaluation process can apply automatic data gathering and analysis. Methodology: A systematic mapping study, based on five research questions, was carried out in order to analyze existing studies about VCoP evaluation methods and frameworks. The mapping included searching five research databases resulting in the selection of 1,417 papers over which a formal analysis process was applied. This process led to the preliminary selection of 39 primary studies for complete reading. After reading them, we select 28 relevant primary studies from which data was extracted and synthesized to answer the proposed research questions. Contribution: The authors of the primary studies analyzed along this systematic mapping propose a set of methods and strategies for evaluating VCoP, such as frameworks, processes and maturity models. Our main contribution is the identification of some research gaps present in the body of studies, in order to stimulate projects that can improve VCoP evaluation methods and support its important role in social learning. Findings: The systematic mapping led to the conclusion that most of the approaches for VCoP evaluation do not consider the combination of data structured and unstructured metrics. In addition, there is a lack of guidelines to support community operators’ actions based on evaluation metrics.

Social Media Use and Its Effect on Knowledge Sharing: Evidence from Public Organisations in Delta State, Nigeria

Abstract: Aim/Purpose This study investigates social media use and its effect on knowledge sharing. Based on the review of related literature, we hypothesised that social media use has a significant effect on outward and inward knowledge sharing. Background While the notion of social media use in work organisations has been progressively developed, empirical studies linking social media to the context of knowledge sharing have only begun to emerge. Even so, literature on social media use and its impact on public organisation is still tentative and remains a developing area. Methodology The partial least square method was utilised in testing of hypotheses with data collected from 103 employees, who by virtue of their position and job function(s) interface with the public for the purpose of sharing knowledge via the social media space. Contribution The study made contributions to the social knowledge management literature in two ways. First, the study developed a research model that links social media use to the two distinct dimensions of knowledge sharing. Second, the study provides a quantitative approach, where statistical techniques were applied to validate the social media use and knowledge sharing link. Findings Statistically, the public organisations utilise social media partly for knowledge sharing, with its effect being significant on outward knowledge sharing and insignificant on inward knowledge sharing. This indicates that social media were deployed mainly for information dissemination “outward knowledge sharing” and not for stakeholders’ feedback and interaction “inward knowledge sharing”. Social Media Use and its Effect on Knowledge Sharing 26 Recommendations Public organisations should develop a policy framework and guidelines for social media use to encourage the full use of this technology to inform and interact with stakeholders. It is important for this policy document to adopt best practices regarding interactive spaces so that both knowledge sharing dimensions manifest themselves in social media communications. Second, it is necessary to carry out staff training for the professional use of this technology for knowledge sharing. Future Research Future studies may extend to public organisations in other geographical locations around Nigeria. It will be useful for studies to provide an international perspective by sampling public organisations from different countries or by comparing and contrasting the findings of other studies, specifically those from other countries. A longitudinal study should be encouraged to detect advancement or development with regards to the subject matter over a period of time.

An Exploratory Study on the DevOps IT Alignment Model

Abstract: Aim/Purpose Based on business-IT alignment, this study addresses the understudied practice of DevOps. Background Although organizations continue to implement DevOps practices, few studies explore connections with prior theory. This study contributes to this need by developing the DevOps strategic IT alignment model. Methodology The sample included 57 firms from the current Forbes Global 2000 and the Fortune 500 lists. The authors employed partial least squares structural equation modeling (PLS-SEM) to evaluate the DevOps IT alignment model. Contribution The proposed model builds a foundation for further investigation into the influence of theory on DevOps using quantitative research methods. It also contributes to a reliable and valid DevOps instrument for future exploration. Findings Continuous integration of software and knowledge sharing increases the level of IT subunit alignment in large organizations that foster DevOps. Furthermore, practicing DevOps positively influences the level of business-IT alignment. Recommendations for Practitioners Organizations that cultivate DevOps experience greater levels of business-IT alignment through stronger knowledge sharing and continuous integration of applications. Thus, managers should identify how to develop closer bonds between subunits with dissimilar skillsets in their organizations. Recommendations for Researchers Researchers should explore how theories interact, help, and/or do not support blossoming practices like DevOps. An Exploratory Study on the DevOps IT Alignment Model 128 Impact on Society Stronger bonds increase knowledge sharing between interdepartmental colleagues. Lower hierarchical levels of an organization as well as higher managerial levels benefit from cross-domain IT knowledge. Future Research It is important to explore how different types of knowledge in diverse disciplines requires unique cross-discipline bonds to form and whether these relationships have connections with the contingency theory and quality management.

Enterprise Knowledge Generation Driven by Internet Integration Capability: A Mediated Moderation Model

Abstract: Aim/Purpose: Drawing on theories of organizational learning, this study analyzes the mechanism of Internet integration capability affecting knowledge generation by 399 Chinese enterprises. This paper will further explore whether there is a moderating role of learning orientation in the mechanism of Internet integration capability affecting enterprise knowledge generation. Background: The Internet has gradually integrated into the enterprise innovation system and penetrated into all aspects of technological innovation, which has promoted the integration and optimization of resources inside and outside the organization. However, there is limited understanding of how the combination of the Internet and integration capability can drive enterprise knowledge generation. Methodology: The study uses survey data from 399 organizations in China. Through structural equation modeling, this study assesses the relationship between Internet integration capability, organizational learning, knowledge generation, and uses PROCESS macro program to test the mediated moderation effect of learning orientation. Contribution: First, this study provides empirical evidence for managers to better build Internet integration capability and ambidextrous learning to promote enterprise knowledge generation. Second, this study highlights the important moderating role of learning orientation in the mediating role of ambidextrous learning. Findings: First, the study confirms the mediating role of exploratory learning and exploitative learning in knowledge generation driven by Internet integration capability. Second, the results show that when organizations have a strong learning orientation, the indirect path of Internet integration capability influencing knowledge generation through exploratory learning will be enhanced. Recommendations for Practitioners: Enterprises should pay full attention to the improvement of internet integration capability and ambidextrous learning to promote knowledge generation. In addition, enterprises should establish a good learning atmosphere within the organization to strengthen the bridge role of exploratory learning between Internet integration capability and knowledge generation. Recommendation for Researchers: Researchers could collect data from countries with different levels of economic development to verify the universal applicability of the proposed theoretical model. Impact on Society: This study provides references for enterprises using Internet integration capability to promote their knowledge generation capability under the internet background. Future Research: Future research can compare the impact of Internet integration capability on knowledge generation in different industries.