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Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view
... 28 However, the decision-making capability (DMC) is not yet mature in the government sector; it is time-consuming and requires the consensus of a larger group of people. 24,29,30 Different factors of the decision-making process affect the adoption and use of big data analytics 28,31 such as the organizational culture. 27 Various scholars 27,28,[32][33][34][35] have explored the challenges and the opportunities of BDAC in the government sector. ...
... Furthermore, the DMC in the government is still based on organizational and bureaucratic cultures, 24,29,30 and most existing studies in the literature have analyzed the effect of organizational culture on BDAC, [70][71][72] whereas few have investigated the impact of BDAC on organizational culture. 49 We endeavor to fill this gap and examine the role of cognitive style of decision makers and organizational culture in the relationship between BDAC and DMC within the 4 FARIDOON ET AL. ...
... This is valuable because many government organizations are still struggling to generate the expected benefits of BDAC. 105 Decision makers can use the generated insights from big data analytics to augment their decision-making process 29,45 and speed it up to take informed decisions. 16,17,106 Our empirical results (via the f 2 method) further show that a well-established DMC is inevitable for the government sector considering the 12,15,36 argue that the main challenges in adopting BDACs are organizational rather than technical. ...
The government sector has started adopting big data analytics capability (BDAC) to enhance its service delivery. This study examines the relationship between BDAC and decision-making capability (DMC) in the government sector. It investigates the mediation role of the cognitive style of decision makers and organizational culture in the relationship between BDAC and DMC utilizing the resource-based view of the firm theory. It further investigates the impact of BDAC on organizational performance (OP). This study attempts to extend existing research through significant findings and recommendations to enhance decision-making processes for a successful utilization of BDAC in the government sector. A survey method was adopted to collect data from government organizations in the United Arab Emirates, and partial least-squares structural equation modeling was deployed to analyze the collected data. The results empirically validate the proposed theoretical framework and confirm that BDAC positively impacts DMC via cognitive style and organizational culture, and in turn further positively impacting OP overall.
... Teece et al. explain how an organization's position affects the organization's strategic position and how competitive advantage is achieved. Paths are about the past events of the organization and whether the past and present of the organization guide or limit its future (Teece et al., 1997;Shamim et al., 2019). ...
... Likewise, organizations that fund in R&D hope that resource excellence will result in excellent product design or productive processes. If this works, it will result in a change in underlying resources, and it can be seen how dynamic capabilities can be considered as fixed, repetitive functions (Shamim et al., 2019). Winter (2003) also believes that the rate of alternation in the organization's behavior is a random element in the decision-making to expand and increase dynamic capabilities. ...
... This focus on the position of managers of how they understand their environment and their frost is an important factor in understanding why and how to develop dynamic capabilities (Shamim et al., 2019). For example, managers who see the environment as complex may have difficulty identifying Which dynamic function to apply and might be avoided to perform it. ...
Today, rapidly changing environmental conditions have necessitated the emergence of new and dynamic working groups that can adapt to these new conditions and the emergence of new leadership types that will guide these groups. In this research, it is aimed to examine all aspects of transformational leadership and dynamic capabilities and the effect of fulfilling these concepts on businesses. This research shows the relationship between the transformational leadership and the dynamic capabilities of the organization and explores their direct or indirect effects on the organizational performance. The research draws on recent leadership literature and examines the methods, data, and research resources used in the relationship between the transformational leadership and the dynamic capabilities in the businesses. The data used in this research are the results of studies conducted by various researchers and authors in the last thirty years. The findings of the research has shown that the behavior of transformational leaders can enhance the dynamic capabilities of employees and encourage innovation. From the findings of the research, it is seen that the characteristics of the transformational leaders inspire the creation of the dynamic capabilities and develop the necessary personal approaches for the dynamic capabilities. In this context, it is expected that the transformational leadership functions of the top manager and the organizational structure will greatly affect the measurement dynamics
... To identify its customers' 13 preferences, Netflix monitors their scrolling and browsing behaviours by collecting data on 14 when they pause, rewind, fast-forward, etc. (Zeng & Glaister, 2018). 15 Existing literature also acknowledges the importance of big data's enhancement of decision- 16 making quality (Shamim, Zeng, Shariq, & Khan, 2018) and value creation across different 17 sectors, including manufacturing and media (Zeng & Glaister, 2018), banking (Hale & Lopez,18 2017), healthcare (Wang, Kung, Wang, & Cegielski, 2018), tourism and hospitality (Li, Xu, 19 Tang, Wang, & Li, 2018), etc. Enabled by digital technology, big data have emerged as the 20 central tool aiding enterprises to facilitate exploitative and explorative activities (McAfee, 21 Brynjolfsson, & Davenport, 2012). While many scholars and practitioners have emphasised 22 the skills needed for exploitative activities, others have highlighted the importance of 23 exploratory activities (e.g., Janssen, van der Voort, & Wahyudi, 2017; Zeng & Glaister, 2018). 1 Central to this view is an emphasis on ambidexterity (Turner, Swart, & Maylor, 2013). 2 Ambidexterity is defined as a firm's ability to reconcile two opposite strategies (for example, 3 simultaneously pursuing both exploration and exploitation) within itself (O'Reilly & Tushman, 4 2013; Simsek, 2009). ...
