The intermediating role of organizational culture and internal analytical knowledge between the capability of big data analytics and a firm’s performance

Influencing mechanism of the intellectual capability of big data analytics on the operational performance of enterprises

In the era of big data, data processing capability is key to gaining a competitive advantage for businesses. With appropriate technical and organizational resources in place, enterprises can extract considerable value from the vast amount of available data, thereby increasing their competitive advantage. Therefore, to utilize big data resources effectively, enterprises should focus on improving the intellectual abilities of big data analysts. Big data analytics intellectual capability (BDAIC) refers to the specialized skills and knowledge that employees of the enterprise possess, including technical, technical management, business, and relational knowledge, that would enable them to use analytics tools to accomplish organizational tasks and shape the core competitiveness of an enterprise. This study constructs a theoretical model that focuses on the mediating role of person-tool fit and examines the mechanisms by which BDAIC affects an enterprise's operational performance. The results show that BDAIC, which contains four basic categories of knowledge, positively influences an enterprise's operational efficiency. Additionally, person-tool matching mediates BDAIC's effect on an enterprise's operational performance. These findings explore the latest avenues of exploration in the research paradigm of big data analytics. Furthermore, this study has important implications for practitioners trying to use big data to improve business performance.

The Impact of Big Data Analytics on Decision-Making Within the Government Sector

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.

Interplay between Networking Capability and Hospital Performance in Indonesia's Medical Tourism Sector

Medical tourism is an industry that is currently developing, but research that focuses on the analysis of supply and institutions as a unit in Indonesia is sparse. This research aims to investigate the variables of digital transformation and resource integration that influence hospital performance, considering the expansion of hospitals' capacities for networking in medical tourism. A structural equation model is used to evaluate the hypothesis. According to our findings, digital transformation and resource integration both have a beneficial effect on networking capabilities. On the other hand, the implementation of digital transformation does not improve hospital performance. Digital transformation has a good link with hospital performance but has no statistically significant effect on hospital performance. In the meantime, the capabilities of resource integration and networking have a positive effect on the overall operation of hospitals. In a similar vein, the ecosystem of medical tourism helps to improve the connection between a hospital's networking capabilities and its overall performance. It is anticipated that the findings of this study will serve as a reference for those in the policymaking and healthcare industries to develop medical tourism.

Influence of big data analytical capability on new product performance – the effects of collaboration capability and team collaboration in high-tech firm

Purpose

As the application of artificial intelligence (AI) becomes more prevalent, many high-tech firms have employed AI applications to deal with emerging societal, technological and environmental challenges. Big data analytical capability (BDAC) has become increasingly important in the AI application processes. Drawing upon the resource-based view and the theory of planned behavior, this study aims to investigate how BDAC and collaboration affect new product performance (NPP). Practically, a harmonic working team is particularly important for creating management synergies, this empirical analysis demonstrates the importance of BDAC and collaboration for NPP.

Design/methodology/approach

This paper focuses on the performance of firms that applied AI in their operations. This study collected data from firms in Greater China, including China and Taiwan, as Greater China is currently the leading manufacturer of semiconductor, electronic and electric products for AI applications in the manufacturing process. Confirmatory factor analysis and structural equation modeling is employed for statistical analysis.

Findings

The analytical results indicate that BDAC positively relates to collaboration capability (CC) in AI applications but not to team collaboration (TC). CC positively correlates with TC, and both CC and TC positively correlate with NPP. Further, the mediating effect was examined using the Sobel t-test, which reveals that CC is a significant mediator in the influence of BDAC on NPP.

Practical implications

The strategic implementation of BDAC and collaboration can allow an enterprise to improve its NPP when driven by the external environment to use AI, which further enhances NPP. These processes indicate that AI and BDAC are both crucial for the success of a company’s collaboration and for effective management to improve NPP in the face of global competition.

Originality/value

This study introduces the concept of BDAC to explain the relationship between CC and TC, as they pertain to NPP. This study presented a discussion of the theoretical and practical implications of the research findings and could provide a framework for managing BDAC.

