Search results

1 – 10 of 651
To view the access options for this content please click here
Article
Publication date: 6 August 2020

Qasim Ali Nisar, Nadia Nasir, Samia Jamshed, Shumaila Naz, Mubashar Ali and Shahzad Ali

This study is undertaken to examine the antecedents and role of big data decision-making capabilities toward decision-making quality and environmental performance among…

Abstract

Purpose

This study is undertaken to examine the antecedents and role of big data decision-making capabilities toward decision-making quality and environmental performance among the Chinese public and private hospitals. It also examined the moderating effect of big data governance that was almost ignored in previous studies.

Design/methodology/approach

The target population consisted of managerial employees (IT experts and executives) in hospitals. Data collected using a survey questionnaire from 752 respondents (374 respondents from public hospitals and 378 respondents from private hospitals) was subjected to PLS-SEM for analysis.

Findings

Findings revealed that data management challenges (leadership focus, talent management, technology and organizational culture for big data) are significant antecedents for big data decision-making capabilities in both public and private hospitals. Moreover, it was also found that big data decision-making capabilities played a key role to improve the decision-making quality (effectiveness and efficiency), which positively contribute toward environmental performance in public and private hospitals of China. Public hospitals are playing greater attention to big data management for the sake of quality decision-making and environmental performance than private hospitals.

Practical implications

This study provides guidelines required by hospitals to strengthen their big data capabilities to improve decision-making quality and environmental performance.

Originality/value

The proposed model provides an insight look at the dynamic capabilities theory in the domain of big data management to tackle the environmental issues in hospitals. The current study is the novel addition in the literature, and it identifies that big data capabilities are envisioned to be a game-changer player in effective decision-making and to improve the environmental performance in health sector.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

Keywords

To view the access options for this content please click here
Article
Publication date: 1 July 2019

Lina Dagilienė and Lina Klovienė

This paper aims to explore organisational intentions to use Big Data and Big Data Analytics (BDA) in external auditing. This study conceptualises different contingent…

Abstract

Purpose

This paper aims to explore organisational intentions to use Big Data and Big Data Analytics (BDA) in external auditing. This study conceptualises different contingent motivating factors based on prior literature and the views of auditors, business clients and regulators regarding the external auditing practices and BDA.

Design/methodology/approach

Using the contingency theory approach, a literature review and 21 in-depth interviews with three different types of respondents, the authors explore factors motivating the use of BDA in external auditing.

Findings

The study presents a few key findings regarding the use of BD and BDA in external auditing. By disclosing a comprehensive view of current practices, the authors identify two groups of motivating factors (company-related and institutional) and the circumstances in which to use BDA, which will lead to the desired outcomes of audit companies. In addition, the authors emphasise the relationship of audit companies, business clients and regulators. The research indicates a trend whereby external auditors are likely to focus on the procedures not only to satisfy regulatory requirements but also to provide more value for business clients; hence, BDA may be one of the solutions.

Research limitations/implications

The conclusions of this study are based on interview data collected from 21 participants. There is a limited number of large companies in Lithuania that are open to co-operation. Future studies may investigate the issues addressed in this study further by using different research sites and a broader range of data.

Practical implications

Current practices and outcomes of using BD and BDA by different types of respondents differ significantly. The authors wish to emphasise the need for audit companies to implement a BD-driven approach and to customise their audit strategy to gain long-term efficiency. Furthermore, the most challenging factors for using BDA emerged, namely, long-term audit agreements and the business clients’ sizes, structures and information systems.

Originality/value

The original contribution of this study lies in the empirical investigation of the comprehensive state-of-the-art of BDA usage and motivating factors in external auditing. Moreover, the study examines the phenomenon of BD as one of the most recent and praised developments in the external auditing context. Finally, a contingency-based theoretical framework has been proposed. In addition, the research also makes a methodological contribution by using the approach of constructivist grounded theory for the analysis of qualitative data.