... This study follows the framework of 23 knowledge-based dynamic capabilities (KBDC), which emphasise knowledge activities. The 24 literature suggests that knowledge activities at any level initially require the willingness of 1 individual employees (Shamim, Cang, & Yu, 2017b). Kim and Lee (2013) also argued that in 2 order to meet increasing customer expectations, firms need to focus on knowledge activities 3 at the individual employee level. ...
... These 18 capabilities can present companies with several business imperatives, in other words, they 19 can enhance the ability for data-driven decision making, which would enable managers to 20 decide on the basis on what they know as opposed to what they think (Janssen et al., 2017;21 McAfee et al., 2012). Literature also suggests that management proclivities towards big data 22 can strengthen value creation through big data; for example, a combination of the right 23 leadership, talent management, culture and technology is important for big data value 1 creation (Shamim et al., 2018). The results of this study suggest that big data value creation 2 mediates the relationship of big data management capabilities with exploitative and 3 exploratory activities. ...
Drawing from the knowledge-based dynamic capabilities (KBDCs) view, this study examines the association of big data management capabilities with employee exploratory and exploitative activities at the individual level. Furthermore, it also investigates the mediating role of big data value creation in the association of big data management capabilities with exploratory and exploitative activities. The partial least square method was employed to analyse the hypotheses using data collected from 308 employees of 20 Chinese multinational enterprises. The existing literature gives scant attention to the role of big data management capabilities at the individual level. The main contribution of this study is that it conceptualises big data management as the ability to utilise external knowledge (generated from global users) under the resource constrained environment of an emerging economy. Furthermore, this study builds upon the existing literature on KBDC to explain big data management capabilities as antecedents to ambidexterity at the individual employee level.
... Besides technological meaning, BDA refers to data-driven culture that convinces the manager to look beyond the tried-andtrue methods in an organizational setting. BDA introduces a new age of intelligence and understanding for flexible managerial decision-making in a firm focused on entrepreneurship (Abbady et al., 2023;Shamim et al., 2023). ...
... The researchers mentioned above have all demonstrated the positive relationship between employees' entrepreneurial orientation and BDAC. In addition to its technological implications, BDA introduces a new dimension of intelligence and understanding, referred to as big data analytical capability, which enables dynamic managerial decision-making within an entrepreneurial-focused company (Shamim et al., 2023). Numerous researchers and scholars have empirically demonstrated this over the past decade (Asadi et al., 2023;Ciampi et al., 2021;Dubey et al., 2023). ...
Information technology-based management capabilities are considered the major contributors to workplace culture transformation that are further categorized as artificial intelligence and big-data analytics capabilities. The primary purpose of this study is to explore the developments made in the domain across the globe and future potential inclination and trends on this topic. Bibliometrix 3.0’ package of the r-program is used to present the influential aspects of literature and related conceptual framework of IT-based dynamic capabilities and Firm Entrepreneurial Performance. We used co-citation analysis and bibliometric coupling to identify key research streams and themes. The inferential results of the study suggest that ‘Journal of Business Research’ and ‘Technological Forecasting and Social Change’ are core sources of published literature related to IT-based management capabilities. The USA is a leading country, and the Norwegian University of Science and Technology is the most relevant affiliation, and Gunasekaran, A. is the impactful contributor. Three research themes (clusters) are identified; a) organizational transition to machine learning, b) implementation of IT-based dynamic capabilities for sustainable supply chain and business outcomes, and c) IT-based capabilities, digitalization, SMEs, knowledge management and competitive business outcome. The study also identifies key research streams for future directions using bibliometric coupling.
... 2016; Shamim et al., 2018). Besides, some studies have pointed out that social capital is not enough to construct big data capability, physical assets, or human traits, such as employee experience, knowledge, leadership qualities, and social relationships which are needed (Akter et al., 2016). ...