Impact of corporate sustainable practices, government initiative, technology usage, and organizational culture on automobile industry sustainable performance

The increasing worldwide automobile production and usage adversely impact the environmental, economic, and social well-being. Although the automobile companies are trying to solve this problem by adopting corporate sustainability, there is a gap in the extant literature on sustainable corporate practices that are the most important to empower better sustainability performance. This study highlights the impact of core corporate sustainable practices attributes, government initiative, technology usage, and organizational culture on the sustainable performance of the automobile industry in India. The study proposed six aspects and fifty-three criteria from the literature review. The current article has used survey questionnaires to collect the primary data. The present article also applied the smart-PLS to test the association among the variables. The results indicated that the corporate sustainable practices attributes, technology usage, and organizational culture have a positive and significant linkage with the sustainable performance of the automobile industry. The current article guides the regulators in developing the regulations to improve sustainable organizational performance using sustainable corporate practices.

Analysis of factors affecting the implementation of green human resource management using a hybrid fuzzy AHP and type-2 fuzzy DEMATEL approach

The topic of green human resource management has attracted considerable attention during this last decade. Despite this interest, little research has been conducted to explore the successful implementation of green human resource management to achieve environmental sustainability goals. Therefore, this study aims to identify the factors affecting the effective implementation of green human resource management in petrochemical companies in Bushehr City. This research is the first article that has evaluated green human resource management measures in petrochemical industries, and on the other hand, it can be stated that it is the first paper to perform green measures of human resource management using the combined method of fuzzy hierarchical analysis and type-2 fuzzy DEMATEL. The present study seeks to identify these factors and examine their relationships based on existing theoretical foundations and expert opinions. Based on results, factors affecting green human resource management implementation were divided into five categories: recruitment and employment, training and development, performance appraisal, service compensation and reward, and green organizational culture management. In other words, a total of five criteria and twenty green sub-criteria were identified for the implementation of green human resource management. Fuzzy AHP and type-2 fuzzy DEMATEL were applied to determine the weights of the criteria. The results showed that the process of green training and development is the most critical factor in the effective implementation of green human resource management. Also, training and development processes, service compensation, and green organizational culture management are affecting factors to achieve this critical issue. In order to implement green human resource management, this study has proposed the priority of green measures for petrochemical industry managers.

Identifying the Key Big Data Analytics Capabilities in Bangladesh’s Healthcare Sector

The study explores the crucial big data analytics capabilities (BDAC) for healthcare in Bangladesh. After a rigorous and extensive literature review, we list a wide range of BDAC and empirically examine their applicability in Bangladesh’s healthcare sector by consulting 51 experts with ample domain knowledge. The study adopted the DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method. Findings highlighted 11 key BDAC, such as using advanced analytical techniques that could be critical in managing big data in the healthcare sector. The paper ends with a summary and puts forward suggestions for future studies.

Antecedents and consequences of adopting CLTS among tribal communities to become open defecation free: case study on Indian Swachh Bharat Abhiyan

The Swachh Bharat Mission undertaken by the Government of India (GoI) has been successful in accomplishing this objective within a short period thereby catalyzing governance following Sustainable Development Goals (SDGs). It is the responsibility of any democratic nation to ensure that its citizens have universal access to adequate and equitable sanitation. The key approach adapted to igniting a change in sanitation behavior rather than constructing toilets. An effort has been made in the study to affirm that even the marginalized sections of the society residing in tribal communities of West Bengal and Chhattisgarh have benefitted from this Government of India Mission and derived the required benefits. There is enough literature available to support the justification that civil participation holds the key for successful implementation of CLTS thereby making the communities open defecation free (ODF). It is therefore imperative to understand the behavioral transformation that takes place during the CLTS implementation. A hybrid model has been proposed in the study making use of the theory of reasoned action (TRA) and theory of planned behavior (TPB) to understand the pre-adoption and post-adoption behavior of residents. In present study, used model was empirically tested for several hypotheses. The finding reflects towards subjective norms and facilitating conditions as major determinants that ensure the continuation of intention for CLTS. They play a pivotal role in improving the health and hygiene conditions in the region and thus decrease the risk of spread of epidemic diseases.