Details

Managerial Auditing Journal, vol. 34 no. 7
Type: Research Article
ISSN: 0268-6902

Keywords

To view the access options for this content please click here
Article
Publication date: 3 June 2020

Francesco Ciampi, Giacomo Marzi, Stefano Demi and Monica Faraoni

Designing knowledge management (KM) systems capable of transforming big data into information characterised by strategic value is a major challenge faced nowadays by firms…

Abstract

Purpose

Designing knowledge management (KM) systems capable of transforming big data into information characterised by strategic value is a major challenge faced nowadays by firms in almost all industries. However, in the managerial field, big data is now mainly used to support operational activities while its strategic potential is still largely unexploited. Based on these considerations, this study proposes an overview of the literature regarding the relationship between big data and business strategy.

Design/methodology/approach

A bibliographic coupling method is applied over a dataset of 128 peer-reviewed articles, published from 2013 (first year when articles regarding the big data-business strategy relationship were published) to 2019. Thereafter, a systematic literature review is presented on 116 papers, which were found to be interconnected based on the VOSviewer algorithm.

Findings

This study discovers the existence of four thematic clusters. Three of the clusters relate to the following topics: big data and supply chain strategy; big data, personalisation and co-creation strategies and big data, strategic planning and strategic value creation. The fourth cluster concerns the relationship between big data and KM and represents a ‘bridge’ between the other three clusters.

Research limitations/implications

Based on the bibliometric analysis and the systematic literature review, this study identifies relevant understudied topics and research gaps, which are suggested as future research directions.

Originality/value

This is the first study to systematise and discuss the literature concerning the relationship between big data and firm strategy.

Details

Journal of Knowledge Management, vol. 24 no. 5
Type: Research Article
ISSN: 1367-3270

Keywords

To view the access options for this content please click here
Article
Publication date: 10 December 2018

Marcello Mariani, Rodolfo Baggio, Matthias Fuchs and Wolfram Höepken

This paper aims to examine the extent to which Business Intelligence and Big Data feature within academic research in hospitality and tourism published until 2016, by…

Abstract

Purpose

This paper aims to examine the extent to which Business Intelligence and Big Data feature within academic research in hospitality and tourism published until 2016, by identifying research gaps and future developments and designing an agenda for future research.

Design/methodology/approach

The study consists of a systematic quantitative literature review of academic articles indexed on the Scopus and Web of Science databases. The articles were reviewed based on the following features: research topic; conceptual and theoretical characterization; sources of data; type of data and size; data collection methods; data analysis techniques; and data reporting and visualization.

Findings

Findings indicate an increase in hospitality and tourism management literature applying analytical techniques to large quantities of data. However, this research field is fairly fragmented in scope and limited in methodologies and displays several gaps. A conceptual framework that helps to identify critical business problems and links the domains of business intelligence and big data to tourism and hospitality management and development is missing. Moreover, epistemological dilemmas and consequences for theory development of big data-driven knowledge are still a terra incognita. Last, despite calls for more integration of management and data science, cross-disciplinary collaborations with computer and data scientists are rather episodic and related to specific types of work and research.

Research limitations/implications

This work is based on academic articles published before 2017; hence, scientific outputs published after the moment of writing have not been included. A rich research agenda is designed.

Originality/value

This study contributes to explore in depth and systematically to what extent hospitality and tourism scholars are aware of and working intendedly on business intelligence and big data. To the best of the authors’ knowledge, it is the first systematic literature review within hospitality and tourism research dealing with business intelligence and big data.

Details

International Journal of Contemporary Hospitality Management, vol. 30 no. 12
Type: Research Article
ISSN: 0959-6119

Keywords

To view the access options for this content please click here
Article
Publication date: 8 February 2021

Nikolaos Stylos, Jeremy Zwiegelaar and Dimitrios Buhalis

Dynamic, volatile, and time-sensitive industries, such as tourism, travel and hospitality require agility and market intelligence to create value and achieve competitive…

Abstract

Purpose

Dynamic, volatile, and time-sensitive industries, such as tourism, travel and hospitality require agility and market intelligence to create value and achieve competitive advantage. The aim of the current study is to examine the influence of big data (BD) on the performance of service organizations and to probe for a deeper understanding of implementing BD, based on available technologies.

Design/methodology/approach

An ethnographic study was conducted following an abductive approach. A primary qualitative research scheme was used with 35 information technology and database professionals participating in five online focus groups of seven participants each. Analytical themes were developed simultaneously with the literature being revisited throughout the study to ultimately create sets of common themes and dimensions.