... Hypothesis 1: BDRA capability is positively associated with BDRIU capability. Existing research from operations management (Wang et al., 2016;Wamba et al., 2015), management decisions (Alstete & Cannarozzi, 2014;Janssen et al., 2017;Shamim et al., 2018), and corporate performance (Chen et al., 2015;Gupta & George, 2016;Akter et al., 2016) explored the value creation of big data analytic. Research has pointed out that big data can bring about different innovations, from processes to products, to value creation architectures or new business models (Caputo et al., 2016;George & Lin, 2017). ...
This paper explores the relationship between big data capability and organizational innovation and the formation mechanism of big data capability based on resource orchestration theory. Data was collected from 179 questionnaires and used to empirically test the model. Our findings suggest that big data resources acquisition capability (BDRA) is conducive to the construction of big data resources integration and utilization (BDRIU) capability and thus can actively promote product innovation. Throughout this process, the big data expected benefits negatively influence the relationship between BDRA capability and product innovation and positively influence the relationship between BDRIU capability and product and business model innovation. In terms of the formation mechanism of big data capabilities, government support has a significant positive impact on the BDRA and BDRIU capabilities. Data governance partially mediates the relationship between government support and big data capabilities.
... A leadership style that comprises components such as inspiration and interaction is called knowledge-oriented leadership. The concept of knowledge-oriented leadership was only recently developed (Shamim et al., 2019) and not very well understood in a true sense (Mohsenabad & Azadehdel, 2016). ...
... The capability to gain competitive advantage depended on the selection of leadership and innovation (Sheng, 2017). In this context, a recent development of the knowledge-oriented leadership concept has gained much attention (Shamim et al., 2019;Donate & de Pablo, 2015). It offers the instilling of extraordinary potential within individuals and enables the creation and application of new knowledge, which is key to innovation performance. ...
The manufacturing sector is an indispensable part of a country's economic system. For Malaysia, it not only helps in transmuting raw material to finished goods but also an essential driver to the country's economic growth. Owing to this sector, Malaysia holds a remarkable position in exports across the world. It is also a principal contributor to the employment of the country. Although, the manufacturing industry is deemed as the backbone of a country's growth, however, the industry also faces many challenges with technological advancements due to the industrial revolution known as Industry 4.0.The aim of Industry 4.0 is to realize productivity and improve efficiency. Its potential disruptive technologies are altering the way of work. Correspondingly, it poses challenges for organizations to innovate and in analyzing their readiness for Industry 4.0. Thereby, current research aimed to investigate the key role of organization innovation and its enablers including electronic human resource management, knowledge-oriented leadership and decentralized organization structure. In addition, change in demographics has shaped another snag in the form of an aging workforce for manufacturing companies. Ergo, the moderating role of the aging workforce was gauged in support to readiness for Industry 4.0 by using Structural Equation Modelling.A quantitative method was adopted to establish the relationship between the variables. By using self-administered questionnaire, a total of 218 useful responses from manufacturing companies of Malaysia were collected and examined through SmartPLS 3 software. The results highlighted the important dual role of organization innovation for readiness of Industry 4.0. It further confirms the moderating act of aging workforce in relationship between organization innovation and readiness for Industry 4.0.Current research contributed to the body of knowledge a detailed vision of Industry 4.0 and its significance for manufacturing sector in Malaysia. The research findings confirmed a noteworthy knowledge concerning high dependency of readiness for Industry 4.0 on organization innovation and moderating effect of aging workforce between them. Additionally, electronic human resource management and knowledge-oriented leadership were also identified as an enabler of organization innovation through empirical examination. The moderating role of organization innovation is of high interest for keen researchers. Current research provides a directive for practitioners to pave the way for successful implementation of Industry 4.0. Forbye, the research outcomes are thoughtprovoking to national policymakers which can aid in development of impressive policies for Industry 4.0 while considering the vital role of organization innovation and aging workforce.
... Leveraging the capabilities of the Internet and emerging technologies, Energy Internet has realized intelligent management of enterprise energy use information [ [35,36]]. Transparency of energy information is conducive to a comprehensive grasp of energy consumption within the enterprise, thus reducing irrational behavior of management in energy use and environmental protection [ [37]]. Therefore, Energy Internet can improve the information environment, thereby optimizing the internal governance mechanism of companies, enhancing the operational and managerial efficiency of enterprises, and ultimately improving the ESG performance of firms. ...