The Impact of Integration of Industry 4.0 and Internal Organizational Forces on Sustaining Competitive Advantages and Achieving Strategic Objectives

Adopting and implementing the Industry 4.0 strategy to increase the overall performance of the organization became one of the main aims of organizations. However, ignoring the linkages between implementing strategic decisions and organizational internal factors/forces can endanger and shrink its performance, competitive advantages, and thus its strategic success. In this context, many companies failed to achieve the expected benefits of adopting the Industry 4.0 strategy. Therefore, the gained advantages of adopting the Industry 4.0 strategy should be sustained through perfect and comprehensive integration between Industry 4.0 concepts and the accompanying upgrades and changes in the organizational internal factors/forces. This will capitalize on organizations’ internal strengths and avoid weaknesses or turn them into strengths. In this paper, a conceptual model is proposed to investigate the relation between Industry 4.0 and internal organizational forces and examine their impacts on the sustainable competitive advantages of the organization. In the hypothesized model, three innovation capabilities (i.e., technological, economic, and commercial innovation) have been used to mediate the relation between the internal forces and the sustainable competitive advantages in parallel with Industry 4.0 adoption. The model and the proposed hypotheses have been simulated and tested using partial least squares structural equations modeling software called SmartPLS. The sample size used is 125 responses from different manufacturing fields. The results demonstrate the significant role that the internal organizational forces play in maintaining and sustaining the organization’s competitive advantages in combination with Industry 4.0.

Entrepreneurial Leadership and Entrepreneurial Success: The Role of Knowledge Management Processes and Knowledge Entrepreneurship

Various leadership styles have been widely studied to understand success. However, little research has empirically explored how entrepreneurial leadership (EL) influences entrepreneurial success (ES). Moreover, the role of knowledge management processes (KMPs) and knowledge entrepreneurship (KE) have been overlooked. Thus, using a knowledge-based view theory, this study aims to determine the relationship between EL and ES, mediated through KMPs. In addition, for a better understanding, the study also used KE as a moderator. A quantitative survey method has been employed to collect data from 390 entrepreneurial venture (EV) owners, co-founders, and managers in tech-oriented ventures (IT and Software-based) operating in Pakistan. Smart partial least squares (PLS) statistical software was used to analyze the impact mechanism of EL on ES through the structural equation model. The findings revealed that EL style positively influences ES. In addition, KMPs fully mediate the relationship between EL and ES. Furthermore, KE as a moderator, strengthens the relationships between EL and the knowledge management process. Theoretically, this study has complemented and enriched research on the influence mechanism between EL and ES. Practically, this study has important implications for leaders, managers, and founders to promote KMPs to achieve ES.

Human-related capabilities in big data analytics: a taxonomy of human factors with impact on firm performance

This study intends to provide scholars and practitioners with an understanding of human resource challenges in the context of Big Data Analytics (BDA). This paper provides a holistic framework of human-related capabilities that organizations must consider when implementing BDA to facilitate decision-making. For this purpose, the authors conducted a systematic literature review adapted from Tranfield et al. (BJM 14:207–222, 2003) to identify relevant studies. The 75 publications reviewed provided the sample for an inductive, and systematic data evaluation following the well-known and accepted approach introduced by Gioia et al. (ORM 16:15–31, 2012). The comprehensive review uncovered 33 first-order concepts linked to human-related capabilities, which were distilled into 15 s-order themes and then merged into five aggregated dimensions: Personnel Capability, Management Capability, Organizational Capability, Culture and Governance Capability, and Strategy and Planning Capability. The study is, to the best of the authors’ knowledge, the first to categorize all relevant human-related capabilities for successful BDA application. As such, it not only provides the scientific basis for further research, but also serves as a useful overview of the critical factors for BDA use in decision-making processes.

Business Intelligence and Business Value in Organisations: A Systematic Literature Review

Organisations must derive adequate business value (BV) from Business Intelligence (BI) adoption to retain their profitability and long-term sustainability. Yet, the nuances that define the realisation of BV from BI are still not understood by many organisations that have adopted BI. This paper aims to foster a deeper understanding of the relationship between Business Intelligence (BI) and business value (BV) by focusing on the theories that have been used, the critical factors of BV derivation, the inhibitors of BV, and the different forms of BV. To do this, a systematic literature review (SLR) methodology was adopted. Articles were retrieved from three scholarly databases, namely Google Scholar, Scopus, and Science Direct, based on relevant search strings. Inclusion and exclusion criteria were applied to select ninety-three (93) papers as the primary studies. We found that the most used theoretical frameworks in studies on BI and BV are the Resource-Based View (RBV), Dynamic Capabilities Theory (DCT), Technology-Organisation-Environment (TOE), and Contingency Theory (CON). The most acknowledged critical factors of BV are skilled human capital, BI Infrastructure, data quality, BI application and usage/data culture, BI alignment with organisational goals, and top management support. The most acclaimed inhibitors of BV are data quality and handling, data security and protection, lack of BI Infrastructure, and lack of skilled human resource capital, while customer intelligence is the most acknowledged form of BV. So far, many theories that are relevant to BI and BV, critical factors, inhibitors, and forms of BV were marginally mentioned in the literature, requiring more investigations. The study reveals opportunities for future research that can be explored to gain a deeper understanding of the issues of BV derivation from BI. It also offers useful insights for adopters of BI, BI researchers, and BI practitioners.