Findings

BD can help organizations build agility, especially within dynamic industries, to better predict customer behavioral patterns and make tailor-made propositions from the BD. An integrated BD-specific framework is proposed to address value according to the dimensions of need, value, time and utility.

Research limitations/implications

Little research exists on the key drivers of BD use for dynamic, real-time and agile businesses. This research adds to the developing literature on BD applications to support organizational decision-making and business performance in the tourism industry.

Originality/value

This study responds to scholars’ recent calls for more empirical research with contextual understanding of the use of BD to add value in marketing intelligence within business ecosystems. It delineates factors contributing to BD value creation and explores the impacts on the respective service encounters.

Details

International Journal of Contemporary Hospitality Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-6119

Keywords

To view the access options for this content please click here
Article
Publication date: 5 October 2020

Surabhi Verma, Vibhav Singh and Som Sekhar Bhattacharyya

Today, big data (BD) is considered as a crucial investment for firms to stay competitive. However, the human resource (HR) function within small- and medium-sized…

Abstract

Purpose

Today, big data (BD) is considered as a crucial investment for firms to stay competitive. However, the human resource (HR) function within small- and medium-sized enterprises (SMEs) has been slow to adopt this innovation. Drawing on the organizational learning theory (OLT), this study aims to propose that BD can improve HR functions, especially of SMEs, thereby yielding them a competitive edge.

Design/methodology/approach

This study analyzed unstructured data from 41 journal papers, based on which, a conceptual framework was developed. Further, this framework was validated with responses collected from 148 SMEs in India.

Findings

Bibliometric analysis and results of partial least squares techniques revealed that better BD quality is needed to improve HR practices, human resource service quality (HRSQ) and innovation competency of SMEs.

Research limitations/implications

This paper contributes to the extant literature by considering strategic management theories such as resource-based view and OLT to evaluate BDA’s effect on organizational functional practices such as HR and HRSQ.

Practical implications

In Indian SMEs, BD quality has a substantial effect on BD HR practices and HRSQ. However, these factors influence can constructively impact SMEs, if SMEs are open to organizational change, whereby they need to develop technical skills and competencies of the HR professionals.

Originality/value

Though BD research works have shown exponential growth in recent times, scholarly empirical research investigating BD’s impact upon human resource management (HRM) is scarce. The present study appraises extant literature on BD in HRM.

Details

International Journal of Organizational Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1934-8835

Keywords

To view the access options for this content please click here
Article
Publication date: 13 January 2020

Mohamad Abu Ghazaleh and Abdelrahim M. Zabadi

Internet of things (IoT) and big data (BD) could change how the societies function. This paper explores the role of IoT and BD and their impact on customer relationship…

Abstract

Purpose

Internet of things (IoT) and big data (BD) could change how the societies function. This paper explores the role of IoT and BD and their impact on customer relationship management (CRM) investments in modern customer service. The purpose of this paper is to develop an analytic hierarchy planning framework to establish criteria weights and to develop a general self-assessment model for determining the most important factors influencing the IoT and BD investment in CRM. The authors found that most studies have focused on conceptualizing the impact of IoT without BD and with limited empirical studies and analytical models. This paper sheds further light on the topic by presenting both IoT and BD aspects of future CRM.

Design/methodology/approach

The analytic hierarchy process (AHP) methodology is used to weight and prioritize the factors influencing the IoT and BD investment in modern CRM in the service industry. The AHP framework resulted in a ranking of 21 sustainability sub-factors based on evaluations by experienced information technology and customer service professionals.

Findings

The paper provides significant insight on the new frontier of CRM, focusing on the use of IoT and BD and the respective solutions to address them were identified. This study primarily contributes in providing the process of effectively managing and implementing IoT and BD in big businesses by identifying the connecting link between firms and customers.

Practical implications

The understanding of new frontier of CRM connective via IoT and BD can solve the dilemmas and challenges linked to the practice of implement IoT and BD in the information systems field. The study provides valuable information and critical analysis of IoT and BD with regard to the integration of CRM. Finally, this study further provides directions for future researchers.

Originality/value

IoT and BD are a growing phenomenon, which business decision-makers and information professionals need to consider seriously to properly ascertain the modern CRM dimensions in the digital economies. They also should embrace the proper CRM innovation, which is powered by IoT and BD, and discover how IoT and BD can bring the next level of maturity to CRM “CRM of everything.”