Under the challenges of global crises such as climate warming, ESG performance, which represents sustainable development, has received widespread attention at home and abroad. Using the panel data from 2011 to 2020, comprising 726 high energy-consuming companies listed on the Shanghai and Shenzhen A-shares, this paper takes Energy Internet demonstration project in 2016 as a quasi-natural experiment and builds a difference-in-difference model to study its microscopic policy effects. The study found that, firstly, Energy Internet can markedly enhance ESG performance of high energy-consuming companies. Secondly, the mechanism test finds that Energy Internet can facilitate high energy-consuming enterprises to enhance their ESG performance through three mechanisms: increasing government subsidies for enterprises in energy conservation and environmental protection, absorbing talent employment and improving information environment within the enterprises. Finally, the heterogeneity analysis proves that Energy Internet's policy effects are more pronounced in regions with higher financial expenditures on local science undertakings and among state-owned enterprises. China ought to persist in advancing the development of Energy Internet and provide companies with adequate support on finance, talent and technology. Meanwhile, during the construction of Energy Internet, attention should be paid to adapting to local conditions and enterprises.
... When storing and processing financial-related data, enterprises often cannot effectively save data other than financial data due to technical conditions, resulting in onesided financial analysis results [8][9]. Therefore, traditional financial decision-making methods are no longer sufficient to support corporate decision-making, provide timely and effective support, and meet the needs of management [10][11]. ...
Exploring the effectiveness of the application of big data technology in financial decision management of enterprise cloud accounting is to help better enterprises achieve economic growth and sustainable development. In this paper, a decision tree algorithm based on information gain and attribute dependency is jointly analyzed under big data technology using attribute dependency of rough set theory, attribute parsimony algorithm, and information gain of ID3 algorithm. The analysis of enterprise cloud accounting and financial decision-making is explained, including the process and content. The data analysis of financial decision management of WK Group, BL Real Estate, and LD Holdings is carried out using a decision tree algorithm. In terms of financing structure, debt financing mainly consists of long-term borrowings, short-term borrowings, and bonds payable, accounting for 66.06%, 21.18%, and 12.76%, respectively. In terms of gearing ratio, the average ratios of WK Group, BL Real Estate, and LD Holdings are 76.6%, 81.54%, and 80.05%, respectively. It shows that the decision tree algorithm based on information gain and attribute dependency can effectively perform corporate financial decision management analysis and visualize the company’s sustainable development strategy through the data.
... Big data technology is a field that has developed rapidly in recent years, which also promotes the development of intelligent life and production [7,8]. e core advantage of big data technology is the processing of cumbersome data. ...
Music art is a form of conveying cultural information and humanistic emotions. From ancient times to the present, the form of music has undergone great changes. The change of music form is closely related to the change in dynasties, the development of the market economy, and the change in humanistic spirit. Today, the development of music has reached a relatively prosperous stage, which is closely related to the rapid development of the market economy. At the heart of the quantitative analysis is the study of associations between data. However, it will be a difficult task to analyze the relationship between the development scale of the market economy and the form of music innovation only by artificial means. This research mainly uses a convolutional neural network and long and short-term memory neural network technology to quantitatively analyze the relationship between the development scale of the market economy and the form of music innovation, which is mainly a quantitative analysis of classical music, pop music, and rap music. The research results show that convolutional neural networks and long short-term memory neural networks have sufficient capabilities to quantitatively analyze the relationship between the market development scale and the form of music innovation. Neural networks with LSTM layers have lower errors in predicting market economic correlates than neural network methods without LSTM layers. The error is reduced by 0.27%. For the prediction of innovative forms of music, the largest prediction error is only 2.93%, which is closely related to the variability of popular music. The linear correlation indices for the predictions of the three forms of musical innovation also all exceed 0.955.