Social capital in agribusiness: an exploratory investigation from a supply chain perspective during the COVID-19 crisis

Purpose

The COVID-19 pandemic has badly affected the global economy. The use of social capital as a resource to diversify agribusiness to get more customers and improve the agricultural supply chain is a considerable issue to explore. This study aims to develop a comprehensive measurement of social capital and examine its effect on the intention to diversify agribusiness. From a supply chain perspective, it uses theory of planned behavior (TPB) and resource-based view (RBV).

Design/methodology/approach

The study uses a mixed-methods approach. In-depth interviews, focus group discussions and surveys are used. Structural equation modeling on a sample of 465 respondents in Vietnam was employed to examine the hypothesized relationships.

Findings

An integrative measurement scale of social capital from an agricultural supply chain perspective is suggested. The study also shows significant causal relationships amongst social capital, motives, TPB's determinants and the intention to diversify agribusinesses in light of supply chain perspectives.

Originality/value

The study offers a significant contribution to the existing body of knowledge in the literature on social capital, motives, TPB, RBV and supply chain perspectives. The study was executed in Vietnam, where most farmers are smallholders, family business owners or micro-scale entrepreneurs in agriculture.

Benchmarking the practices of flexibility with maturity models and frameworks of organizational capabilities

Purpose

Organizational capabilities are crucial to achieve the objectives. A plethora of maturity models is available to guide organizational capabilities that create a perplexing situation about what stuff to improve and what to leave. Therefore, a unified maturity model addressing a wide range of capabilities is a necessity. This paper establishes that a flexibility maturity model is an unified model containing the operational, strategic and human capabilities.

Design/methodology/approach

This paper does a comparative analysis/benchmarking studies of different maturity models/frameworks widely used in the information technology (IT) sector with respect to the flexibility maturity model to establish its comprehensiveness and application in the organization to handle multiple goals.

Findings

This study confirms that the flexibility maturity model has the crucial elements of all the maturity models. If the organizations use the flexibility maturity model, they can avoid the burden of complying with multiple ones and become objective-driven rather than compliance-driven.

Research limitations/implications

The maturity models used in information technology sectors are used. This work will inspire other maturity models to adopt flexibility phenomena.

Practical implications

The comparative analysis will give confidence in application of flexibility framework. The business environment and strategic options across organizations are inherently different that the flexibility maturity model well handles.

Social implications

A choice is put to an organization to see the comparison tables produced in this paper and choose the right framework according to the prevailing business situation.

Originality/value

This is the first study that makes a conclusion based on comparative benchmarking of existing maturity models.

Sustainable Competitive Advantage Driven by Big Data Analytics and Innovation

Big data analytics (BDA) is one of the main pillars of Industry 4.0. It has become a promising tool for supporting the competitive advantages of firms by enhancing data-driven performance. Meanwhile, the scarcity of resources on a worldwide level has forced firms to consider sustainable-based performance as a critical issue. Additionally, the literature confirms that BDA and innovation can enhance firms’ performance, leading to competitive advantage. However, there is a lack of studies that examine whether or not BDA and innovation alone can sustain a firm’s competitive advantage. Drawing on previous studies and dynamic capability theory, this study proposes that big data analytics capabilities (BDAC), supported by a high level of data availability (DA), can improve innovation capabilities (IC) and, hence, lead to the development of a sustainable competitive advantage (SCA). This study examines the proposed hypotheses by surveying 117 manufacturing firms and analyzing responses via partial least squares–structural equation modeling (PLS-SEM) statistical software. Findings reveal that BDAC relies significantly on the degree of DA and has a significant role in increasing IC. Furthermore, the analysis confirms that IC has a significant and direct effect on a firm’s SCA, while BDAC has no direct effect on SCA. This study provides valuable insights for manufacturing firms to improve their sustainable business performance and theoretical and practical insights into BDA implementation issues in attaining sustainability in processes.