Details

International Journal of Organizational Analysis, vol. 28 no. 1
Type: Research Article
ISSN: 1934-8835

Keywords

To view the access options for this content please click here
Book part
Publication date: 30 September 2020

Anam and M. Israrul Haque

The rapid increase in analytics is playing an essential role in enlarging various practices related to the health sector. Big Data Analytics (BDA) provides multiple tools…

Abstract

The rapid increase in analytics is playing an essential role in enlarging various practices related to the health sector. Big Data Analytics (BDA) provides multiple tools to store, maintain, and analyze large sets of data provided by different systems of health. It is essential to manage and analyze these data to get meaningful information. Pharmaceutical companies are accumulating their data in the medical databases, whereas the payers are digitalizing the records of patients. Biomedical research generates a significant amount of data. There has been a continuous improvement in the health sector for past decades. They have become more advanced by recording the patient’s data on the Internet of Things devices, Electronic Health Records efficiently. BD is undoubtedly going to enhance the productivity and performance of organizations in various fields. Still, there are several challenges associated with BD, such as storing, capturing, and analyzing data, and their subsequent application to a practical health sector.

Details

Big Data Analytics and Intelligence: A Perspective for Health Care
Type: Book
ISBN: 978-1-83909-099-8

Keywords

To view the access options for this content please click here
Article
Publication date: 28 March 2020

Itzhak Gnizy

While big data (BD), a transformative emerging phenomenon on its youth, plays a growing role in organizations in improving marketing decision-making, few academic works…

Abstract

Purpose

While big data (BD), a transformative emerging phenomenon on its youth, plays a growing role in organizations in improving marketing decision-making, few academic works examine the mechanism through which BD can be applied to guide future competitive advantage strategies. The purpose of this paper is to examine if BD’s predictive power helps business to business (B2B) firms selecting their intended generic (differentiation, focus, and cost leadership) strategies.

Design/methodology/approach

Drawing on the learning theory, the study proposes the use of BD as a key driver of intended strategies. Based on data from a cross-industry sample of executives, a conceptual model is tested using path and robustness analyses.

Findings

The use of BD plays a prominent role in the selection of intended future strategies in industrial markets. Additional tests demonstrate conditions of competitive intensity and strategic flexibility where BD is more and less beneficial.

Research limitations/implications

The study furthers the understanding of traditional learning and intelligence use frameworks and of contemporary future strategies drivers.

Practical implications

BD availability enables managers leveraging knowledge embedded in data-rich systems to gain predictive insights that help in guiding new strategic directions to maintain competitive advantage.

Originality/value

The study reinforces the continued applicability of Porter’s generic positioning strategies in the digital era. It addresses the paucity of research on BD in B2B context and is the first to provide theoretical and practical reflections on how BD utilization influences industrial intended strategies. The study strengthens contemporary managerial views defending that data drive strategies rather than the opposite.

Details

Journal of Business & Industrial Marketing, vol. 35 no. 7
Type: Research Article
ISSN: 0885-8624

Keywords

To view the access options for this content please click here
Article
Publication date: 24 October 2019

Sandeep Jagtap and Linh Nguyen Khanh Duong

Recently, the concept of big data (BD) has evolved and started to play an essential role in the advancement of new product development (NPD) in various sectors…

Abstract

Purpose

Recently, the concept of big data (BD) has evolved and started to play an essential role in the advancement of new product development (NPD) in various sectors contributing to value creation, idea generation and competitive advantage. However, limited research has been done on how the food industry can exploit BD to improve the processes involved in NPD. The purpose of this paper is to understand the use of BD in new food product development. It helps to find relevant information and integrate sustainability to the early stages of the NPD process in the food industry.

Design/methodology/approach

This research illustrates a case study of a beverage company wherein they used BD analytics to support their NPD team to launch a two-litre lemonade drink in the market for their retailer with less than 5 g sugar per 100 ml in the shortest possible time.

Findings

The use of BD helps to reduce NPD costs and time without affecting the taste and on par with competitor’s products.

Originality/value

The research can support NPD professionals through the application of BD analytics to bring products at lower costs to the market as quickly as possible.

Details

British Food Journal, vol. 121 no. 11
Type: Research Article
ISSN: 0007-070X

Keywords

1 – 10 of 651