Business environments are getting increasingly dynamic and data-intensive because of the emerging technologies and advances in data science, and information and communication technologies, which require enterprises to make regular and quick decisions to cope with the changes. This paper explores how big data influences decision-making processes and, consequently, organizational design in turbulent business environments. This study uses a qualitative approach (multiple case-study) by applying interviews to gain rich and illuminating data from organizations that use large data sets as a source of information based in the UK. In total, 12 participants from 9 organizations were chosen for the interviews who had a deep understanding of organizational and information-processing mechanisms, such as CEOs (chief executive officers), data analysts, data consultants, CIOs (chief information officers) and middle managers. This study contributes to decision-making theory by providing new insights about dynamic decision making in the context of big data and a better understanding of organizational strategies (either developing new dynamic capabilities or reconfiguring the current ones) for working with and leveraging value from big data. In addition, for the practical aspect, it contributes to guiding decision-makers in evaluating their organizations in terms of required capabilities and processes to become better enabled to reap value from big data.KeywordsBig dataDecision makingDynamic capabilitiesOrganizational design
As of late, “STAY AT HOME” is the main slogan; household needs are constantly changing for many reasons, such as the change in the human life cycle, the shift to smart cities, and adopting new modern technologies to reduce the risks. However, while moving to a smart solution, many forgotten social dimensions are being interpreted into the design of many services, including housing. Accordingly, this study aims to explore housing flexibility through a review of relevant literature and how housing design will change to accommodate new needs through quarantine and spread of Corona virus Disease 2019 (Covid-19) to formulate new design codes for stakeholders and real-estate developers to consider in the future. It examines the impact of quarantine on personal household priorities, house design, and how they innovate in their interior design to suit their new needs by conducting a wide online social survey. The research uses an online survey to evaluate the importance of the new arrangement of household requirements using quantitative analysis tools and techniques. The findings display housing guidelines to apply housing design flexibility to cope with any external or internal changes that may happen in the next period and affect household needs in smart cities and others.KeywordsHousing flexibilityBasic needsCOVID-19QuarantineHofficeOnline survey
The role of big data in implementing supply chain finance (SCF) initiatives lacks empirical study. There is little guidance available for managers on developing an integrated SCF process in the era of big data. Using organizational information processing theory, this study develops and empirically tests a theoretical framework that investigates the effect of big data analytics capability (BDAC) on SCF Integration, and the moderating effect of data-driven culture. The hypothesized relationships were tested using structural equation modelling and moderated regression analysis, with primary survey data collected from a sample of 307 manufacturing firms in China. The results indicate that BDAC has a significant positive effect on internal SCF Integration, and internal SCF Integration fully mediates the relationships between BDAC and SCF Integration with customers and suppliers. Data-driven culture significantly moderates the effect of BDAC on internal SCF Integration. These empirical findings provide timely and useful guidance for managers on using big data analytics and data-driven culture to implement integrated SCF practices to survive in today's data-rich and uncertain environment.
The business world is continually changing. Dynamic environments, full of uncertainties, complexities, and ambiguities, demand faster and more confident decisions. To compete in this environment, Industry 4.0 emerges as an essential alternative. In this context, the reliability of manufacturing is an essential aspect for companies to make successful decisions. In the literature, several technologies associated with Industry 4.0 have been applied to improve the availability of equipment, including the Internet of Things (IoT), Cyber-Physical Systems (CPS), blockchain, and data mining. Nevertheless, there is still no survey study that seeks to show how reliability has collaborated to support decision-making in organizations, in the context of Industry 4.0. In general, most applications still focus on the productivity and health of individual equipment. However, in today's volatile and complex businesses, local decisions are no longer sufficient; it is necessary to analyze the organization entirely. Thus, being aware of the impacts that a local failure can impose on the entire company has significant weight in the decision-making process. In this context, this article presents a survey to identify how researches on systems reliability has contributed to and supported the development of decision-making in Industry 4.0. The main contribution of this article is to highlight how reliability can be used to support different types of strategic decisions in the context of Industry 4.0. Finally, it highlights the need for research associating management decisions with the technologies of Industry 4.0.
This study examines the interdependence of relational strategies and data management policies of SMEs during product innovation. The type of data management developed by a small firm to support its innovation efforts requires it to engage in competitive, vertical cooperative or coopetitive relationships. An empirical study of 109 leaders of French high-tech SMEs provides a descriptive and explanatory analysis of this question. This empirical study combines three theoretical dimensions: the characteristics of a Big Data policy, of an innovation product and of a relational strategy. We enrich the existing knowledge concerning the exploitation of data by SMEs by presenting a typology of their data strategies. We also find that Big data and Smart data policies are deployed by SMEs to support product innovation. Finally, we show that SMEs implement data management individually to support radical product innovation but will collaborate to support incremental product innovation. The nature of the data innovation guides the relational context of the SME. This study deepens the interdependence of data management and relational strategies among SMEs.
Nowadays, big data analytics (BDA) have widely used in our business environment as an undeniable function for firms to not only survive in turbulence but also have the opportunity to be ahead of their major competitors. One of the promising aspects of BDA relates to its influence on innovation performance. In line, the present study proposed a conceptual model in order to investigate the relationship between BDA use and innovation performance by considering the role of dynamic capability (DC) theory. In this research, we consider firm agility in terms of DC theory and decompose it into three main factors contacting sensing agility, decision making agility, and acting agility. The research model and required data were analyzed using Partial Least Squares (PLS)/Structured Equation Modelling (SEM). The outcome of this study indicates that firms would be able to increase their innovation performance from a DC theory. This study also shows that BDA use has a positive influence on sensing agility of firms.
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